Congestion Driven Mechanism Based Transmission Expansion Planning Under Market Environment

Restructuring and deregulation of power industry has exposed transmission planner to new objectives and uncertainties, such as how to handle uncertain factors concerning the planning of new power plants as well as the demand management. Therefore, new criteria and approaches are needed for transmission expansion planning in deregulated environment.In this dissertation, an OPF based power-pool pricing model is developed to analyze system congestion and some system congestion index are firstly proposed to evaluate the reliability in transmission planning optimization. Then considering power system uncertainties, the framework of new optimal planning models with the congestion index constraint is presented. Eventually, the applied results show that the expanded transmission system can satisfy demands from network users and provide a fair environment to all market participants.The content below is also included in the dissertation:1. A new system congestion index is proposed to evaluate system reliability under power market environment.2. A new optimal planning model with the congestion index constraint is presented to consider the effect of transmission congestion. Compared with the traditional expansion planning model, the new model can simulate the system optimal operation point by solving the optimal power flow in the market environment, so that the results can provide more accurate basis to make decision to relieve system congestion. Also considering the early convergence existing problem in the standard genetic algorithm, a new niche genetic algorithm (NGA) is designed based on fitness sharing function. By dynamically adjusting individual's selecting probability, NGA can improve the algorithm's convergent capability effectively.3. A new congestion-constrained model for transmission flexible planning is presented based on chance constrained programming. Then a method is presented for solving the optimization problem using both Monte-Carlo simulation and improved genetic algorithm, which provides more flexibility to network planning evaluation. At the same time, Benders decomposition algorithm is introduced to account for transmission expansion planning programming, which decomposes the planning model into a base planning master problem and a series of separate operational sub-problems. Then the optimized planning schemes are received from the iteration process alternatively.4. By in-depth analyzing the effects of congestion index and congestion cost on multistage transmission system expansion planning, a new optimization model for the multistage transmission system expansion planning is first presented and solved using the improved NGA. And a new chance constrained model for the multistage transmission system expansion planning is also presented to solve the flexible planning problem.5. In accordance with the framework of information infusion, a new comprehensive expansion planning evaluation model is proposed, combined evidence reasoning technique with multi-scenario analysis technique.