Market Performance And Transmission Planning In Competitive Electricity Market With Network Constraints

In a competitive electricity market, the oligopoly structure of the market and the network constraints may produce results far from the perfect competition. The producers want to bid strategically to maximum their profits. All these make the network impacts analysis become necessary. The modeling of the bidding behavior of the producers is a key-point in modeling and simulation of the competitive electricity markets. Different models of competition have been proposed and employed. Among them, linear supply function model has been proposed and widely used in competitive electricity markets. The network structure of the power system that accommodates the economic transactions, in a pool based electricity market, may have severe impacts on the market performances, reducing considerably the market efficiency, especially in presence of strategic bidding of the producers. In this context the network re-enforcement plays a major role and proper strategies of transmission planning need to be devised.In the chapter II of this thesis, the optimal market dispatch by Independent System Operation based on a linear supply function model is analyzed analytically from without any constraints in the markets to both the constraints from the line flow limits, in which DC power flow model is applied, and the generation capacity limits are considered. The analytical formulations of the dispatch results under all of these different constraint situations are given. In the third Chapter, the strategic bidding of producers in which the producers will change the intercept of their supply function is studied. Such strategy is based on one two-level optimization problem: Independent System Operator maximize the system surplus according to the bidding of producers and customers while the producers want to maximize their producer surplus during their bidding knowing that their biddings will affect the dispatch result of Independent System Operator. Based on the analytical result in Chapter II, the two-level optimization problem in the strategy can be solved analytically so that the supply function model can be applied to big system and the limitation that the supply function model is limited to small system is released.The purpose of the Chapter IV is to find the supply function equilibrium in which the producers should change the slope of their supply function during the strategic bidding. It is difficult to find the best slope if the same method of searching the best intercept in Chapter III is applied. The indirect way, that searches the market equilibrium through changing intercept of supply function and then finds the best slope by the market equilibrium and the intercept of the marginal cost, is introduced, and it can get the same results that are the Supply function equilibrium of producers. At the same time, the best rate of changing intercept and slope together is also found by the similar indirect way.In Chapter V, 4-bus system, IEEE-30 bus system and IEEE-118 bus system are used as test cases to compare the three strategic biding methods in the previous two chapters. Market results from the three methods are always so close so that all of them should be feasible strategies. Based on the strategic biding models of producers in the previous chapters, the network impacts are analyzed in Chapter VI. Two conceptual approaches to the evaluation of the performances of the electricity market with network representation in presence of bidding behavior of the producers and in a constrained market is given. In the first assessment approach, different scenarios are studied and compared on the basis of a set of micro-economic metrics. The model formulated allows for a true side by side comparison between the perfect competition and the oligopoly with and without network constraints. From such analysis the worsening of the market efficiencies and performances, due to the joint effects of the non perfect competition and the network constraints, may be assessed and quantified. In the second conceptual approach, the linear supply function model is used to analyze the market outcomes under network constraints and strategic bidding of producers. The effect to the market outcomes is analyzed in three factors, congestion, market power because of the concentration of producers, and market power because of the line flow limit through comparing different scenarios: the perfect competition with network constraints to perfect competition without network constraints; the oligopoly condition with network constraints in which line flow limit is known to producers when they bid strategically to the perfect competition with network constraints; the oligopoly condition with network constraints in which line flow limit is known to producers when they bid strategically to the oligopoly condition with network constraints in which line flow limit is unknown to producers when they bid strategically. Related indices are defined to reflect the effects of the three different factors. At last part of the chapter, the sensitivity of the social surplus, producer surplus, consumer surplus and average weighted price to the value of the line flow limits are defined and they are taken as the criterion to rank the lines in the network. The IEEE 30 bus system is used as the test case in the chapter.Chapter VII presents, for a pool based market, two heuristic procedures to select, from a set of predefined candidate lines, the most effective subset of lines that would reduce the market impacts within the allowed budget for network expansion. Some indices that accounts for the economic effects of the candidate lines, both in terms of construction cost and market efficiency, are proposed and used for the heuristic selection. The proposed sensitivity indicates one new way to define the objective of transmission planning in the deregulated environment. The proposed methods are applied and compared with reference to a 18-bus test system.Chapter VIII gives all the conclusions drawn from the whole thesis.