基于改进粒子群算法在多能互补微网中的应用

doi:10.16180/j.cnki.issn1007-7820.2022.10.012

摘要/Abstract

摘要：

多能互补微网系统存在多维变量和多重约束,从而导致系统综合年化成本计算复杂且成本较高。在计算过程中,由于系统需要功率平衡,易诱发多种设备出力超出规定限值的问题。针对该问题,文中提出了一种改进的粒子群算法。该算法综合考虑系统内电-热-冷多种负荷功率平衡,在粒子群算法的基础上引入二次限制,将系统内超出限值的设备出力重新拉回约束边界内,动态优化系统内设备出力的缩减系数,避免因系统内部功率平衡导致的设备超限问题。通过算例分析,将遗传算法、改进前的算法和改进后的算法应用到多能互补微网系统,并对比分析了不同场景下的设备出力和综合年化成本。实验结果证明了所提算法的有效性与普遍适用性。

关键词: 多能互补微网, 多维变量, 多重约束, 功率平衡, 综合年化成本, 粒子群算法, 二次限制, 遗传算法

Abstract:

The multi-energy complementary microgrid system has multi-dimensional variables and multiple constraints, which leads to the complex and high-cost calculation of the system comprehensive annual cost. In the calculation process, because the system needs power balance, it is easy to cause the problem that the output of various equipment exceeds the specified limit. In view of this problem, an improved particle swarm optimization algorithm is proposed. The algorithm comprehensively considers the power balance of electricity-heat-cooling multiple loads in the system, and introduces a secondary limit on the basis of the particle swarm algorithm. The algorithm pulls the equipment output beyond the power limit back to the constraint boundary, and dynamically optimizes the reduction coefficient of the equipment output to avoid the over-limit problem caused by the internal power balance of the system. Through the analysis of examples, the genetic algorithm, the algorithm before the improvement, and the algorithm after the improvement are applied to the multi-energy complementary microgrid system, and the equipment output and the comprehensive annualized cost in different scenarios are compared and analyzed. The experimental results prove the effectiveness and universal applicability of the proposed algorithm.

Key words: multi-energy complementary microgrid, multi-dimensional variable, multiple constraints, power balance, comprehensive annualized cost, particle swarm algorithm, quadratic limit, genetic algorithm

中图分类号:

TP391

赵鉴,袁渤巽,倪凌凡,林顺富,王维. 基于改进粒子群算法在多能互补微网中的应用[J]. 电子科技, 2022, 35(10): 72-78.

ZHAO Jian,YUAN Boxun,NI Lingfan,LIN Shunfu,WANG Wei. Application of Improved Particle Swarm Optimization Algorithm in Multi-Energy Complementary Microgrid[J]. Electronic Science and Technology, 2022, 35(10): 72-78.

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粒子个数	迭代次数	y	x	用时/s
5	5	3.285 5	1.068 1	0.012 4
10	10	1.243 0	1.061 1	0.014 7
20	20	0.003 9	1.049 4	0.016 3
50	50	0.000 9	1.050 1	0.015 5
100	100	0.000 0	1.050 0	0.017 1

算法名称	y₁	x₁	x₂	用时/s
PSO算法	0.00	1.050	2.080	5.825 7
遍历算法	0.25	1.050	2.075	0.638 0

算法名称	y₂	x₁	x₂	x₃	用时/s
PSO算法	0.126	1.053 4	2.079 2	5.020 5	5.905
遍历算法	0.500	1.050 0	2.075 0	5.025 0	57.160

设备	投资成本	维护成本系数	效率	运行周期/年
风机	6 000元/kW	0.050元/kW	——	20
光伏	12 700元/kW	0.039元/kW	——	25
热电联供机组	3 300元/kW	0.059元/kW	电:0.3 热:0.45	20
燃气锅炉	1 780元/kW	0.026元/kW	0.872	20
余热锅炉	672元/kW	0.013元/kW	0.80	20
电制冷机	1 180元/kW	0.013元/kW	3.5	20
吸收式制冷机	1 780元/kW	0.013元/kW	1.44	20
蓄电池	972元/(kW·h)	0.013元/(kW·h)	0.75	20
热储	102元(kW·h)	0.026元/(kW·h)	0.9	20
冷储	136元/(kW·h)	0.026元/(kW·h)	0.9	20

设备名称	功率限制/kW
系统与电网的交换功率	-12≤P₁≤12
热电联供机组	0≤P₂≤30
燃气锅炉	0≤P₃≤30
电制冷机	0≤P₄≤30
吸收式制冷机	0≤P₅≤30
蓄电池	-5≤P₆≤5
热储	-7.5≤P₇≤7.5
冷储	-12≤P₈≤12