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Based on Improved Particle Swarm fish with the Unit Commitment Optimization

Author: DuWeiJie
Tutor: ZhangJunFang
School: Nanjing University of Technology and Engineering
Course: Proceedings of the
Keywords: Unit Commitment Optimization He assigned negative economic Artificial fish swarm algorithm (AFSA) Particle swarm optimization (PSO) Tabu Search (TS) Immunization (IV) Electricity market
CLC: TM732
Type: Master's thesis
Year: 2009
Downloads: 354
Quote: 10
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Abstract


Unit Commitment Optimization of power system is the core issue of short-running programs, is a typical non-linear optimization problem that involves many non-linear, discrete, stochastic and uncertainties and other factors. Conventional mathematical methods in dealing with such issues have some limitations, and intelligent optimization method was suitable for solving traditional optimization methods are difficult to solve highly nonlinear, high-discrete combinatorial optimization problems. This paper focuses on optimal combination unit, expand the following main tasks: (1) on fish school algorithm, particle swarm algorithm, immune algorithm and tabu search algorithm research. Artificial fish swarm algorithm to handle large coordinate system problem has its own advantages, the artificial fish swarm algorithm applied to a large system coordination combinatorial problems that can quickly solve large portfolio of high dimensional systems, solving problems and other issues; against particle swarm the global search ability, the late evolutionary slow convergence algorithm to reach a certain accuracy can not continue to run other shortcomings, proposed immunity based on vaccination contraindications PSO (IVT-PSO). Simulation results show that the algorithm can get better optimization results verify the effectiveness of the method. (2) study the optimal combination of the basic principles of the unit and mathematical models. Consider the load demand limiting constraint, single output power of the upper and lower bound, the unit start and stop times the maximum allowable bound coordinate the artificial fish swarm algorithm based on vaccination and immunization taboo particle swarm optimization algorithm is applied to the unit commitment problem, the minimum amount to coal as the objective function of the unit start-stop mode and economic dispatch of these two questions alternately iterative solution. The simulation and analytical results demonstrate the correctness, effectiveness and superiority. (3) under the conditions of competition in the electricity market, considering the reactive power and alternate revenue impact to the availability status of the unit itself, power generation, power limits, ramp rate and system spare capacity and electricity market trading as the constraints of the electricity market structure competitive conditions unit optimized mathematical model. In order to gain maximum power plants as the objective function of the unit start-stop mode and economic dispatch of these two questions were used to coordinate the fish swarm algorithm based on vaccination and immunization taboo PSO alternately iterative solution. The simulation and analytical results demonstrate the correctness, effectiveness and superiority.

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Power system scheduling, management, communication > The operation of the power system
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