Research On Generation Investment Decision-making And Generation Capacity Adequacy In Electricity Market Environment

One of the most significant features of the power industry restructuring is the separation of the generation sector from the transmission/distribution sectors. In other words, the monopoly utility company is divided into one power grid company and two or more generation companies (GenCos). In the new electricity market environment, generally there is no centralized generation expansion planning, which was made by a monopoly utility company based on forecasted load, loss of load probability (LOLP) calculation and estimates of the value of lost load (VOLL) in the traditional power system. Investment on new generation capacity additions is a commercial and risky activity, and the objective of generation investors is to maximize investment profits, rather than to ensure sufficient supply of electricity in nowadays and in the future. Actually, it is not clear who has the ultimate responsibility for the generation capacity adequacy hence the reliability of electricity supply. Probably, there does not exist such an entity or a market participant to undertake this responsibility. Given this background, it is a problem of extreme importance for governments or regulators to establish an appropriate market mechanism for inducing sufficient generation capacity so as to ensure the reliability of electricity supply. On the other hand, it is important for GenCos to make optimal generation investment decisions and production decisions so as to maximize potential profits. In this thesis, above problems are investigated systematically and some significant results are obtained.Since the production decisions of GenCos have a great impact on their revenues and hence on their generation investment decision-making, therefore the problem of optimal generation capacity allocation among different kinds of markets for GenCos is studied at first. Assumming that GenCos have the freedom to sell energy in the energy market, in operating reserve market or in both. Based on the well-developed portfolio theory, an optimization model is established to carry out the optimal generation capacity allocation decision-making for GenCos so as to maximize their profits with risks associated well taken into account, and a solvingapproach presented.Secondly, as one of the most important approaches for ensuring adequate generation capacity, the capacity obligation mechanism is employed in some operating electricity markets. In these markets, each LSE has to acquire enough installed capacity to meet its capacity obligation. Through analyzing the optimal allocation strategies of generation capacity for GenCos between two electricity markets under different levels of installed capacity prices as well as the optimal purchasing strategies of LSEs, the problem of determining an appropriate level of generation installed capacity price for ensuring generation capacity adequacy is represented as a two-level optimization problem, and a mathematical model is developed and a solving approach presented.Thirdly, a preliminary research is carried out for the generation investment decision-making problem in the electricity market environment. A new methodological framework for sloving this problem is established, with load growth uncertainty and competition for generation investment from other investors taken into account. A solving approach based on the well-known Monte-Carlo simulation and genetic algorithm is next developed.Fourthly, given that the load growth uncertainty is assumed to be the major source of uncertainty, a new methodological framework for generation investment decision-making is presented based on the well-developed real option approach (ROA), with competition for generation investment from other investors taken into account. A mathematical model is developed and a solving approach presented for this purpose. Finally, the effects of different market mechanisms on generation investment incentives and hence the generation capacity adequacy are also investigated in a quantitative way.Lastly, conclusions are made based on the research outcomes, and directions for future research indicated.