Research Of Generation Expansion Planning's Methods In Electricity Market

Great changes have been observed in the power mechanisms due to the competition of electricity market, which hence has a great influence on the generation expansion planning (GEP) technologies. Because of the alteration of the planner and request of market mechanisms, the evaluation standard for the planning schemes is changed from reliability or system-wide cost minimization to maximization of their profits. In electricity market, generation plays an important role, because the planning schemes of each planner, including generation capacity and structure, will be greatly affected by the benefit of each participator in the market, and influence the security of power system at the same time. Therefore GEP becomes essential. To solve these problems, this dissertation analyzes the new characteristics and requests of GEP for the developing electricity market; builds novel models for GEP; introduces new methods to evaluate the schemes, i.e., the equilibrium of maximal real option value among planners; and solves the models by a new algorithm. The innovations of this dissertation are as the follows. 1) A novel joint planning model of generation expansion and environment protection based on extended ranking algorithm is presented. In this model, environmental cost and operation cost of existing units are included in the objective function. The planning procedures are reduced reasonably to obtain an optimal environment protection scheme and phase-out scheme of generating units as soon as possible. The adoption of extended ranking algorithm can avoid the problem of"combination explosion". Thus, regulator and planners of GEP can optimize their own environment protection scheme from the view of GEP.2) A novel noncooperative game model for maintenance scheduling of generating units (MSU) is developed. The objective is to maximize the profit of each generating company. The maintenance risk loss and the compensation fee of interruptible load when the permitted maintenance capacity in the system is insufficient are taken into consideration. A method of stochastic search is used to coordinate multiple equilibria of MSU game. The game of optimal maintenance scheduling makes the evaluation of GEP scheme fit for the environment of electricity market.3) A novel deferment option game model of generation investment is proposed. Based on real option pricing theory and noncooperative game theory, the game behaviors of generation investors are investigated. From simulation of many strategy combinations, the real option value of each investor is calculated and Nash equilibrium is obtained. Meanwhile, the optimal scheme of environment protection is a main concern of each investor, and noncooperative game model for MSU is incorporated in the computation of its revenues. Since real option pricing can deal with the situation of investment value's variation, flexible generation investment strategies will be provided for planners by the above model.4) A novel deferment option game model of joint investment between generation and transmission network is put forward. Based on option game theory, with the consideration of optimal scheme of environment protection and the incorporation of MSU game, many strategy combinations are simulated. Three main modes of electricity market are analyzed, and formulation of control performance standard (CPS) fee is deduced. The real option value of each generation company or transmission company is calculated and its optimal investment scheme is obtained to maximize its profits from electricity investment.5) According to the shortcomings in the application of Tabu Search (TS) in the GEP, some ways are proposed to improve calculation speed and global convergence performance. Based on scope partition, the adoption of remembrance-guided search method improves the efficiency of local search. The use of dynamically managed tabu frequency information reduces the demand of memory. The problem of GEP is solved by the above measures to get satisfying solution.Briefly, model 1) focuses on the problem of environment protection in the cost analysis of generation investment. Model 2) investigates the problem of MSU game in the revenue computation of generation investment. Based on model 1) and 2), the problem of generation investment decision-making for multiple investors in electricity market is debated. As a further research, joint investment between generation and transmission network is concerned in model 4). 5) is the algorithm of model 3) and 4). The models and algorithm mentioned above take full consideration of the characters of GEP in electricity market, which can be effectively applied to game among investors, uncertainty of investment value, economic benefit of each investor and large-scale generation expansion planning. The simulation results of a real generation expansion scheme with many different objectives indicate they are feasible and efficient, and provide new ideas to solve the problem of GEP in electricity market.