Metrics for Measuring Progress Toward Implementation of the Smart ...

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sources to gather this information include EPRI, EEI, universities, IEEE, and the national laboratories. There is a lack of resources to accomplish this and additional personnel, funding, and tools will need to be allocated to be able to establish a baseline and track progress for this metric. Number of States that Have Defined Electric Rate Structures Based on Power Quality Service Level The first step in developing this metric is to determine how many states have defined electric rate structures based on power quality service level and how many states have initiated and established electric rate structures based on power quality service level. Potential data sources for gathering this information include public utility commissions, NARUC, NRECA, industry groups, and FERC. Analysis is needed to better define aggregation level (state versus utility, etc.) and determine focus (IOU, muni, co-op); determine what defines power quality service level; and investigate the availability of power quality rates versus customer adoption. Number of Customer Complaints Regarding Power Quality Issues The first step in developing this metric is to determine the most appropriate definition of power quality; this definition depends on customer class, (i.e. industrial, commercial, or residential). Next, it will be necessary to determine how to attribute customer satisfaction improvements to the smart grid. Gathering this information could entail having focus groups, utility marketing groups, and advocacy groups use questionnaires targeted at each defined power quality customer class to obtain data. Potential issues include who pays for and administers these surveys and being sure to collect an adequate amount of customer responses in order to have a large enough data set to examine. TABLE 4.1. LIST OF PARTICIPANTS Name Hawk Asgeirsson Clayton Burns Joe Bucciero Lawrence Carter Steve Hauser Eric Hsieh Ward Jewell Mladen Kezunovic Tom King Ben Kroposki Bob Lash Arshad Mansoor Merv McInnis Joe Schatz Richard Schomberg Le Tang Chuck Whitaker Terry Winter Brian Marchionini, Facilitator Organization DTE Energy National Grid KEMA, Inc. Bonneville Power Administration GridPoint NEMA Wichita State University Texas A&M University Oak Ridge National Laboratory National Renewable Energy Laboratory USDA-RUS Electric Power Research Institute Emerson Southern Company Electricity de France ABB, Inc. BEW Engineering American Superconductor Energetics Incorporated Energetics Incorporated 16 July 2008
TABLE 4.2. COMMENTS ON THE CHARACTERISTIC • Suggested Revised Wording: Provides power quality for the range of needs in the 21 st Century economy. TABLE 4.3. METRICS (DIAMONDS INDICATE THE NUMBER OF VOTES RECEIVED TO IDENTIFY THE TOP FIVE PRIORITIES) Sense Communicate Process Control/Action Impacts • Number of power quality measurement points divided by number of customers • Number of devices sold and installed to measure power quality • % of circuit miles (or customers) monitored and communicating power quality information to a central location • Number of devices that are necessary measurement and communications equipment contributing to open architecture • Number of power quality incidents that you can identify and anticipate over time • Number of devices divided by improvement in reliability indices - Determining how many controllable devices have been sold and installed - Number of power quality control points divided by number of customers - Number of customers with service interruptions at all households, businesses in a service territory - Number of points that control power quality factor • % of sensitive loads that have built in immunity (for example-ride through capability) • The DG capacity level (how small) at which voltage regulation is effective/effected economically • Number of instances where generators have to operate outside of their target efficiency range - Controlling flicker within local standard - Provide voltage per standard to the customer • Number of states that have defined electric rate structures based on power quality service level • Number of choices a customer has for various levels of power quality at various costs - Varying grades of power quality at different pricing levels • Number of customer complaints regarding power quality issues - Level of customer satisfaction on a scale of 1-10 - Duration of resolution to power quality complaint • Minimum cost to economy $power quality/GDP/time - Number of people seriously affected because of power quality disturbances Energetics Incorporated 17 July 2008
Page 1 and 2: Metrics for Measuring Progress Towa
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