2 TransmissionExpansionPlanning Approaches 4 can be classified in: • static, and • dynamic approaches. In static planning the planner seek the optimal plan for a single year on the planning horizon, that is, planner answer only to the questions “what” transmission facilities must be added to the network and “where” they must be installed. In dynamic planning multi year is considered and planners seek the optimal strategy along the whole planning period. On the other word, in dynamic planning in addition to “what” and “where” planners answer to the question “when” the transmission facilities must be installed in planning horizon. From the viewpoint of power system structures, transmission expansion planning approaches can be classified in transmission expansion planning approaches for: • regulated, and • deregulated power systems. The main objective of expansion planning in regulated power systems is to meet the demand of loads, while maintaining reliability and service quality of power system. In this environment uncertainty is low. Transmission expansion planning is centralised and coordinated with generation expansion planning. Planners have access to the required information for planning. In these systems location of loads and generations, size of loads and generating units, availability of units, load pattern, and dispatch pattern are known. Therefore, planners can design the least cost transmission plan based on the certain reliability criteria. Transmission planning in regulated systems is modelled with a deterministic optimization. The objective function is cost of planning and operation, with technical and economical constraints. In general this optimization is a nonlinear mixed-integer constraint optimization. Different mathematical and heuristic approaches have been proposed to solve this problem . Deregulation has changed the objective of transmission expansion planning and increased the uncertainties of power systems. Due to these changes, new approaches are needed for transmission expansion planning. The goal of this dissertation is to present a transmission expansion planning approach for deregulated environments. Hence, here the publications on non-deterministic transmission expansion planning approaches and transmission expansion planning approaches for deregulated environments are reviewed . The bibliographies of the publications on transmission expansion planning approaches for regulated environments are presented in .
2 TransmissionExpansionPlanning Approaches 5 2.1.1 Non-deterministic TransmissionExpansionPlanning Approaches Uncertainties can be classified in two categories: • Random, and • non-random uncertainties. Random uncertainties are deviation of those parameters which are repeatable and have a known probability distribution. Hence, their statistics can be derived from the past observations. Uncertainty in load is in this category. Non-random uncertainties are evolution of parameters which are not repeatable and hence their statistics cannot be derived from the past observations. Uncertainty in generation expansion is in this category. Besides the uncertainties, there are imprecision and vague data in expansion planning. Imprecision and vague data are the data which can not be clearly expressed. Importance degree of different criteria in multi objective planning falls in this category. Non-deterministic approaches which have been used for transmission expansion planning are: • probabilistic load flow, • probabilistic based reliability criteria, • scenario technique, • decision analysis, and • fuzzy decision making. Probabilistic load flow and probabilistic based reliability criteria approches take into account random uncertainties. Scenario technique considers the non-random uncertainties. Decision analysis is a proper method for dynamic programming. Fuzzy decision making considers imprecision and vague data. 188.8.131.52 Probabilistic Load Flow Probabilistic load flow is used for network analyzing and expansion planning of regulated power systems. Probabilistic load flow is similar to ordinary load flow, except it gets the probability density functions (PDFs) of loads as input and computes the PDFs of output variables -. This can be accomplished by Monte Carlo simulation, analytical methods and combination of them. PDFs of loads can be estimated based on load prediction and uncertainty analysis . To reduce the computations, power flow equations are linearized around the expected value region and then convolution technique is used for computing the PDFs of outputs. The algorithm of transmission expansion planning using probabilistic load