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The Smartness Barometer -
How to quantify smart grid projects and
interpret results
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A EURELECTRIC paper
F e b r u a r y 2 0 1 2

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Dépôt légal: D/2012/12.105/8

The Smartness Barometer – How to quantify smart
grid projects and interpret results
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DSO Coordination for smart grid Deployment
LANDECK Erik (DE) Chair
BIRKNER Peter (DE); BREUER Andreas (DE); CARILLO Susana (ES); DE LICHTERVELDE Ferdinand (BE); DI
NAPOLI Mariangela (IT); DISKIN Ellen (I E); EFTHYMIOU Venizelos (CY); GLEICH Tomas (CZ); HALLBERG Per
(SE); JASPER Jörg (DE); KABS Joachim (DE); KOPONEN Ari (FI); KUDRNAC Jiri (CZ); LEFORT Michel (BE);
MERKEL Marcus (DE); MESSIAS António Aires ( PT); NORDENTOFT Niels Christian (DK); PETRONI Paola Lucia
(IT); PETTERSSON Anders (SE); POSTMA Andre (NL); REISSING Thomas (DE); ROZYCKI Artur (PL); S ANCHEZ
FORNIE Miguel Angel (ES); SCHEIDA Karl (AT); SMITH Paul (GB); TENSCHERT Walter (AT); THEISEN Thomas
(DE); VANBEVEREN Donald (BE); WEISS Bertram (AT)
Contact:
Koen Noyens, Advisor Networks Unit – knoyens@eurelectric.org

EXECUTIVE SUMMARY 5
1. INTRODUCTION – IDENTIFYING THE NEED TO QUANTIFY SMART GRIDS 6
1.1 WHY DO WE NEED QUANTIFICATION? 6
1.2 WHAT DELIVERABLES CAN BE EXPECTED FROM SUCH QUANTIFICATION? 6
1.3 WHERE TO GO WITH THE SMART GRID DEVELOPMENT: UNIVERSALLY ACCEPTED BENEFITS 8
2. SMART GRID COST-BENEFIT ANALYSIS METHODOLOGY 10
2.1 BACKGROUND 10
2.2 BRIEF OVERVIEW OF THE EPRI METHODOLOGY 11
2.3 THE DETAILED SEVEN-STEP APPROACH 12
STEP 1 – DESCRIBE THE TECHNOLOGIES, ELEMENTS AND GOALS OF THE PROJECT 13
STEP 2 – IDENTIFY THE SMART GRID FUNCTIONALITIES 15
STEP 3 – MAP EACH FUNCTIONALITY ONTO A STANDARDISED SET OF BENEFIT TYPES 17
STEP 4 – ESTABLISH THE PROJECT BASELINE 19
STEP 5 – QUANTIFY AND MONETISE THE IDENTIFIED BENEFITS AND BENEFICIARIES 21
STEP 6 – QUANTIFY AND ESTIMATE THE RELEVANT COSTS 25
STEP 7 – COMPARE COSTS TO BENEFITS 26
3. HOW TO EXTRAPOLATE PROJECT RESULTS TO THE NATIONAL LEVEL? 30
3.1 THE GRID AND ITS LIMITATIONS 30
3.2 STEPS TO EVALUATE BASE COST 31
3.3 KEY ASSUMPTIONS 32
4. CONCLUSION AND GUIDELINES 34
4.1 PROJECT LEADERS: EVALUATING A PROJECT 34
4.1.1 EVALUATING A COMPLETED PROJECT 34
4.1.2 AIDING PROJECT PLANNING 35
4.1.3 THE CRITICAL ROLE OF COST / BENEFIT ANALYSES – DEPLOYMENT PROPOSALS 36
4.2 REGULATORS & POLICYMAKERS: HOW TO MAKE INFORMED INVESTMENT DECISIONS 36
4.2.1 THE EVOLVING ROLE OF THE REGULATOR 36
4.2.2 WHAT IS A “SMART” INVESTMENT? 37
4.2.3 EXTRACTING INFORMATION FROM OTHER PROJECTS IN EUROPE AND BEYOND 37
4.3 HOW DISTRIBUTION COMPANIES AND REGULATORS CAN HELP WORK TOGETHER 38
4.4 EUROPEAN FUNDING SOLUTIONS 38

Executive Summary
‘Smart Grid’ solutions will only be considered as alternatives to conventional network
reinforcement if investors can compare such investments on a cost-benefit basis. Yet such
comparisons remain challenging for two reasons: the rapidly developing and largely untested
nature of ‘smart’ solutions and the difficulty of comparing two inherently different types of
investment both aimed at achieving the same purpose – reinforcing distribution networks to
increase capacity and improve power quality, supply security and efficiency.
This paper details the challenge facing the electricity distribution industry in evaluating smart
grid investments, both demonstration projects and large-scale deployments. It explains the need
for a consistent framework allowing for such evaluation and cost-benefit analysis so that
industry, regulators or potential investors can make informed decisions on the benefits and
effectiveness of a ‘smart’ investment.
The evaluation method presented in this document has been developed by the Electric Power
Research Institute (EPRI) and has been adapted to the smart-grid work underway in Europe.
Adjustments include neglecting steps deemed beyond the necessary scope of such an analysis,
and adopting the terminology defined by the European Commission Expert Group 1. This aims to
ensure that the methodology can be applied consistently across Europe and adheres to EU
standards currently under development.
The proposed evaluation methodology consists of seven steps, starting from a description of a
project’s goals and eventually resulting in a direct comparison of costs and benefits. The paper
describes each step and then gives practical examples from the InovGrid project, an open
platform integrating end users, public standards and vendors’ interoperable solutions, led by the
Portuguese distribution system operator EDP Distribução to inform the adaption of the
methodology for its application in Europe. The work builds on intensive collaboration between
EURELECTRIC and the European Commission’s Joint Research Centre (JRC).
The paper finds that the methodology can support distribution companies and regulators in
evaluating and comparing different types of ‘smart’ investments, communicating their results
and developing investment strategies which incorporate ‘smart’ investment options where
appropriate. The methodology can clearly help to show which technological solutions work –
and which do not. Moreover, it allows for meaningful comparisons between different types of
projects installed in different systems across Europe. Investors receive a clear idea of the value
of their initial investment; and in contrast to other approaches this methodology also pinpoints
who will benefit from the investment – a useful tool for distribution companies looking to
reassure regulators that ‘smart’ grid investments will benefit society at large.
The paper thus concludes that the described evaluation method is potentially suited to purpose,
although the authors recognise that this is an evolving field. The JRC are currently further
developing this methodology and evaluating smart grid development in Europe, and are also
engaged in reconciling EU and American terminology. In the meantime, success criteria and
realistic business cases based on intensive pilots are vital to raise awareness of smart grid
investment needs among public and private stakeholders at national and European level. The
methodology presented in this paper provides a basis for evaluating such pilots and for
extrapolating the combined contribution of several such smart grid projects to national and
European energy policy targets.
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1. Introduction – Identifying the Need to Quantify Smart Grids
1.1 Why do we need quantification?
The smart grid is an enabler, not an end in itself. It is accepted worldwide that an
implementation of smart grids is absolutely necessary in order to achieve the strategic
targets for integration of renewable energy sources in the most effective manner, a more
secure, sustainable electricity supply, optimal and efficient use of energy and full inclusion of
consumers in the electricity market.
At the same time, investments for the development of smart grids should be financially
sound. Market forces must see real financial returns in achieving these energy policy goals to
incentivise the continued significant investments which will be required over the coming
decades.
As a consequence, the quantification of costs, benefits and their allocation to the
appropriate beneficiaries is necessary to identify and mitigate business risks and encourage
investors. The process proposed is a methodological framework that will provide a
standardised approach for estimating the benefits and costs of smart grid demonstration
projects or subsequent larger scale deployments. Policymakers, regulators and investors are
in need of such a methodology meeting the following requirements:
� A fair, consistent, repeatable and methodological approach to estimate the cost
and benefits of smart network pilot projects and related investments based on
data from smart grid field demonstration projects;
� Identification and standard definition of the various types of benefits;
� A consistent and uniform approach for all projects and deployments;
� Basic principles for developing (a) computational tool(s) that all smart grid
stakeholders could use to determine the costs and benefits of smart grid
deployments.
In outlining the thought process, approach, and underlying concepts and assumptions of the
proposed methodology, we aim to aid the attainment of these goals and would support the
creation of a computational tool to enhance the work of the users.
1.2 What deliverables can be expected from such quantification?
The adopted methodology is intended as an assessment process to be universally accepted
and consistently applied providing two separate deliverables. Both deliverables contribute to
the ‘Smartness Barometer’ concept, which captures the idea how this technological
advancement in electricity grids achieves the set strategic European policy goals:
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1. The definition of “performance indicators” quantifying the extent to which a
specific smart grid project is contributing to progress toward the “ideal smart
grid”. 1 This output reveals to what extent a project or deployment achieves the
following smart grid services (characteristics) as defined by EC expert group 1:
� Integration of new users and requirements for sustainability,
� Consumer inclusion,
� Improving market functioning and consumer service,
� Enhancing efficiency in day to day grid operation,
� Enhancing better planning of future investments, and
� Ensuring network security / control / quality of supply
An assessment framework to qualitatively capture the impact of a smart grid
project on the considered electricity system (in terms of the delivery of smart grid
services) is recognised as an important feature, but is beyond the scope of this
paper. 2 However, the authors recognise the importance of such a framework and
the complementary value it can bring to the quantitative results of a cost-benefit
analysis (CBA).
2. A “Cost and Benefit analysis” assessing the profitability of a smart grid solution and
associated investment. An essential outcome of this analysis is the identification of
the specific beneficiaries. Benefits from smart grid investments accrue throughout
the value chain from generators, suppliers and customers to society as a whole.
This is why economic regulation defining the conditions for the so-called
socialisation of a major part of the investments is key for the successful
implementation of smart grids. Too narrow a view when evaluating the cost
efficiency of smart grid investments – to be undertaken mainly by DSOs – should be
avoided.
This paper aims to outline the first step towards the effective attribution of costs
and benefits, necessary to the development of a successful market-based approach
to govern the evolution of smart grids and achieve all related strategic policy goals.
The objective is to define the methodological approach for conducting such costbenefit
analyses of smart grid projects. Moreover, it provides project leaders with
guidance in establishing a broad approach in their cost-benefit analyses for smart
grids, taking indirect benefits and social factors into consideration.
1 Important to note is that such a measurement towards the “Ideal Grid” for a specific country should be seen
as the relative and not absolute improvement. Moreover the consecutive order of functionality will not follow
the same path throughout Europe; there will be "jumps".
2 The EC Task Force has already elaborated an initial assessment approach to link benefits and indicators to
services and functionalities and evaluate the smartness of a smart grid project and the merit of its deployment.
European Commission Task Force for smart grids (2010) Expert Group 1: Functionalities of smart grid and smart
meters.
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1.3 Where to go with the smart grid development: Universally accepted benefits
In the context of this analysis, a ‘benefit’ is an impact (of a smart grid project) that is of value
to any regulated or commercial body, energy consuming households or society at large. To
gauge their magnitude and facilitate comparison, benefits should be quantified and
expressed in monetary terms.
For smart grid systems, it is well accepted that there are four fundamental categories of
benefits 3 :
� Economic – reduced costs, or increased production at the same cost, that result from
improved utility system efficiency and asset utilisation;
� Reliability and Power Quality – reduction in interruptions, service quality assistance
improvement and power quality events;
� Environmental – reduced impact of climate change and effects on human health and
ecosystems due to pollution;
� Security and Safety – improved energy security (i.e. reduced oil and gas
dependence); increased cyber security and reductions in injuries, loss of life and
property damage.
Within each of the broad categories, there are several types of benefit and by definition they
are mutually exclusive in terms of accounting for different benefit categories. However,
smart grid functionalities that lead to one type of benefit can also lead to other types of
benefits. For example, improvements that reduce distribution losses (an economic benefit)
mean that pollutant emissions are reduced as well (which is an environmental benefit).
Having identified the achieved benefits, it is very important to identify the beneficiaries in
the process. In general, benefits are reductions in costs and damages, whether to
generators, distribution system operators, consumers or to society at large. In this
evaluation process the various benefits are defined so as to avoid instances of transfer
payments between these groups of beneficiaries, to avoid mistakes in the evaluation of the
total benefits, and to illustrate benefits from the separate perspectives of each group.
Broadly speaking the beneficiaries are the following:
� Consumers: Consumers can balance or reduce their energy consumption with the
real-time supply of energy. Variable pricing will provide consumer incentives to install
their own in-home infrastructure that supports the smart grid development. The
smart grid information and communication infrastructure will support additional
services not available today.
3 EPRI (Electric Power Research Institute) (Faruqui, A., Hledik, R.) (2010). Methodological Appr oach for
Estimating the Benefits and Costs of smart grid Demonstration Projects, Palo Alto, CA: EPRI. 1020342
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� Utilities (generators, transmission system operators, distribution system operators
and suppliers): Utilities can provide more reliable energy, particularly during
challenging emergency conditions, while managing their costs more effectively
through efficiency and information which can be used for more effective
infrastructure development, maintenance and operation.
� Society: Society benefits from more reliable supplies and consistent power quality for
both domestic customers and all industrial sectors – manufacturing, services, ICT –
many of which are sensitive to power outages. Renewable energy, increased demand
efficiency, and electric vehicles or other distributed storage support will reduce
environmental costs, including society’s carbon footprint.
A benefit to any one of these stakeholders can in turn benefit the others. For example, those
benefits that reduce costs for a DSO could lower prices, or prevent price increases, for
customers. However in such cases it is vital to ensure that benefits transferred from one
party to another are not double counted. Lower costs and decreased infrastructure
requirements enhance the value of electricity to consumers. Reduced costs increase
economic activity which benefits society. Societal benefits of the smart grid can be indirect
and hard to quantify, but cannot be overlooked.
Other stakeholders also benefit from the smart grid. Regulators can benefit from the
transparency and audit-ability of smart grid information. Vendors and integrators benefit
from business and product opportunities around smart grid components and systems.
Total benefits are the sum of the benefits to utilities, consumers and society at large –
though any transfer payments between these beneficiary groups must be taken into account
and dealt with suitably. Ultimately transfer payments could be a solution to realise project
financing where the global balance is positive, but where some stakeholders clearly benefit
while others lose out.
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2. Smart Grid Cost-Benefit Analysis Methodology
2.1 Background
Over the past few years, there have been various models and constructs put forth related to
evaluating smart grid projects and related investments. The lack of a standard, commonly
accepted operator-level cost-benefit framework or system has led to few effective
investment analysis approaches. However, DSO executives and policy decision makers are in
need of such a framework.
Why is it so difficult?
Smart grid project investment analysis is particularly difficult because it
� involves a large number of technologies, programmes and operational practices;
� impacts on all the operational areas of the electricity value chain in an interlinked
way (transfer of costs and benefits);
� requires long-term vision 4 and commitment to fully implement;
� assumes active involvement of customers in using new technologies and software,
the reliability and extent of which is still highly uncertain.
Moreover, variation among European DSOs in existing grid infrastructure (e.g. current
communications and metering systems, network age and condition) or service area
characteristics (e.g. customer geographic density and consumer end-use loads) – even within
a single country – is so great that decision makers so far could not rely on existing studies
from other regions or DSOs to justify smart grid investments.
From an economic point of view, certain challenges arise when attempting to apply
traditional cost-benefit analysis in the context of smart grid investments. Evaluating smart
grid project investments can be different from traditional investment analyses:
� All benefits related to smart grid investments may not be borne by the investing
party and some additional costs required to realise a benefit may be borne by other
parties. Should these additional costs and benefits be incorporated into the analysis?
If so, how will all costs and benefits be attributed to the appropriate parties, in
modelling and analysis?
� Uncertainty with respect to the magnitude of benefit streams is not unique to smart
grids. However, some potential metrics associated with smart grids present
particularly difficult issues for accurate quantification (e.g. environmental impact,
reliable levels of response). The rationale and assumptions made for some chosen
parameters can greatly affect the outcome of the analysis.
4 In ’10 Steps to Smart Grids – EURELCTRIC DSOs’ Ten-Year Roadmap for Smart Grid Deployment in the EU’, EURELECTRIC
DSOs outline the 10 steps that are required for implementing smart grids in Europe.
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What is necessary?
Work must be done to define a methodological framework of estimating, calculating and
assessing smart grid benefits and cost, including evaluation of less quantifiable benefits.
EURELECTRIC, as a stimulator of the development of smart grids in society, takes the
opportunity to address this lack and proposes in this section a common methodological
framework that allows assessment of European smart grid project results.
The basic structure of the proposed framework relies on the work of the US Energy Power
Research Institute (EPRI). EPRI published a report in January 2010 on an approach for
evaluating the US Department of Energy’s smart grid demonstration projects. 5 It builds upon
many previous studies and represents the most comprehensive approach to smart grid
evaluation to date.
In an initiative to develop and fine-tune this methodology for the European smart grid
dimension recognising EU-specific drivers and priorities, EURELECTRIC collaborated with the
European Commission’s Joint Research Centre to use a running smart grid project as a case
study. The InovGrid project of the Portuguese distribution system operator EDP Distribução
was selected from the JRC catalogue for application of the EPRI methodology to its full
extent. 6
Through the buy-in of the Inovgrid management and the detailed and extensive preliminary
data provision over a period of six months, real project experience proved invaluable in
illustrating the steps of the cost-benefit analysis methodology. For the first time, the focus of
the smart grid evaluation debate lay on sound and tangible estimated costs and benefits
rather than addressing the theoretical framework in isolation.
However the authors remain fully aware of the limits of such a case study and urge readers
to bear this in mind. A single experience in smart grid operations cannot be used as a
universal reference to assess the impact of such solutions on the future power system. Given
the wide variety of existing pre-conditions for European utilities implementing smart grid
projects, variation with alternative solutions deployed will always exist.
2.2 Brief overview of the EPRI methodology
The EPRI approach provides a framework for evaluating economic, environmental, reliability,
and safety and security benefits from the perspective of the involved stakeholders. It also
indicates the level of certainty of achieving estimated benefits and focuses on identifying
benefits that are directly measurable, easy to understand and quantifiable in monetary
terms.
5 EPRI (Electric Power Research Institute) (Faruqui, A., Hledik, R.) (2010). Methodological Approach for Estimating the
Benefits and Costs of Smart Grid Demonstration Projects, Palo Alto, CA: EPRI. 1020342
6 The methodology is the first case study that has been chosen. Other smart grid case studies from the JRC catalogue will be
tested in the near future.
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The approach outlined in the report can be applied in generic form to most smart grid
investments. The EPRI methodology can be divided into three major steps as follows:
1. Characterisation of the project
2. Quantification and monetisation of benefits
3. Comparison of costs and benefits
The joint effort between Members of EURELECTRIC, JRC and EDP Distribução resulted in a
methodological framework to systematically estimate the different benefits of smart grid
projects in seven steps. The methodology focuses on the identification and definition of
benefits through a sequential, logical estimation process.
Drawing from the InovGrid case study and experiences, the logical flow of the developed
methodological framework is shown in the figure below, which outlines the proposed
process for identifying benefits and estimating their monetary value. The final methodology
foresees seven building blocks:
2.3 The detailed seven-step approach
Figure 1 – Cost-Benefit Analysis Framework
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This section describes the overall seven-step structure of the cost-benefit methodological
framework. Each step covers the underlying principles and recommendations on how the
framework should be used. Throughout the section examples from the InovGrid project
illustrate how the methodology can be applied in practice. We suggest the reader
alsoconsult the complementary JRC report 7 ‘Guidelines for conducting a cost-benefit analysis
of smart grid projects’, which covers more examples and addresses quantitative aspects (in
its annexes) related to the calculation and estimation of costs/benefits.
STEP 1 – Describe the technologies, elements and goals of the project
The initial step in estimating the benefits of a project is to describe it by identifying the goal
of the project and the smart grid assets.
A. Goal
As a first step it is important to describe the high-level goals of the overall solution and how
the installed components will allow the objectives of the project to be addressed. It should
be clear who the stakeholders are and how their needs are addressed.
InovGrid illustration – Goal of the project
The INOVGRID project 8 aims at replacing the current LV meters with electronic devices called EDP Boxes
(EB), using AMM (Automated Meter Management) standards. The EB is a gateway to energy management,
which includes the functions of smart metering, has the capacity of local interaction with other devices
through an interface Home Area Network (HAN).
Local control equipment (DTC -Distribution Transformer Controller) in secondary substations performs
automation functions for the distribution transformer and collects information from the EDP Boxes and
sends them to the upstream systems.
The project will integrate distributed generation (DG), Electric vehicles charging network and demand side
management in network operation, providing a new set of system ancillary services. The project aims at
demonstrating that a properly developed integration tool can facilitate the integration of DG, a more
efficient use of energy and a reduction in CO2 emissions, without compromising security of operation and
quality of supply.
7 European Commission – Joint Research Centre Institute for Energy and Transport, 2012. Guidelines for
conducting cost-benefit analysis of smart grid projects”, Joint Research Centre Reference Report, February
2012.
8 http://www.inovcity.pt/en/Pages/homepage.aspx
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B. Smart grid assets
Figure 2 – InovGrid project – technical architecture
Smart grid assets consist of the technologies, devices, and equipment that are purchased,
installed, and made operational for the smart grid project. Assets could include, for example,
in-home displays, load control devices, voltage control devices, a communications network
and associated infrastructure, cyber security upgrades, enhanced fault detection technology
or advanced metering infrastructure.
It is important to identify what specific assets are installed, where they are installed, how
the system is affected and what they do.
InovGrid illustration - What smart grid technologies are installed?
Distribution
Transformer
Controller (DTC)
DTC Cell Module –
Distribution
Automation
DTC Power Quality
Module
Local control equipment will be installed in distribution transformer
stations, the main components being a measurement module, control
module and communications module. The main functions are, collecting
data from EB and MV/LV substation, data analysis functions and grid
monitoring.
Module that enables turning on and off remotely or locally, the various
independent circuits of the MV-LV substation.
Module that allows the recording and reporting of the quality characteristic
values of the wave voltage (rms value, flicker, voltage dips, harmonics),
providing information and generating alarm events
Furthermore, assets can include energy resources that interact with the grid, including
distributed generation, stationary electricity storage, plug-in electric vehicles, and smart
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appliances. These resources can generally communicate and make business decisions or
receive commands based on signals from the grid, customers or other operators like
retailers, using either integrated technology or other assets of the project.
Each of the deployed assets will produce a unique list of possible functionalities. Detailed
fact sheets of the installed products can also help to define those functionalities and
illustrate their role in the project.
STEP 2 – Identify the smart grid functionalities
Once identified, these assets can be integrated to enhance the delivery and use of electricity
by enabling smart grid functionalities. Functionalities describe the enhanced capabilities
provided by smart grid assets for delivering electricity across the grid from power plants to
consumers.
Expert Group 1 (EG1) of the EC Smart Grid Task Force has defined the smart grid in terms of
six high-level characteristics (referred to in 1.2 above) that are delivered through 33 specific
network functionalities.
A. Enabling the network to integrate users with new requirements
1. Facilitate connections at all voltages / locations for any kind of devices
2. Facilitate the use of the grid for the users at all voltages/locations
3. Use of network control systems for network purposes
4. Update network performance data on continuity of supply and voltage quality
B. Enhancing efficiency in day-to-day grid operation
5. Automated fault identification / grid reconfiguration reducing outage times
6. Enhance monitoring and control of power flows and voltages
7. Enhance monitoring and observability of grids down to low voltage levels
8. Improve monitoring of network assets
9. Identification of technical and non technical losses by power flow analysis
10. Frequent information exchange on actual active/reactive generation/consumption
C. Ensuring network security, system control and quality of supply
11. Allow grid users and aggregators to participate in ancillary services market
12. Improved operation schemes for voltage/current control taking into account ancillary services
13. Intermittent sources of generation to contribute to system security
14. System security assessment and management of remedies
15. Monitoring of safety particularly in public areas
16. Solutions for demand response for system security in required time
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D. Better planning of future network investment
17. Better models of DG, storage, flexible loads, ancillary services
18. Improve asset management and replacement strategies
19. Additional information on grid quality and consumption by metering for planning
E. Improving market functioning and customer service
20. Participation of all connected generators in the electricity market
21. Participation of VPPs and aggregators in the electricity market
22. Facilitate consumer participation in the electricity market
23. Open platform (grid infrastructure) for EV recharge purposes
24. Improvement to industry systems (for settlement, system balance, scheduling)
25. Support the adoption of intelligent home / facilities automation and smart devices
26. Provide to grid users individual advance notice for planned interruptions
27. Improve customer level reporting in occasion of interruptions
F. Enabling and encouraging stronger and more direct involvement of consumers in
their energy usage and management
28. Sufficient frequency of meter readings
29. Remote management of meters
30. Consumption/injection data and price signals by different means
31. Improve energy usage information
32. Improve information on energy sources
33. Availability of individual continuity of supply and voltage quality indicators
The functionalities defined by EG1 describe in broad terms the different ways in which smart
grid technology can be used to improve the reliability, efficiency, operation, and security of
the electrical grid. Depending on which smart grid assets are installed, how they are
combined and how they are operated in a system, different functionalities can be triggered.
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InovGrid illustration - What can the smart grid technologies do?
The DTC Cell Module, which is a very specific component of the InovGrid project, allows triggering the
Distribution Automation functionality. Looking to the functionalities defined by EG1 of the TF smart
grids, following functionalities out of the list are activated
(3) Use of network control systems for network purposes
(5) Automated fault identification/grid reconfiguration reducing outage times
Figure 3 – Mapping assets to functionalities: overview matrix
Figure 4 – Mapping assets to functionalities: detail
STEP 3 – Map each functionality onto a standardised set of benefit types
As assets are mapped to functionalities, functionalities are mapped to benefits. Each of the
triggered functionalities has to be considered to determine if and how they can provide any
of the smart grid benefits.
The general categories of benefits include improved economic performance (such as
reduced operating and maintenance costs), enhanced reliability, reduced emissions and
greater energy security. The EPRI methodology has developed a complete list of four benefit
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categories comprising 22 specific benefits. This has been adopted as a comprehensive list 9
that is also suitable for use in Europe:
Economic
Reliability
Improved Asset
Utilization
T&D Capital Saving
T&D O&M Savings
Optimized Generator Operation (Utilities)
Deferred Generation Capacity Investments (Utilities)
Reduced Ancillary Service Cost (Utilities)
Reduced Congestion Cost (Utilities)
Deferred Transmission Capacity Investments (Utilities)
Deferred Distribution Capacity Investments (Utilities)
Reduced Equipment Failures (Utilities)
Reduced Distribution Equipment Maintenance Cost (Utilities)
Reduced Distribution Operation Cost (Utilities)
Reduced Meter Reading Cost (Utilities)
Theft Reduction Reduced Electricity Theft (Utilities)
Energy Efficiency Reduced Electricity Losses (Consumer)
Recovered Revenue Detection of anomalies relating Contracted Power (Utilities)
Electricity Cost Savings Reduced Electricity Cost (Consumer)
Power Interruptions
Power Quality
Environmental Air Emissions
Security Energy Security
Reduced Sustained Outages (Consumer)
Reduced Major Outages (Consumer)
Reduced Restoration Cost (Utilities)
Reduced Momentary Outages (Consumer)
Reduced Sags and Swells (Consumer)
Reduced CO2 Emissions (Society)
Reduced Sox, Nox, and PM-10 Emissions (Society)
Reduced Oil Usage (Society)
Reduced Wide-scale Blackouts (Society)
Table 1 – List of Benefits
The relationship between the smart grid functionalities and the expected benefits should
then be illustrated in a functionalities-benefits matrix.
9 These benefits differ from the ones published by ERGEG and the EC Task Force smart grids. These benefits can
easily be monetized. For a description of the benefits, we refer to Annex I of the JRC report ‘Guidelines for
conducting a cost-benefit analysis of smart grid projects’.
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InovGrid illustration - What benefit results from the technology?
The ’Use of network control systems for network purposes’ (3) smart grid functionality can deliver a
benefit like Reduced Distribution Operations Costs: it refers to meter or repair operations that can
now be performed remotely instead of sending service workers.
The ‘Automated fault identification/grid reconfiguration reducing outage times’ (5) smart grid
functionality can deliver a benefit like Reduced Restoration Costs: by more quickly and precisely
locating an clearing faults, field service workers can spend less time searching for the cause of the
faults. It is also possible that by better isolating the fault, less damage occurs.
Matching each functionality with one or more benefits from the list requires thorough analysis and a
good deal of thinking.
Figure 5 – Mapping functionalities to benefits
STEP 4 – Establish the project baseline
The implementation of a smart grid project incurs costs and delivers benefits that have to be
compared with the scenario had the project not taken place. It is therefore essential for any
cost-benefit analysis to define and characterise the baseline against which all other aspects
of the analysis are compared.
The baseline encompasses all the quantitative data that is needed to represent the current
situation. Since all cost-benefit analyses are based on measuring or assessing change, two
cases are required to measure the change that is to be assessed. The EPRI methodology puts
forward the two types of states of the system necessary to start the evaluation:
19

� The Business as Usual (BAU) scenario 10 : the baseline (or control) conditions that
reflect what the system condition would have been without the smart grid system in
place
� The smart grid scenario: The realised and measured conditions with the smart grid
system installed
The quantification of a specific benefit or cost, as explained in the next step, is then the
incremental change in that cost and benefit metric between BAU and the smart grid
scenario.
There might be a number of candidate baselines for each benefit, and the smart grid project
will have to select the baseline that is viewed as the most representative of the state of the
grid had the smart grid project not been implemented. Important factors that have to be
taken into account when defining the baseline include, inter alia, extreme events 11 , inflation,
demand growth, load growth, evolution of electricity prices and final date of the project.
InovGrid illustration – set the right baseline to measure the benefit
Example benefit 1: Reduced Distribution Maintenance cost
BAU condition Direct costs related to:
- the maintenance of transformers, secondary substations
- the breakdown of transformers
- the theft of transformers at secondary substations
Smart Grid condition Estimated reduction in maintenance with InovGrid infrastructure:
- remotely control and monitor asset condition and utilization,
avoiding side visit related costs
- better information on power flow and distribution load, implying
less breakdown of transformers
- sensors on the secondary substations that warn in case of the
decreasing thefts
Example benefit 2: Reduced Technical Losses
BAU condition Estimation of the total amount of losses (in %) at Distribution and
Transmission level, corresponding to total monetized value for the
considered period.
Smart Grid condition Estimated reduction in technical losses due to:
- energy efficiency (consumption reduction and peak load
transfer)
- new capacity to control the reactive power level
10
The analysis should not be always based on a single BAU scenario; it can be useful to consider a limited
number of options for the BAU scenario.
11
“Extreme events” could not be assumed in modelling a baseline scenario due to their sporadic and
unpredictable nature. However, if an extreme event occurs over the period where the smart grid project was in
operation and measurements were made, this will likely impact on the results of the “Smart Grid Scenario”.
Thus, if possible, the impact of the same event should be built into the BAU scenario. The accuracy of this
would depend on there being historical evidence of how the system has dealt with such events in the past.
20

STEP 5 – Quantify and monetise the identified benefits and beneficiaries
Quantifying the benefits in this case means “measuring the effects or outcomes that the
project will deliver.” The challenge lies in evaluating these effects in monetised terms. The
metrics needed to monetise the benefits may be quantified in terms of physical units ( e.g.
reduction in kWh). The quantified benefits should in turn be monetised by applying a cost
per unit (e.g. €/kWh).
Every identified benefit requires an approach and data for the calculation of both the BAU
condition and the smart grid condition. The incremental monetary change between both
conditions can in general be expressed as:
Value (€) = [Condition]BAU – [Condition]SG
InovGrid illustration – what is the benefit worth?
Reduced Local Meter Operations Costs (Benefit)
Rationale:
Figure 6 – Reduced Local Meter Operations Cost (Benefit)
� The BAU condition represents the total costs related to local meter operations
without InovGrid infrastructure in place.
� The benefit is expressed as an incremental cost reduction referring to meter
operations that now can be performed remotely with InovGrid infrastructure (e.g.
change in contracted power, change of tariff plan, switching,
connection/disconnection, etc.).
� It is assumed a communications success rate of around 95%.
21

A. Externalities - Parameter Values for Monetisation
When calculating benefits, it is clear that some benefits, such as reduced emissions or
reduced damages to end-users from power interruptions, are difficult to monetise. A project
would, for example, need to estimate the emissions before the project on the electricity
generated for the area under study, and after the smart grid investments are in place. In this
respect the choice of the right parameter values is important. 12
On top of that, the project may deliver benefits that cannot be accurately monetised. These
benefits include, inter alia, new services and products offered, vehicle-to-grid services, job
creation and new business opportunities. In general, they benefit the public or society at
large. They should not be overlooked and should be taken, quantitatively or qualitatively,
into account in the total smart grid project assessment.
The following benefits require specific attention:
Reliability and power quality benefits
To monetise reliability and power quality benefits, the most common approach is to apply
the cost per un-served kilowatt-hour (or customer hour depending on regulatory
framework) from the interruption-cost estimates. Benefits calculated from this approach are
a direct function of the change in the number of interrupted hours (from what is
experienced under a baseline conditions to what is experienced after smart grid investments
are made). 13
Environmental benefits
To the extent that they can be reasonably quantified (and that they can be attributed to the
smart grid investment), environmental benefits should be quantified, monetised in the costbenefit
framework and designated a societal benefit. In some cases, environmental benefits
can be estimated based on the average cost of installing remediation equipment as an
alternative, such as emission reduction technology. In other cases, there are market
instruments from which the benefits can be readily calculated (e.g. spot and future values of
allowances traded in market exchanges).
Societal benefits
From an economist’s viewpoint, substantial benefits accrue to consumers and, more
interestingly, to third parties because of positive externalities created from a smart grid
implementation. The analysis should include a unique list of societal benefits and internalise
all externalities, thereby understanding and valuating the community welfare effects.
System operators and regulators should ultimately include benefits with a broader societal
impact in their assessments. Some typical benefits include:
12
Annex II of the JRC report offers an approach for quantifying and monetizing smart grid benefits illustrated
by parameters.
13
Sullivan, M.M., Mercurio, M., Schellenberg, J. (2009) “Estimated Value of Service Reliability for Electric Utility
Customers in the United States,” Report LBNL-2132E, prepared for the Office of Electricity Delivery and Energy
Reliability, U.S. Department of Energy, Berkeley, CA: Lawrence Berkeley National Laboratory, June 2009.
22

� Environmental and health benefits due to decreased peak electricity generation and
the associated release of pollutants into the atmosphere ( as peaking capacity is
generally carbon-intensive rather than renewable).
� New industries can develop to deliver a whole new spectrum of products ( prepayment,
demand response programmes), energy efficiency applications and new
technologies (smart appliances, storage, etc.) . Smart grid projects could leverage
innovation in distinct areas like electric vehicles, renewables, distributed generation
and energy efficiency.
� Sustained job creation: including direct utility jobs created by smart grid programmes
(new skills, jobs created in the broad “energy services” sector), non-utility smart-grid
related jobs (contractors, technology design, manufacturing, for example in new
industry lines like plug-in electric hybrid vehicles).
B. Beneficiaries
When conducting the analysis, it is of extreme importance to take into consideration the
complete value chain and all the effects that a society experiences from producing and
consuming electricity in the smart grid deployment, and not only the effects on the
generators that produce electricity and their registered consumers who consume
electricity. Benefits need to be clearly allocated to their beneficiaries.
InovGrid illustration - Beneficiaries
Figure 7– Benefits accrue through the value chain: ESCO, DSO, Consumer, Producer, Regulator
23

Where smart grid investments are to be made by distribution companies, it is vital that
regulators bear the relevant beneficiaries in mind. Increasingly there are examples of the
DSO bearing significant costs which will be recovered by other stakeholders than the DSO
who made the investment. This is for example the case in the cost-benefit analysis
performed by the Irish energy regulator (CER) , facilitated by ESB Networks, of a national
smart metering rollout based on a large-scale test deployment over two years. As illustrated
below, although there was a significant net benefit to society, the DSO experienced a
financial loss.
Background:
Figure 8 - NPV benefits of smart metering in Ireland (€m), as determined by the Irish CER
This study was based on the full deployment of smart metering in Ireland, with
installation beginning in Q3 2014 and continuing until the end of 2017. The benefits
presented here are the Net Present Value (NPV) in 2011 based on cash flows 2011-
2032. The costs and benefits included are those which are robustly quantifiable – a
range of less reliably quantifiable benefits were also taken into consideration in
reporting but not included in calculations.
Amongst these benefits was an expectation that by the end of the CBA period CO2
emissions would be 100,000-110,000 tonnes below baseline each year and annual SO2
emissions lower by 117-129 tonnes. Quantified benefits pertaining to the customer
and distribution system operator included efficiency and peak shifting such that
customer bills are reduced and distribution capacity uprates may be deferred. The
expected customer behaviour was based on an 18 month customer behavioural trial
with smart metering and a range of stimuli including in-home displays, web portals,
variable tariffs, higher levels of billing information and more regular billing.
24

STEP 6 – Quantify and estimate the relevant costs
The relevant costs of a project are those incurred to deploy the project, relative to the
baseline. The complete picture of costs is required to determine if the project has delivered
a positive return on investment and, if so, at what stage during or after deployment the
cumulative spend matched the benefits accrued.
EPRI provides some guidelines when defining the appropriate costs:
� Cost data can come directly from the project, estimated or tracked by the
investor;
� Capital costs are amortised over time; each project has to estimate its activitybased
costs, using its approved accounting procedures for handling capital costs,
debit, depreciation, and taxes;
� Both baseline and actual project costs should be tracked, with a distinction
between costs that would normally be incurred in a-scale investment and those
due to the RD&D aspects of the project.
Moreover, it is important to note that costs should always be estimated and/or calculated
on the same time intervals for which benefits are calculated. In general, following costs
could be considered:
Category Type of Cost
Programme Planning and administration
Smart Grid programme implementation
Marketing
Measurement, verification, analysis
Participant incentive payments
Capital investments Generation
Transmission
Distribution
Other
Operation & maintenance Generation
Ancillary service
Transmission
Distribution
Meter reading
Participant incentive payments
Losses and theft Value of losses
Value of theft
Reliability Restoration costs
Environmental costs CO2 control equipment and operation
CO2 emission permits
SO2, NOx, PM control equipment and operation
SO2, NOx emission permits
Energy security Cost of oil consumed to generate power
Cost of gasoline, diesel and other petroleum products
Costs to restore wide-area blackouts if any actually occur during the
project period
Research and development R&D costs
Table 2 – Overview of costs
25

InovGrid illustration - Cost of Action tracked
For the estimation of relevant costs of the InovGrid project, EDPD made a recent market consultation.
Other costs were measured by the company and tracked in their accounting notes.
Figure 9 – Cost of Action tracked for the InovGrid project
STEP 7 – Compare costs to benefits
Once costs and benefits have been estimated, they need to be compared in order to
evaluate the cost-effectiveness of the project. This comparison could be done by using one
of the following universally accepted approaches (also put forward by the EPRI
methodology):
- Annual comparison: Compiling the annual benefits and costs over the duration of
the project – i.e. the differences compared with the BAU condition for both benefits
and costs for each year of the study period.
- Cumulative comparison: Presenting costs and benefits cumulatively over time, with
each year’s costs or benefits being the sum of that year’s value plus the value of all
prior years. This approach helps identifying the ‘break-even’ point in time when
benefits exceed costs.
- Net present value (NPV): Calculating the net present value, in which benefits minus
costs each year of the project are discounted using an agreed discount rate. The NPV
represents the total discounted value of the project – i.e. the total amount by which
benefits exceed costs after accounting for the time value of money.
- Benefit-cost ratio: This method shows the ratio of benefits to costs. It represents the
size of benefits relative to that of the costs. If the ratio is greater than one, the
project is cost-effective.
All of the above approaches have their individual benefits, but it is up to the individual
project team representing the interests of the financing consortium to decide what
methodology to use and what to present to whom. Each approach provides added value for
the different interested stakeholders, being the shareholders, regulators and policymakers.
26

InovGrid illustration - Annual Comparison
The annual comparison allows identifying in which years the costs exceed benefits. Initial investments
in the first phases of the smart grid deployment deliver benefits only after some time. Please note
that the figures shown below are only indicative and (for confidentiality reasons) n ot represent the
exact numbers of the InovGrid project.
Sensitivity analysis
Figure 10 – Annual comparison of costs to benefits
When comparing costs to benefits, this must be carried out around certain factors or
parameters depending on the choice of the project coordinators. These are generally
parameters with a high degree of variability and/or uncertainty. Key assumptions underlying
the analysis, including those that drive estimates of major cost components, should be
clearly documented, and the variability or uncertainty of estimates should be incorporated
into those estimates.
The proposed methodology recommends including a sensitivity analysis as part of the costbenefit
information filing supporting the smart grid project investments. Indeed, different
geographies and regulatory environments will have different impacts on the cost and
benefits quantification. The sensitivity analysis should:
� Identify the key variables. Good candidates include the cost and reliability of
technology, customer behaviour change achieved, discount factor when calculating
net present values, emission costs and reliability factors, which have a wide range of
potential values and are more subjective in nature.
27

� Produce different cost-benefit results in order to demonstrate the impact various
scenarios might have on the economic and societal profile of the smart grid project.
We consider the following two factors as having a high impact on the final outcome of the
analysis:
� Discount rate
The realisation of smart grid benefits and costs may occur gradually and over extended
periods of time. Therefore, all cost-benefit analyses in support of a smart grid investment
should reflect and adjust for the expected timing of estimated costs and benefits. The rate of
return on grid investments or the interest rate on long-term state bonds could be a
reasonable choice for a discount rate. However, different discount rates can be used to
assess the benefits for different beneficiaries, e.g. consumers may have a different assumed
cost of capital compared to system operators.
The question of discount rate as should be applied and the influencing factors in its
determination depend on the context in which the analysis is to be considered. Two cases
warrant consideration here – the rate applied in analysis to inform a purely commercial
decision regarding the financial implications of implementing a technical solution in
comparison with other options for the benefit of the investing party, and analysis for
comparative purposes where a project may be publicly funded to realise potential benefits
to society.
Where a smart grid investment is being considered by the grid operator as an alternative to
more conventional investments on purely technical and financial terms, it must be noted
that “smart” investments are often far closer to typical telecommunications investments,
generally with a higher risk level than conventional utility investments. Additionally, this is
often less mature technology, applications and a new technological environment for the
utility, increasing the risk of not achieving expected returns. Thus if the discount rate is to
fairly reflect the relative risk of the projects, a higher discount rate should be applied to the
“smart investment” analysis.
However as the useful economic lifetime of smart grid assets will likely be shorter, this
higher risk is limited to a shorter period. Thus should there be a will to incentivise “smart”
investments over conventional ones for societal reasons on the part of government, the
regulator or other policy determining organisations, an appropriate means of achieving this
would be through allowing the grid operator a higher WACC and shorter depreciation on
such investments, thus seeing the additional risk subsidised by the driving body.
There is however, a case for a lower discount rate to be applied on a theoretical level to
show what the return for society on an investment will be relative to the return seen on
other public investments. Where a “smart grid” is being considered for social reasons with
the costs and gains to society, then it would be appropriate for the discount rate to reflect
the risk to the state, specified by the state body responsible for determining whether the
project will be publicly funded. In this case the DSO is merely the implementing body
contracted by the state, with funding for the project guaranteed. (In this case, the DSO is an
appropriate body to be contracted both due to opportunity, expertise and experience and
also as it is likely to be able to fund the project at a lower interest rate than many other
28

odies which will likely be fully commercial. Thus the total cost borne by the public will likely
be lower.)
With a “risk free” rate as specified by the appropriate body applied, all project risk must be
diligently built into the cash flows by the DSO in forming the financial model of the
investment. This risk includes the uncertainty in achieving cost savings which a project is
expected to deliver.
The interaction between discount rate and implementation schedule of a project will have a
direct impact on the NPV cost of the project. Thus it is vital that both are accurate and do
not disproportionately emphasise costs or benefits at any stage in the project. Where the
costs or rate of return vary over the discounting period, this must be factually reflected. This
is pertinent in the case of smart grids, as evidence to date suggests that benefits are
achieved later due to the interdependence of different systems which must be deployed, the
current immaturity of technology leading to price volatility and the requirement for public
engagement to realise potential benefits.
It must be borne in mind that no generic discount rate can be applied in either case as this
will depend on a complex combination of matters including the debt level of the funding
body. The rate applied in any case, be it utility WACC or the rate on state bonds, requires
calculation by those fully informed on the case in question and qualified to do so. However
standardising the useful economic lifetime of assets would be a far more achievable
measure due to its dependence on technology rather than financial status of a body.
� Lifetime
The lifetime over which a cost-benefit analysis is conducted should reflect the projected
useful life of the smart grid investment or system. It represents the continuous period of
time when the components and system of the investment operate correctly and reliably to
perform their designed functionalities. The project coordinator should carefully document
the basis for its determination of the investment’s useful life and also the length of time over
which reasonable customer and societal benefits can be reliably estimated.
InovGrid illustration – Sensitivity analysis: parameters that impact benefits
- Deferred Distribution Capacity Investments:
o Different consumption trends (increasing or retracting) can influence this variable
o Also the current installed capacity in a given country influences this benefit
- Reduced Meter Reading cost:
o This variable has a direct relation with the number of local readings on the baseline
situation
o The cost of local reading may also be different from location to location (e.g. manpower
cost, tools available)
- Reduced Distribution cost:
o The potential of this benefit is related with the number and type of local meter
operations that can differ in different geographies or regulatory environments
- Reduced Technical losses:
o In countries where the consumption is more concentrated or closer to the
generation points (grid density) or with different consumption mix in different
voltage levels (HV versus LV), the level of technical losses will be variable
29

3. How to extrapolate project results to the national level?
The methodology presented in Chapter Two provides insight into how to interpret results of
single projects. The costs, benefits and their allocation to beneficiaries across society can be
identified through the process described by the different steps. This could prove an effective
tool to evaluate the impact of a project on a part of the electricity system.
However, once individual project results have been evaluated against a well-defined
baseline, there is the need to extrapolate what the combined contribution of several such
smart grid projects to the national and European targets would be. This should be done to
inform the on-going policy move towards a low carbon power system, considering the
technological environment and standards which will impact the rollout process. There is an
added value in determining to what extent a project has led to improving broader
“indicators” that represent the evolution towards a smarter European grid. Simultaneously,
the evaluation of projects values on a European wide scale should include detailed analysis
of the scaling-up and replication conditions.
As it stands, the methodology itself provides no clear answer as to how this can be achieved.
Some first fundamental conceptual ideas are elaborated in this chapter. They rely on some
of the aspects of the EPRI report 14 which aimed to produce a preliminary estimate of the
required investment needed to create a viable smart grid in the USA. The determination of
European KPIs is an on-going process.
3.1 The grid and its limitations
The national quantification process should start by separating the project deliverables into
distinct functional areas and making a number of assumptions about technology
development, deployment, and cost over the desired study period. For consistency
throughout Europe stakeholders need to agree on a study period and other key assumptions
for the evaluation process to form a basis for comparison.
It is important to clarify assumptions and definitions in the evaluation process. The whole
power delivery system should cover everything from the electrical grid busbar at the
generating plant to the energy-consuming device or appliance at the end-user. This means
that the power delivery system encompasses generation step-up transformers; the
generation switchyard; transmission substations, lines, and equipment; distribution
substations, lines and equipment; intelligent electronic devices; communications; distributed
energy resources located at end users; power quality mitigation devices and uninterruptible
power supplies; sensors; energy storage devices; and other equipment.
14 EPRI (Electric Power Research Institue) (2011). Estimating the Costs and Benefits of the Smart Grid, a
Preliminary Estimate of the Investment Requirements and the Resultant Benefits of a Fully Functioning Smart
Grid, Palo Alto, CA: 2011. 1022519
30

3.2 Steps to evaluate base cost
To conduct a quantitative estimate of the level of investment needed over the chosen time
period, a good approach is to separate the core technologies of the project into four broad
areas: transmission, substations, distribution and the customer interface. The cost
estimation process should be further divided into the following categories to consistently
identify the base cost for the required development:
� Elements that meet load growth and correct network issues through installation,
upgrade, and replacement of built network capacity. This is the conventional
means of accommodating new customers (new connects), serving increasing
energy demand of existing customers, and mitigating other network issues
including bottlenecks or potentially high fault currents.
� The additional investments needed to develop and deploy advanced
technologies to enhance the functionality of the electricity system and achieve
the functionalities of a smart grid.
Maintain
Reliability
Figure 11 – smart grid investment types
The figure above illustrates that the division between the various investment types may not
be clearly identifiable and for this reason, base cost evaluation is very important as a
platform for benefit evaluation. In the figure above, the first two segments (red and blue)
represent investments required to maintain adequate capacity and function of the existing
power delivery system, while the third segment is the additional cost to elevate this system
to that of a smart grid.
31
Power Delivery
Power Delivery
system of the

3.3 Key Assumptions
In this future planning and quantification exercise, cost estimates could be based on four key
assumptions for clarity and consistency:
1. Incorporate technologies that make the electricity system smarter, but also stronger,
more resilient, adaptive, and self-healing. Costs are likely to decrease while
performance levels are expected to increase over the assessment period.
Technological options and the roll-out process will have different impacts on CAPEX
and OPEX.
2. Where reasonable and cost-effective, incorporate solutions which adhere to
European and national regulatory standards:
� Consistent with the functionality requirements of Mandates M/441, M/468
and / or M/490.
� Complies with public standards and vendors interoperability
� Meets requirements of European renewables targets (and related
European Directives) as well as national roadmaps
� Meets supply quality standards such as EN50160
3. Consider technology and policies that meet load growth and power system needs by
enhancing smart grid functionality. These must give due regard to:
� smarter network management
� smarter integrated generation
� smarter markets & customers
4. Simultaneous deployment of different smart grid functionalities will be mutually
beneficial. While deployments will realistically be made along parallel paths and in
discrete steps, planning should consider the interaction between the systems being
deployed (for example, in considering future distribution automation, it should be
noted if there is likely to be smart metering deployed in the area over the DA roll-out
period, how the communications systems and additional local data could be
leveraged and add to system benefits for little marginal cost increase).
Smart grids will not be rolled out in a single all-encompassing deployment. Grid
development is an incremental and continuous step-by-step learning process, characterised
by different starting points and projects throughout Europe, leveraging on-going advances in
technology and expertise. Rather than instant revolution, this should be a steady evolution
which must include customers, energy suppliers and producers.
Project leaders and smart grid stakeholders must therefore bring results of research and
demonstration projects to the national and European level. The dissemination of
information, results, best practices and lessons is vital to inform effective development and
integration of optimal solutions. In addition, smart grid development can prove a catalyst for
future partnership and action on a larger scale.
32

Success criteria and realistic business cases based on intensive pilots are vital to shape views
and raise awareness of smart grid investment needs among public and private stakeholders
on national and European level. Tangible cases in support of smart grid investment can only
be presented at national and European level if preliminary estimates on costs and benefits
can be presented.
33

4. Conclusion and guidelines
Regulators and distribution companies are at a unique crossroads. Electricity networks have
developed for decades along a similar path, with the challenge of supplying increasing
demand being met through investment in conventional infrastructural capacity.
However there is a paradigm shift in electricity generation and supply. Distributed
generation, pushed in energy policy, is playing an ever more dominant role in distribution
networks which were never designed to harness that energy.
While the related planning challenges alone could perhaps be met by continued
conventional investment, this would be costly and environmentally unsound. More urgently,
there are a range of operational challenges which need new solutions. Automation,
protection, control and monitoring must all be developed to meet the challenges to supply
quality that have already become apparent with the proliferation of distributed generation.
Thus integrating planning and operational solutions, with the required innovation and
ingenuity, could lead to optimal, cost-efficient and technically effective, sustainable network
development. The key is to invest in the right kind of development. Thus investment
decisions need evidence-based, like-for-like comparison of the options available.
The methodology described in this paper can have two main purposes, independent but
inherently linked in their goal of informing financial decisions regarding smart grid
investments. This is a tool to aid project leaders in a cost-benefit analysis of their work and a
sound, repeatable method that can assist regulators in developing the right investment
incentives, based on the comparison of the relative costs and benefits of different smart grid
investments and to whom they apply.
In developing this methodology, it has been crucial that the outcomes be applicable to the
European context rather than just the situation in the United States, for which it was
originally developed. Thus every effort has been made to align the American and European
terminology (“services”/“characteristics”, “functions”/“functionalities”).
4.1 Project Leaders: evaluating a project
4.1.1 Evaluating a completed project
Ultimately it is the role of the project leader to illustrate the results of the project. If the
technical solution developed in a project is to be adopted, a clear concise illustration of the
cost-benefit is vital.
In adopting this approach, as is always the case where there are quantified outputs, the
quality of the available data will have a direct bearing on the outcome’s credibility. This
34

eing the case, the formulae available for benefit quantification are globally recognised and
highly credible. For many of the variables required for quantification a breadth of data is
available.
One example is the case of figures used for inflation. To add most credibility, they should be
appropriate to the region of deployment (or from which assets are procured), the currencies
involved and based on credible forecasts by the appropriate economic bodies. However if a
“smart grid” project is to be compared to a conventional investment by the same body, the
accepted inflation figure used by the utility in regular investment appraisals may be the most
suitable to give an accurate comparison. Similar care must be taken in applying demand
growth projections and the evolution of electricity prices. In all cases, however, it is vital to
explicitly state the figures used, their sources and, if necessary, the rationale for the choice
of particular figures.
The quality of description of project assets – the technology to be deployed and
operational/control systems employed – has a significant bearing on what the completed
report will communicate. Smart grid development and integration is a field of international
concern and implicit in this is the barrier which language can create. While a written
description of a project’s process and goals has merit, many reviewers will be far better able
to objectively evaluate the project and its applications if they receive a comprehensive
overview of the technology involved in the form of technical specifications. Graphical
descriptions giving an overview of the project and integrating the individual assets and
systems tend to communicate more universally and directly than text.
Clarity and accuracy are vital to ensure that the completed analyses have the highest level of
credibility and that the quality of the project can be best communicated. Indicating the level
of uncertainty in all results ensures that they can be interpreted in context. Future
development of this methodology could perhaps define levels of uncertainty, relating the
“label” to sensitivity bands, historical variation in the quantity in question or other suitable
ranges.
4.1.2 Aiding project planning
Project leaders often find themselves in the challenging position of trying to leverage
funding for projects. Without economic merit, even the most technically accomplished
system will never become a solution.
When using this method to appraise a project in the planning or pre-planning stages, as aid
in leveraging project funding, it has the potential to enhance project planning. Sensitivity
analyses around asset costs, implementation schedules or the balance between budgetary
allowances to different areas (technology, installation, marketing, communications) can
prove an invaluable indicator as to how best to allocate a budget and how to structure the
project to give the best possible chance of achieving the potential benefits.
35

4.1.3 The critical role of cost / benefit analyses – deployment proposals
Where a smart or innovative technical solution has been implemented and tested in a
demonstration project, the next step is to roll out the solution, deploying it where required
across the networks.
Regardless of a project’s technical merit, obtaining investment is a matter of communicating
the expected benefits. Ultimately, communicating benefits is most universal and most
practical when expressed in monetary terms – investors must be able to see the value that
their initial investment can offer.
While this method is ideal for post-analysis, where the costs and benefits are measured and
real, giving a measured and quantified result, it also provides an instrument for the appraisal
of a full rollout. Inevitably, this is required to secure the investment needed.
This method has a unique value where one is looking to obtain project funding, in indicating
not only the benefits, but to whom they apply. Thus where a project may have limited value
to the distribution company – with a similar cost-benefit to a conventional investment and
the less tangible benefit of innovation and development of expertise within the company – it
may have a range of benefits for society, the environment or others. These will strengthen a
business case, particularly as presented to the regulator whose primary concern is to society
at large rather than the distribution company.
4.2 Regulators & Policymakers: how to make informed investment decisions
4.2.1 The evolving role of the regulator
Just as the core role of electricity networks is in delivering secure, reliable power supplies
rather than facilitating the technology and systems integrated on them, so the purpose of
“smart networks” is in enhancing the security, quality and efficiency of existing networks in
the most cost-effective manner possible. Though attaining environmental targets (EU 2020
targets, Kyoto Protocol amongst others) may be an objective in itself, the most cost-effective
means of achieving this will vary from region to region, system to system or population to
population.
Regulators play a central role in supporting the development of the networks of the future
to be done by DSOs. The solutions integrated into networks, be they conventional
infrastructural upgrades or more complex solutions based on control and communicational
development, will require investment and the investment decisions taken by distribution
companies are heavily influenced by the regulatory environment. Thus regulators are faced
with the question as to what investment incentives are needed to best serve the people. A
primary task to address this question consists of designing a flexible economic regulatory
framework that allows DSOs to take responsibility in making the right investment decisions.
In this view, the methodology presented in this paper provides regulators with a clearsighted,
broad analysis of the possible benefits of smart network investment, necessary for
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the development of the appropriate regulatory financing model applied to DSOs. With the
right incentives for innovation included, such a model will ensure the investment climate
that is needed for grid operators to further innovate in technologies and systems which
contribute to the development of the grid to play its part in the efficient delivery of a lowcarbon
economy.
Innovation can lead to solutions which offer improved network performance – the key is in
supporting the innovation which offers this in an efficient, reliable and cost-effective
manner. Ultimately, environmental sustainability can only be achieved hand in hand with
technological and economic sustainability.
4.2.2 What is a “smart” investment?
A “smart investment” does not have to be heavily reliant on ICT – the smartest, most
sustainable investment is the one which achieves the goal at the lowest cost.
Thus determining what constitutes the smartest investment is a matter of making a clear,
objective, like-for-like comparison of investment options. The methodology proposed here
compares the intended investment option to a baseline – the same system without the
investment under investigation having been made. The same methodology can be applied to
any conventional investment to directly compare the two solutions: the “smart” investment
or the conventional one.
The key value in this methodology and its widespread adoption is that it provides a means of
comparing the relative costs and benefits of different projects and options on the most
generic, levelled playing field possible. Thus a range of “smart grid” projects can be
compared by regulators to understand which offers the most suitable technical solution
while delivering the kind of financial return required in their own economic, political and
legal environment. While no analysis can be considered absolutely accurate or universal, the
adoption of this standard approach at least facilitates the comparison of projects.
4.2.3 Extracting information from other projects in Europe and beyond
Learning from past or on-going projects is vital in assessing future projects under
consideration – the challenge is in identifying how past projects, often in other regions, can
give insight into future projects or deployments in one’s own area.
Projects which have been assessed under the proposed methodology lend themselves to
this purpose through explicitly highlighting those underlying figures and assumptions in each
calculation which may be region or regime specific. It is important for anybody using past
project evaluations as an indicator to take these variables into account. Similarly, the insight
offered in the included sensitivity analyses allow regulators, policymakers or any other
assessors to better apply the results to their own context.
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While a project’s exact financial benefits cannot be directly assumed to remain the same if it
were repeated or deployed in another region or system, the proportional breakdown of
benefits and benefitting stakeholders should be broadly indicative of the more global
application. Using the sensitivity analyses to put the results of a given project in the context
of a specific regulator’s region of concern, an indication of the benefits for various
stakeholders and society in general can be derived.
4.3 How distribution companies and regulators can help work together
It is in the interest of all those concerned in network development – regulators, distribution
companies, generators and consumers included – that the best, most effective and costefficient
investments be made in a timely manner. Beyond this, innovation will lead to new
and more effective solutions. There must be an onus on distribution companies who are
developing and operating networks to innovate, design, test and develop solutions which
have the potential to be more sustainable. Equally, regulators must encourage this, but
always in a manner which reflects the concerns of society as to economic sustainability.
Both parties will better meet their aims with cooperation. It is imperative that regulators
clearly communicate what they require, in technical, economic and environmental fields.
The support mechanisms or frameworks they intend to deliver must be clearly
communicated and the criteria for their application made transparent.
Similarly distribution companies must develop both their systems and their expertise to
deliver the solutions which will provide benefits to all stakeholders in so far as possible.
Both parties must continue to perform due diligence both in innovation as to how they
operate and in the level of knowledge and expertise amongst their organisations. Only with
the appropriate skills, experience, ability and expertise can either side develop or analyse as
is required to achieve positive results. Needless to say, these attributes will be increasingly
essential in managing the electrical grid of the future.
4.4 European funding solutions
Smart grid projects entail inherent uncertainty as they have not yet been tested on a large
scale. Given that large-scale demonstration projects would generate new information on
how smart technologies perform in practice, these projects would lead to positive
externalities for all smart grid actors. EU policymakers can help accelerate the development
of smart grids by facilitating financing options for smart grid projects.
In this perspective, EURELECTRIC welcomes the inclusion of smart grid projects in the
current draft Regulation on Guidelines for Trans-European Energy Infrastructure (part of the
Connecting Europe Facility), as well as the fact that distribution companies are identified as
potential project promoters. The methodology outlined in this document could contribute to
the discussions on the selection and monitoring approach for the implementation of smart
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grid projects of common interest, thereby providing guidance on the evaluation of projects’
contribution to the relevant criteria.
Ultimately, EURELECTRIC continues to support the SET Plan and the European Electricity Grid
Initiative, believing that knowledge sharing, dissemination of best practices and large-scale
demonstration projects will be needed to accelerate and optimise grid implementation in
Europe to the benefit of customers.
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