基于MNUM-遗传算法的分布式电源P-Q优化控制设计
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摘要
为了降低并网中分布式电源在输出功率指令突变时产生的功率过冲,提高系统功率控制鲁棒性,提出了基于多点非均匀变异遗传算法(MNUM-GA)的分布式电源P-Q控制系统优化设计方法。该方法的要点为将分布式电源P-Q控制器参数优化设计问题转换为一个典型的有约束优化问题,并将系统有功功率的误差绝对值时间积分性能指标(ITAE)和系统无功功率的ITAE设计为目标函数,而后利用所设计的MNUM-GA获得分布式电源P-Q控制器最优参数。最后在一台容量为2.5 kW三相并网逆变实验系统上进行了仿真测试实验和硬件平台测试实验。实验结果表明,相对于采用Z-N经验法、传统GA的分布式电源系统,所设计的基于MNUMGA的分布式电源P-Q控制系统具有最优的功率控制性能。
In order to improve the robust control performance and power overshoot of distributed generation units in grid-connected mode when the output power command has a sudden change,a novel P-Q control design method is designed for the distributed generation units based on multi non-uniform mutation-genetic algorithm(MNUM-GA).The core content behind the proposed method is firstly formulating the design problem of P-Q controller for the distributed generation units as a typical constrained optimization problem, where the integrated time absolute error(ITAE) of active power and the ITAE of reactive power are weighed as the optimization objective function.Then,a MNUM-GA is designed to solve formulated problem.At last,the superiority in power control performance of the proposed method to Z-N empirical method, tradition genetic algorithm is demonstrated by simulation and experimental results on a 2.5 kW threephase grid-connected inverter.
In order to improve the robust control performance and power overshoot of distributed generation units in grid-connected mode when the output power command has a sudden change,a novel P-Q control design method is designed for the distributed generation units based on multi non-uniform mutation-genetic algorithm(MNUM-GA).The core content behind the proposed method is firstly formulating the design problem of P-Q controller for the distributed generation units as a typical constrained optimization problem, where the integrated time absolute error(ITAE) of active power and the ITAE of reactive power are weighed as the optimization objective function.Then,a MNUM-GA is designed to solve formulated problem.At last,the superiority in power control performance of the proposed method to Z-N empirical method, tradition genetic algorithm is demonstrated by simulation and experimental results on a 2.5 kW threephase grid-connected inverter.
引文
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[3] Hassan M A,Abido M A.Optimal Design of Microgrids in Autonomous and Grid-connected Modes Using Particle Swarm Optimization[J].IEEE Trans. on Power Electronics,2011,26(3):755-769.
[4] Adhikari S, Li F. Coordinated V-f and P-Q Control of Solar Photovoltaic Generators With MPPT and Battery Storage in Microgrids[J].IEEE Trans. on Smart Grid,2014,5(3):1270-1281.
[5] W Al Saedi,S W Lachowicz,D Habibi,et al.Voltage and Frequency Regulation Based DG Unit in an Autonomous Microgrid Operation Using Particle Swarm Optimization[J]. IEEE Trans. on International Journal of Electrical Power&Energy Systems,2013,53(7):742-751.
[6]周明,孙树栋.遗传算法原理及应用[M].国防工业出版社,1999.
[7]刘金琨.先进PID控制MATLAB仿真(第3版)[M].北京:电子工业出版社,2011.