基于NSGA-Ⅱ算法的局域野战微电网优化配置

doi:10.12305/j.issn.1001-506X.2024.11.22

Abstract

Abstract:

In order to meet the needs of power supply in local military operations in the new era, a new local field microgrid system based on distributed generation supply and power supplement of generator vehicles is proposed. Based on the analysis of mission requirements, military environment and system resource requirements, a local field microgrid optimal configuration model is established. Compared with the general civil microgrid model, the model considers the timeliness of power supply, the stability of energy supply and anti-damage. According to the construct model, the solution algorithm is designed based on non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) framework, and the elite reservation mechanism and military decision-maker's preference factor are added. Experimental results show that the optimal configuration model of local field micro-grid accords with the reality of military operations, and the solution algorithm has better ability of fast search and global optimization.

Key words: local field, microgrid, multi-objective, evolutionary algorithm

CLC Number:

E917

Yanfeng YE, Mengjun MING, Hongtao LEI. Optimal configuration of local field microgrid based on NSGA-Ⅱ algorithm[J]. Systems Engineering and Electronics, 2024, 46(11): 3800-3806.

Figures/Tables 9

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References 28

1	张国平, 王维俊, 米红菊, 等. 基于改进粒子群算法的岛礁孤立多能源军事供电系统运行优化研究[J]. 军事运筹与系统工程, 2021, 35 (3): 52- 58.
	ZHANG G P , WANG W J , MI H J , et al. Research on operation optimization of island reef isolated multi-energy military power supply system based on improved particle swarm optimization algorithm[J]. Military Operations Research and Systems Engineering, 2021, 35 (3): 52- 58.
2	高明宇, 刘金宁, 冯长江. 军用独立型光储柴微电网模态转换控制策略[J]. 兵工自动化, 2021, 40 (6): 1- 7.
	GAO M Y , LIU J N , FENG C J . Mode conversion control strategy of military independent optical diesel storage microgrid[J]. Ordnance Automation, 2021, 40 (6): 1- 7.
3	李瑜, 张占强, 孟克其劳, 等. 基于分层控制的孤岛微电网储能优化控制策略[J]. 储能科学与技术, 2022, 11 (1): 176- 184.
	LI Y , ZHANG Z Q , MENG K Q L , et al. Optimal control strategy for energy storage of isolated island microgrid based on hierarchical control[J]. Energy Storage Science and Technology, 2022, 11 (1): 176- 184.
4	李彦生. 主动配电网分布式电源规划分析与研究[J]. 电子设计工程, 2021, 29 (12): 14- 18.
	LI Y S . Analysis and research on distributed generation planning of active distribution network[J]. Electronic Design Engineering, 2021, 29 (12): 14- 18.
5	张瑞成, 翟电杰, 张怡. 含混合储能系统直流微电网分布式协调控制策略[J]. 兵器装备工程学报, 2020, 41 (4): 232- 236. doi: 10.11809/bqzbgcxb2020.04.044
	ZHANG R C , ZHAI D J , ZHANG Y . Distributed coordinated control strategy for DC microgrid with hybrid energy storage system[J]. Journal of Ordnance Engineering, 2020, 41 (4): 232- 236. doi: 10.11809/bqzbgcxb2020.04.044
6	江宏玲. 考虑储能充放电的孤岛微电网经济优化模型[J]. 实验室研究与探索, 2022, 41 (1): 132- 137.
	JIANG H L . Economic optimization model of island microgrid considering energy storage charge and discharge[J]. Laboratory Research and Exploration, 2022, 41 (1): 132- 137.
7	冯麒铭, 刘继春, 杨阳方, 等. 含不同类型能源的多局域电网优化经济调度[J]. 电网技术, 2019, 43, 471- 480.
	FENG Q M , LIU J C , YANG Y F , et al. Optimal economic dispatch of multi local power grids with different types of energy[J]. Grid Technology, 2019, 43, 471- 480.
8	李坚, 吴亮红, 张红强, 等. 基于排序交叉优化算法的冷热电联供微电网经济调度[J]. 电力系统保护与控制, 2021, 49 (18): 137- 145.
	LI J , WU L H , ZHANG H Q , et al. Economic scheduling of combined cooling, heating and power micro grid based on sequencing cross optimization algorithm[J]. Power System Protection and Control, 2021, 49 (18): 137- 145.
9	伊洪冰, 张爱民, 刘亚东. 面向智能化战争的装备保障[J]. 军事交通学报, 2022, 1 (2): 29- 32.
	YING H B , ZHANG A M , LIU Y D . Equipment support for intelligent warfare[J]. Journal of Military Transportation, 2022, 1 (2): 29- 32.
10	苗青青, 石春艳, 张香平. 碳中和目标下的光伏发电技术[J]. 化工进展, 2022, 41 (3): 1125- 1131.
	MIAO Q Q , SHI C Y , ZHANG X P . Photovoltaic power generation technology under the goal of carbon neutralization[J]. Progress in Chemical Industry, 2022, 41 (3): 1125- 1131.
11	温春雪, 路国杰. 并网中小型风电系统最大功率跟踪控制[J]. 可再生能源, 2012, 30 (2): 13- 17.
	WEN C X , LU G J . Maximum power tracking control of grid connected small and medium-sized wind power systems[J]. Renewable Energy Sources, 2012, 30 (2): 13- 17.
12	曹阳, 温彩凤, 刘珍, 等. 基于RSM和NSGA-Ⅱ法的风电系统经济优化研究[J]. 太阳能学报, 2022, 43 (1): 161- 168.
	CAO Y , WEN C F , LIU Z , et al. Research on economic optimization of wind power system based on RSM and NSGA-Ⅱ method[J]. Journal of Solar Energy, 2022, 43 (1): 161- 168.
13	XIANG Z , ZHU Z . Multi-objective optimization of a composite orthotropic bridge with RSM and NSGA-Ⅱ algorithm[J]. Journal of Constructional Steel Research, 2022, 188, 106938.
14	孙鸿强, 张占月, 方宇强. 基于NSGA-Ⅱ算法的编队卫星重构策略[J]. 上海交通大学学报, 2021, 55 (3): 320- 330.
	SUN H Q , ZHANG Z Y , FANG Y Q . Formation satellite reconstruction strategy based on NSGA-Ⅱ algorithm[J]. Journal of Shanghai Jiaotong University, 2021, 55 (3): 320- 330.
15	陈嘉贝, 王青平, 叶源, 等. 基于NSGA-Ⅱ的波前相位畸变特性分析[J]. 系统工程与电子技术, 2022, 44 (5): 1439- 1446.
	CHEN J B , WANG Q P , YE Y , et al. Analysis of wavefront phase distortion based on NSGA-Ⅱ[J]. Systems Engineering and Electronics, 2022, 44 (5): 1439- 1446.
16	SU Z P , ZHANG G F , ZHOU X X , et al. Segment-adaptive spread spectrum audio watermarking using NSGA-Ⅱ[J]. Chinese Journal of Electronics, 2021, 30, 727- 735.
17	CHATURVEDI S , RAJASEKAR E , NATARAJAN S . Multi-objective building design optimization under operational uncertainties using the NSGA Ⅱ algorithm[J]. Buildings, 2020, 10 (88) doi: 10.3390/buildings10050088
18	ZHAGN J T , DONG Z C , CHEN T . Multi-objective optimal allocation of water resources based on the NSGA-2 algorithm while considering intergenerational equity: a case study of the middle and upper reaches of Huaihe River Basin, China[J]. International Journal of Environmental Research and Public Health, 2020, 17 (9289): 9289.
19	RASHMI P , DHARAVATH R . NSGA-2 optimized fuzzy inference system for crop plantation correctness index identification[J]. IEEE Trans.on Sustainable Computing, 2022, 7 (1): 172- 188.
20	SCHAFFER J D. Multiple objective optimization with vector evaluated genetic algorithms[C]//Proc. of the Hillsdale: L. Erlbaum Associates, 1985: 93-100.
21	FONSECA C M, FLEMING P J. Genetic algorithm for multiobjective optimization: formulation, discussion and generation[C]// Proc. of the San Mateo: Morgan Kauffman Publishers, 1993: 416-423.
22	SRINIVAS N , DEB K . Multi-objective optimization using non-dominated sorting in genetic algorithms[J]. Evolutionary Computation, 1994, 2 (3): 221- 248.
23	ZITZLER E , THIELE L . Multi-objective evolutionary algorithms: a comparative case study and the strength Pareto approach[J]. IEEE Trans.on Evolutionary Computation, 1999, 3 (4): 257- 271.
24	DEB K , PRATAP A , AGARWAL S , et al. A fast and elitist multi-objective genetic algorithm: NSGA-Ⅱ[J]. IEEE Trans.on Evolutionary Computation, 2002, 6 (2): 182- 197.
25	HORN J, NAFPLIOTIS N, GOLDBERG D E. A niched Pareto genetic algorithm for multiobjective optimization[C]//Proc. of the IEEE Congress on Evolutionary Computation, 1994: 82-87.
26	KNOWLES J D , CORNE D W . Approximating the non-dominated front using the Pareto archived evolution strategy[J]. Evolutionary Computation, 2000, 8 (2): 149- 172.
27	CORNE D W , KNOWLES J D , OATES M J . The Pareto-envelope based selection algorithm for multi-objective optimization[M]. Berlin: Springer-Verlag, 2000: 869- 878.
28	REN Y Y . Multi-task scheduling of AGVS system based on improved NSGA-Ⅱ algorithm[J]. Journal of Physics: Conference Series, 2021, 1924 (1): 012007.

节点	光伏设备	风机设备	垃圾发电	蓄电池	柴油发电机	大发电车	小发电车
节点1	√	√	√	√	√	可达	可达
节点2	√	-	-	√	√	可达	可达
节点3	-	-	-	-	√	可达	可达
节点4	√	-	-	√	√	不可达	可达
节点5	√	-	-	√	√	可达	可达
节点6	√	-	-	√	√	不可达	可达
节点7	√	-	-	√	√	可达	可达
节点8	√	-	-	√	√	可达	可达
节点9	-	-	-	-	√	不可达	可达
节点10	√	√	√	√	√	可达	可达

设备	设备参数	体积/m³	购买单价/万元	运维单价/万元
光伏设备	峰值功率2 kW/套	0.5	0.5	0.02
风机设备	额定功率6 kW/台	3	2	0.1
	启动风速3 m/s
	额定风速10 m/s
	停机风速20 m/s
柴油发电机	额定功率5 kW	0.2	0.6	0.03
柴油发电机	油耗量0.2升/(kW·h)	0.2	0.6	0.03
垃圾发电设备	日发电量120 kW·h	-	8	0.4
蓄电池	电池容量2 kW·h	0.12	0.5	0.02
大发电车	额定功率90 kW	-	20	1
大发电车	油耗量0.1升/(kW·h)	-	20	1
小发电车	额定功率50 kW	-	10	0.5
小发电车	油耗量0.1升/(kW·h)	-	10	0.5

配置点	光伏设备	风机设备	垃圾发电设备	蓄电池	柴油发电机
节点1	5	2	1	3	4
节点2	4	0	0	2	3
节点3	0	0	0	0	2
节点4	5	0	0	5	3
节点5	4	0	0	5	1
节点6	3	0	0	2	3
节点7	4	0	0	2	3
节点8	3	0	0	3	2
节点9	0	0	0	0	2
节点10	5	1	1	2	3
系统需要的小发电车数量: 1
系统需要的大发电车数量: 1
系统需要的花销和油料: 107.35万元8 287.03升

时间	负载位置	大发电车	小发电车	需发电量
第6天	节点3	-	1	24
第7天	节点3	-	1	24
第8天	节点3	-	1	24
第9天	节点3	-	1	24
第34天	节点1	-	1	33
	节点10	1	-	110
第35天	节点1	-	1	33
	节点10	1	-	110
第36天	节点1	-	1	33
	节点10	1	-	110
第40天	节点1	-	1	33
	节点3	1	-	96
第41天	节点1	-	1	33
	节点3	1	-	96
第42天	节点1	-	1	33
	节点3	1	-	96
第43天	节点1	-	1	33
	节点3	1	-	96
第82天	节点10	-	1	41.46
第83天	节点10	-	1	41.46
第84天	节点10	-	1	41.46
第85天	节点10	-	1	41.46

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Optimal configuration of local field microgrid based on NSGA-Ⅱ algorithm

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