Research On Transmission System Planning Based On Chance Constrained Programming

The transmission system plays an important role in providing access to all participants in a competitive electricity market for supply and delivery of electric power. The operation status of the transmission system such as capacity adequacy has an important influence on the electricity market competition. Reasonably expanding or reinforcing the transmission system could have an important effect on meeting generating companies and customers' needs, eliminating or relieving transmission congestion so as to enhance competition in the electricity market and to improve the operation efficiency of the power system. Compared with the problem in the traditional vertically integrated monopoly industry, the transmission system planning problem in the electricity market environment is more complicated and has more uncertain factors to be dealt with, such as uncertainties associated with locations and capacities of new power plants. Given this background, the problem of transmission system planning in electricity market environment is studied thoroughly in this dissertation.A new transmission system expansion planning approach is developed to handle future uncertainties, especially the locations, capacities of new power plants and demand growth in a competitive market environment. The aim is to determine the optimal plan, which is robust and flexible enough to meet the requirements of the transmission planning in competitive environment.With advancements in technology and improvements in management as well as the deepening of the restructuring of the electricity industry, engineers have the capability and need to intervene and regulate power flow patterns to some extent. This will pose higher requirements for flexibility in transmission system expansion planning. Therefore, the optimal result will be on the conservative side if the constraints are handled by deterministic methods. Given this background, a new method for the optimal transmission system expansion planning is presented in this dissertation based on chance constrained programming (CCP). CCP is a kind ofstochastic optimization approaches and is especially suitable for solving optimization problems with uncertain factors. In the electricity market environment, more flexibility and robustness are required for transmission system planning, and CCP could well meet such requirements by imposing required confidence levels.Optimal multistage transmission system expansion planning is a large-scale nonlinear combinatorial optimization problem. Deregulation introduces more uncertain factors for the transmission planning processes, and hence security and economic risks will be inevitably incurred in the planning scheme produced under such an uncertain environment. Given this background, a new risk-constrained model for the multistage transmission system expansion planning is first presented based on the chance constrained programming, and a method is next presented for solving the optimization problem using the well-known Monte Carlo simulation method and the genetic algorithm.Deregulation in the electricity supply industry has brought many new challenges to the problem of reactive power planning. Although the problem has been extensively studied, available standard optimization models and methods do not offer good solutions to this problem, especially in a competitive electricity market environment where many factors are uncertain. Given this background, a novel method for optimal reactive power planning based on chance constrained programming is presented in this dissertation. Given the confidence levels in advance, the proposed framework could quantify the security risk created by uncertainties while minimizing the operation cost and investment cost.