Study On Locational Marginal Prices And Congestion Management Algorithm

Congestion management is an important function of the ISO in maintaining system security and reliability. Different congestion management methodologies are adopted according to different types of transaction or settlement mechanism. Locational marginal prices (LMP), a pricing method used to price energy purchases and sales in market, also can alleviate congestion. Basing on the theoretical study and practical application of domestic and international congestion management methods and locational marginal price, this paper does some in-depth study of these two problems considering Chinese electricity market characteristics. Some results have applications in industry.1 Linear system of equations is used to research on relationships of loactional marginal price and marginal generator and of marginal generator and shadow prices of congestion lines. Afterwards, the relationship between loactional marginal price and shadow prices of congestion lines is deduced. Economic phenomena caused by congestion are explained that congestion will decrease total surplus.2 AC-DC iterative method calculating loactional marginal price with losses is proposed. DCOPF is in charge of economic dispatch, and AC power flow takes charge of losses. These two processes iterate one another till method convergence, and transpose Jacobian matrix is adopted to calculate penalty factors. LMP with losses is deduced according with LMP without losses got by DCOPF and penalty factors. IEEE 14 bus system is used to illustrate how slack bus affects LMP and convergence. IEEE 118 bus system is adopted to testify this method has engineering application value.3 All-time-period optimization model for loactional marginal price superior to single-time-period optimization model is proposed. This model developes loactional marginal price theory and contributes to electricity market optimal operation. All-time-period optimization model provide a theoretical basis for economic dispatch of electricity market. The PJM-ISO five bus system study case shows that in the day-ahead market, all-time-period optimization model can accomplish security-constrained economic dispatch more effective than single-time-period optimization model. IEEE118 bus is used to analyze relationship between scalar of optimal period and time consumption.4 Security constrained optmal power flow model is utilized for congestion management of day-ahead market. Primal-dual interior point method and Particle SwarmOptimization are presented for solving this model. IEEE118 bus system is used to compare effectiveness of two methods.5 According to annual transaction and monthly transaction of northeast regional electricity market of China, linear optimization model with two sub-ooptimization conception is proposed to deal with medium and long-term transction. Congestion management of medium and long-term transction for northeast regional electricity market of China adopted presently is local optimization methodology with Convergence defect. A novel congestion management model for medium and long-term transction obeyding Kirchhoff's law, considering security constrained branches as optimized variables. For the situation that the linear optimization problem has no solutions, a two sub-optimization conception is proposed, that is, during the first sub-optimization process, the optimization model is set up to get the feasible solution domain, the in the second sub-optimization process, the optimal solution is obtained from the feasible solution domain that is got by the first sub-optimization. Thus the proposed method is guarnteed to be feasible for actual engineering application.6 Bidding strategy for price-taker energy suppliers paid at LMPs is discussed. Based on the theory that the maximum profit is realized when marginal cost equals the revenue, the relationship between optimal bidding price and optimal offering energy is analyzed. A function governing the LMP and profit relationship is conjectured. Price probability density function is deduced by piecewise polynomial curve fitting. An expectation function is given and the relationship between optimal bidding price and expected profits is analyzed. The bidding strategy is obtained by maximizing the expected profits. A cased study with historical data with curve fitting techniques proves the validation of this bidding strategy.It is important for health development and security operation of electricity market to study on Congestion management and locational marginal price. The congestion management model submitted in the thesis for medium and long-term transction has been validated in northeast regional electricity market of China. AC-DC iterative method is proposed to calculate loactional marginal price with losses. All-time-period optimization model developes loactional marginal price theory and contributes to electricity market optimal operation. Fruits of research have a wider significance for building and developing of electricity market in theoretical and practical aspects.