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The Research of Self-scheduling in Pool for Generators Based on Robust Optimization

Author: WenQiang
Tutor: TongXiaoJiao
School: Changsha University of Science and Technology
Course: Proceedings of the
Keywords: Power system Marginal Price Self - scheduling Robust Optimization Wind Power
CLC: F224
Type: Master's thesis
Year: 2010
Downloads: 79
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Abstract

In electricity markets Pool mode, self-scheduling power producers in order to pursue the maximization of their profits to develop Generation Scheduling generation plans to the system control center, the system control center based on the grid bound to adjust the power generation plan, develop scheduling . Implement self-scheduling, power producers generating unit plans to develop Pool mode provides certain liberties. With the deepening of the reform of the electricity market, increasing market transactions, the new environmental requirements to power suppliers more and more autonomy. Although China has not yet implemented the power suppliers self-scheduling, but in the context of continuous reform of the electricity market, power generation demanding autonomy has become increasingly evident, therefore, self-scheduling of power producers increasingly important research. The Gencos since scheduling mathematical model for optimization problems with certain parameters. The parameters of the optimization model (such as: node marginal price, load, etc.) is characterized by uncertainty, and as the system size increases, the optimization problem of equality and inequality constraints increased, this change will allow self-scheduling problem difficulties. Therefore, how to use the new mathematical theory and methods, to design efficient calculation methods for such uncertainty optimization problem, and has a certain value and practical significance. Uncertainty from the scheduling problem, parameter processing is one of the key issues. The traditional method is the probability of stochastic optimization methods. Probabilistic methods taking into account the need to predict the distribution of the parameters, and forecast itself is not easy to deal with the problem in the electricity market operator. Therefore, different from the traditional approach, In this paper, a robust optimization method, consider the marginal price and asynchronous wind turbine output node uncertainties both cases, the establishment of robust optimization-based self-scheduling model and the model calculations. The main work of this paper are as follows: consider the uncertainty of the Marginal Price (LMPs) self-scheduling. Robust optimization theory and methods, the LMPs uncertainty 'cassette' uncertain collection to establish a self-scheduling model, and the model for the complex max-min optimization problem. Optimization duality theory in order to simplify the model, using the model simplification conventional nonlinear optimization problem, which can be used the traditional nonlinear optimization methods for solving. IEEE-30 node system in order to test the validity of the model, to call MATLAB provided Quadprog quadratic programming method, by calculating the results show the feasibility and effectiveness of the model and calculation methods. Compared with traditional methods, the characteristics of the method is no need to predict the distribution of parameters, and calculated to ensure the safe operation of the system. With the development of wind power, including wind turbine research has practical value higher self-scheduling problem. Study plan based on self-scheduling of price uncertainty, combined with the uncertainty of the wind power output, containing wind power and LMPs self-scheduling model uncertainty. The new model for the max-min optimization problems, and optimize the constraint max optimized form. We use robust optimization method simplified model for the conventional nonlinear optimization problem. IEEE-30 bus test calculation results show the feasibility of the method. The content is uncertainty at the power generation Marginal Price (LMPs) Research Extension and Development.

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