Optimization of Capacity Configuration of Wind–Solar–Diesel–Storage Using Improved Sparrow Search Algorithm
In order to reasonably allocate the capacity of distributed generation and realize the goal of stable, economic and clean operation of the system, a multi-objective optimization model with investment cost, environmental protection and power supply quality as indicators has been established, and the...
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| Published in | Journal of electrical engineering & technology Vol. 17; no. 1; pp. 1 - 14 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Singapore
01.01.2022
대한전기학회 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1975-0102 2093-7423 |
| DOI | 10.1007/s42835-021-00840-3 |
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| Abstract | In order to reasonably allocate the capacity of distributed generation and realize the goal of stable, economic and clean operation of the system, a multi-objective optimization model with investment cost, environmental protection and power supply quality as indicators has been established, and the multi-objective sparrow search algorithm is used to optimize the solution. Although the multi-objective search algorithm is more efficient than the traditional single objective algorithm, it is easy to fall into local optimum. To this end, the niche optimization technology is used to improve the optimization effect of multi-objective sparrow search algorithm, and the Levy flight strategy is introduced to enhance the ability of multi-objective sparrow search algorithm to jump out of local optimum. The calculation example uses the traditional multi-object search algorithm and the niche multi-objective sparrow search algorithm with levy disturbance to solve the proposed model. The simulation results verify the effectiveness of the multi-objective sparrow search algorithm improved by levy disturbance and niche optimization technology. |
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| AbstractList | In order to reasonably allocate the capacity of distributed generation and realize the goal of stable, economic and clean operation of the system, a multi-objective optimization model with investment cost, environmental protection and power supply quality as indicators has been established, and the multi-objective sparrow search algorithm is used to optimize the solution. Although the multi-objective search algorithm is more efficient than the traditional single objective algorithm, it is easy to fall into local optimum. To this end, the niche optimization technology is used to improve the optimization effect of multi-objective sparrow search algorithm, and the Levy flight strategy is introduced to enhance the ability of multi-objective sparrow search algorithm to jump out of local optimum. The calculation example uses the traditional multi-object search algorithm and the niche multi-objective sparrow search algorithm with levy disturbance to solve the proposed model. The simulation results verify the effectiveness of the multi-objective sparrow search algorithm improved by levy disturbance and niche optimization technology. In order to reasonably allocate the capacity of distributed generation and realize the goal of stable, economic and clean operation of the system, a multi-objective optimization model with investment cost, environmental protection and power supply quality as indicators has been established, and the multi-objective sparrow search algorithm is used to optimize the solution. Although the multi-objective search algorithm is more effi cient than the traditional single objective algorithm, it is easy to fall into local optimum. To this end, the niche optimization technology is used to improve the optimization eff ect of multi-objective sparrow search algorithm, and the Levy fl ight strategy is introduced to enhance the ability of multi-objective sparrow search algorithm to jump out of local optimum. The calculation example uses the traditional multi-object search algorithm and the niche multi-objective sparrow search algorithm with levy disturbance to solve the proposed model. The simulation results verify the eff ectiveness of the multi-objective sparrow search algorithm improved by levy disturbance and niche optimization technology KCI Citation Count: 0 |
| Author | Liu, Lianxin Si, Shuqian Dou, Zhenhai Dong, Jun Wang, Zichen |
| Author_xml | – sequence: 1 givenname: Jun surname: Dong fullname: Dong, Jun organization: Shandong University of Technology (SDUT) – sequence: 2 givenname: Zhenhai orcidid: 0000-0002-9739-4397 surname: Dou fullname: Dou, Zhenhai email: douzhenhai1105@126.com organization: Shandong University of Technology (SDUT), Inner Mongolia University of Science and Technology (IMUST), China Agricultural University (CAU) – sequence: 3 givenname: Shuqian surname: Si fullname: Si, Shuqian organization: Shandong University of Technology (SDUT) – sequence: 4 givenname: Zichen surname: Wang fullname: Wang, Zichen organization: Shandong University of Technology (SDUT) – sequence: 5 givenname: Lianxin surname: Liu fullname: Liu, Lianxin organization: Shandong University of Technology (SDUT) |
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| Cites_doi | 10.1109/TSTE.2013.2288804 10.1080/21642583.2019.1708830 10.1007/s42835-020-00345-5 10.1002/dac.4617 10.13451/j.sxu.ns.2020135 10.1016/j.ijepes.2015.11.085 10.13700/j.bh.1001-5965.2020.0298 10.1016/j.enconman.2020.112465 10.1016/j.energy.2016.09.104 10.1016/j.egyr.2020.11.102 10.1109/TIE.2011.2159692 10.3390/app9245446 10.1002/tee.23001 10.1016/J.EPSR.2020.106638 10.1109/TPWRS.2012.2237043 10.1109/TSTE.2017.2762364 10.1007/s00202-016-0475-1 10.1007/s00202-018-0726-4 10.1049/iet-gtd.2020.0625 |
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| Keywords | Sparrow search algorithm Capacity configuration Niche optimization technology |
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In: Proceedings of the IEEE international conference on evolutionary computation, pp 1456–1461 GeWTengJPanCWangSGaoKOperation regulation strategy of source-storage-load with wind energy storage energyPower Syst Protect Control2019471361006105 ZhangJLeiYLiuNXiaoRCapacity configuration optimization for island microgrid with wind/photovoltaic/diesel/storage and seawater desalination loadTrans China Electrotech Soc2014292102112 Qinghua M, Qiang Z, Chengcheng M, Jiaxuan B (2021) Mixing sine and cosine algorithm with Lévy flying chaotic sparrow algorithm[J/OL]. 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Int J Electr Power Energy Syst 80:252–263. https://doi.org/10.1016/j.ijepes.2015.11.085 XueJBoSA novel swarm intelligence optimization approach: sparrow search algorithmSyst Sci Control Eng2020812234405298010.1080/21642583.2019.1708830 Zeyu W, Jun X, Gang X, Xinying X (2021) Multi-objective sparrow search algorithm based on new crowding distance[J/OL]. Comput Eng Appl 1–10 [2021-07-06]. http://kns.cnki.net/kcms/detail/11.2127.TP.20210311.1136.008.html Al-ShetwiAQSujodMZModeling and design of photovoltaic power plant connected to the MV side of Malaysian grid with TNB technical regulation compatibilityElectr Eng201810042407241910.1007/s00202-018-0726-4 BoLYanZNaYImproved particle swarm optimization method and its application in the siting and sizing of distributed generation planningTrans China Electrotech Soc20082103108 Hirose T, Matsuo H (2012) Standalone hybrid wind-solar power generation system applying dump power control without dump load. IEEE Trans Ind Electron 59(2):988–997 Mohammadjafari M, Ebrahimi R, Darabad VP (2020) Optimal Energy management of a microgrid incorporating a novel efficient demand response and battery storage system. J Electr Eng Technol 15(3):571–590 MattiKKonstantinosPRodrigoHEENeilDPoulSApplication of microscale wind and detailed wind power plantdata in large-scale wind generation simulationsElectric PowerSyst Res202119010.1016/J.EPSR.2020.106638 ZhouTWeiSOptimization of battery-supercapacitor hybrid energy storage station in wind/solar generation systemIEEE Trans Sustain Energy20145240841510.1109/TSTE.2013.2288804 Zia U, Shaorong W, Jordan R (2019) A novel method based on PPSO for optimal placement and sizing of distributed generation. 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| References_xml | – reference: WeiYBai-yueYXiao-yaWChen-peiMYing-yingWResearch on inventory-distribution optimization of cold chainlogistics enterprises in low-carbon environmentPackaging Eng202142114552 – reference: Al-ShetwiAQSujodMZModeling and design of photovoltaic power plant connected to the MV side of Malaysian grid with TNB technical regulation compatibilityElectr Eng201810042407241910.1007/s00202-018-0726-4 – reference: EssamMAtwaYMEl-SaadanyEFContiSRizzoSAMicro-grids reliability enhancement under different penetration levels of hybrid DG unitsJ Electr Eng Technol201813414071418 – reference: ZhangJLeiYLiuNXiaoRCapacity configuration optimization for island microgrid with wind/photovoltaic/diesel/storage and seawater desalination loadTrans China Electrotech Soc2014292102112 – reference: ShengSChenYZhangJResearch on maximum power point tracking strategy based on differential evolution artificial bee colony algorithm of photovoltaic systemPower Syst Prot Control201846112329 – reference: Yu W, Wang W, Ma X, Zhang Z, Wu X (2018) Optimization design of hybrid wind-PV system based on improved genetic algorithm. Res Explor Lab 37(1):125–129+185 – reference: ElazimSMAAliESOptimal locations and sizing of capacitors in radial distribution systems using mine blast algorithmElectr Eng201810011910.1007/s00202-016-0475-1 – reference: Xin L, Xiaodong M, Jun Z, Zhen W (2021) Chaos sparrow search optimization algorithm. J Beijing Univ Aeronaut Astronaut 1–10 [2020-09-05]. https://doi.org/10.13700/j.bh.1001-5965.2020.0298 – reference: XueJBoSA novel swarm intelligence optimization approach: sparrow search algorithmSyst Sci Control Eng2020812234405298010.1080/21642583.2019.1708830 – reference: CaiZGeYLiYMaSOptimal placement and schedule of hybrid energy management system in microgridElectric Mach Control20172154250 – reference: Hirose T, Matsuo H (2012) Standalone hybrid wind-solar power generation system applying dump power control without dump load. IEEE Trans Ind Electron 59(2):988–997 – reference: LiuWXuYRandomised learning-based hybrid ensemble model for probabilistic forecasting of PV power generationIET Gener Transm Distrib202014245909591710.1049/iet-gtd.2020.0625 – reference: Xie X, Zhang W, Yang Z (2002) A dissipative particle swarm optimization. In: Proceedings of the IEEE international conference on evolutionary computation, pp 1456–1461 – reference: DingMWangBZhaoBChenZConfiguration optimization of capacity of standalone PV-wind-diesel-battery hybrid microgridPower Syst Technol20133703575581 – reference: AliESElazimSMAAbdelazizAYAnt lion optimization algorithm for renewable distributed generationsEnergy201611644545810.1016/j.energy.2016.09.104 – reference: Qinghua M, Qiang Z, Chengcheng M, Jiaxuan B (2021) Mixing sine and cosine algorithm with Lévy flying chaotic sparrow algorithm[J/OL]. J Shanxi Univ (Nat Sci Ed):1–6 [2021-07-06]. https://doi.org/10.13451/j.sxu.ns.2020135 – reference: Zeyu W, Jun X, Gang X, Xinying X (2021) Multi-objective sparrow search algorithm based on new crowding distance[J/OL]. Comput Eng Appl 1–10 [2021-07-06]. http://kns.cnki.net/kcms/detail/11.2127.TP.20210311.1136.008.html – reference: Georgilakis PS, Hatziargyriou ND (2013) Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans Power Syst 28(3):3420–3428. https://doi.org/10.1109/TPWRS.2012.2237043 – reference: Zheng Y, Zhao J, Song Y, Luo F, Meng K, Qiu J et al (2018) Optimal operation of battery energy storage system considering distribution system uncertainty. IEEE Trans Sustain Energy 9(3):1051–1060 – reference: Ali ES, Elazim SMA, Abdelaziz AY (2016) Improved Harmony Algorithm and Power Loss Index for optimal locations and sizing of capacitors in radial distribution systems. Int J Electr Power Energy Syst 80:252–263. https://doi.org/10.1016/j.ijepes.2015.11.085 – reference: El-HanaBHRSharjeelJMAbubakarSYShoaibSMMuhammadRMAYaqoubLDecomposition based multiobjective evolutionary algorithm for PV/Wind/Diesel Hybrid Microgrid System design considering load uncertaintyEnergy Rep20217526910.1016/j.egyr.2020.11.102 – reference: Sa’Ed JA, Amer M, Bodair A, Baransi A, Zizzo G (2019) A simplified analytical approach for optimal planning of distributed generation in electrical distribution networks. Appl Sci 9(24):5446 – reference: BoLYanZNaYImproved particle swarm optimization method and its application in the siting and sizing of distributed generation planningTrans China Electrotech Soc20082103108 – reference: Abd ElazimSMAliESOptimal network restructure via improved whale optimization approachInt J Commun Syst202010.1002/dac.4617 – reference: GeWTengJPanCWangSGaoKOperation regulation strategy of source-storage-load with wind energy storage energyPower Syst Protect Control2019471361006105 – reference: Wei-yan Z, Yun-hui F, Hua-feng J, Jia-qi L, Pei-li L, Jian-ye C et al (2016) A research review of locating and sizing distributed generation. J Nanjing Inst Technol (Nat Sci Ed) 14(03):45–51 – reference: Li Y, Wang G, Ma J, Yang H, Zhu L, Yan H (2020) Study on optimal capacity in the construction of wind-solar-diesel-battery hybrid power system based on bettle antennae search algorithm improved genetic algorithm. 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| SubjectTerms | Electrical Engineering Electrical Machines and Networks Electronics and Microelectronics Engineering Instrumentation Original Article Power Electronics 전기공학 |
| Title | Optimization of Capacity Configuration of Wind–Solar–Diesel–Storage Using Improved Sparrow Search Algorithm |
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