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Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm

2022-06-02

【论文推荐】天津大学马晓燕等：基于改进鸟群算法的微电网多目标优化调度

摘要

利用智能算法解决微电网多目标优化调度问题被认为是提高微电网经济和环境友好性的有效措施，然而传统智能算法的低精度和低收敛性一直是系统运营商面临的挑战。鸟群算法(Bird swarm algorithm, BSA)作为一种新的生物启发式群智能算法，可以潜在地解决上述挑战。然而，当优化小部分多极值函数时，BSA在计算迭代过程中易陷入局部最优，并导致过早收敛。因此，为分析微电网多目标经济-环境调度并改善BSA的性能，本研究提出了一种基于自适应levy飞行策略的BSA(LF-BSA)。LF-BSA用于解决微电网调度问题，并提高系统调度收敛精度、稳定性和速度，从而提高其优化性能。本研究通过采用六个典型测试函数将 LF-BSA 与三种常用算法进行仿真比较，验证了所提算法的优越性。最后，以夏季典型日微电网能源场景为例，采用LF-BSA对微电网经济-环境多目标模型进行仿真，结果表明了LF-BSA的可行性、多目标优化的有效性以及在微电网优化中使用可再生能源和储能的必要性。

Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm

基于改进鸟群算法的微电网多目标优化调度

Xiaoyan Ma¹, Yunfei Mu¹, Yu Zhang², Chenxi Zang³, Shurong Li⁴, Xinyang Jiang¹,Meng Cui⁵

(1.Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, P.R.China 2.Global Energy Interconnection Development and Cooperation Organization, Beijing 100031, P.R.China 3.Xiamen University, Xiamen 361102, P.R.China 4.State Grid Xiongan New Area Electric Power Supply Company, Baoding 071700, P.R.China 5.State Grid Baoding Electric Power Supply Company, Baoding 071000, P.R.China)

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Multi-objective optimal microgrid dispatch based on improve

Abstract

Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However, the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm (BSA), a new bioheuristic cluster intelligent algorithm, can potentially address these challenges; however, its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic–environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA, a self-adaptive levy flight strategy-based BSA (LF–BSA) was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy, stability, and speed, thereby improving its optimization performance.Six typical test functions were used to compare the LF–BSA with three commonly accepted algorithms to verify its excellence.Finally, a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF–BSA, effectiveness of the multiobjective optimization, and necessity of using renewable energy and energy storage in microgrid dispatching optimization.

Keywords

Microgrid, Operation optimization, Bird swarm algorithm, Levy flight strategy, Self-adaptive.

Fig.1 Schematic diagram of the candidate microgrid

Fig.2 BSA behavior and its application in microgrid

Fig.3 Levy flight step distribution map

Fig.4 Flow chart of microgrid optimization dispatching based on LF-BSA

Fig.5 Convergence curves of PSO, IPSO, BSA and LF-BSA

Fig.6 Cold & electric load and inflexible DER power points of the WT, the PV & MT in 24 hours

Fig.7 FC output diagram under different objective functions

Fig.8 BT output diagram under different objective functions

Fig.9 Grid output diagram under different objective functions

Fig.10 The Pareto front curve of the case study

Fig.11 Cost diagram at each time of grid-connected operation under the Comb. mode

本文引文信息

Ma XY, Mu YF, Zhang Y, Zang CX, Li SR, Jiang XY, Cui M (2022) Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm. Global Energy Interconnection, 5(2): 154-167

马晓燕，穆云飞，张宇，臧辰熙，李树荣，姜欣阳，崔蒙 (2022) 基于改进鸟群算法的微电网多目标优化调度. 全球能源互联网（英文），5(2): 154-167

Biographies

Xiaoyan Ma

Xiaoyan Ma received her master degree from Hebei University of Technology, Tianjin,China.She is currently working towards the Ph.D.degree at Tianjin University, Tianjin,China.Her research interests include the optimal operation of microgrid, the integration of 5G base stations and power grids, et al.

Yunfei Mu

Yunfei Mu received his bachelor, master and Ph.D.degrees from Tianjin University, Tianjin,China, in 2007, 2009, and 2012, respectively.He is currently a Professor of electrical engineering in the School of Electrical and Information Engineering, Tianjin University.From 2010 to 2011, he was a Research Assistant with the school of Engineering,Cardiff University, Cardiff, U.K.His research interests include power system stability analysis and control, demand response, integrated energy system and the optimal operation of microgrid, et al.

Yu Zhang

Yu Zhang received his bachelor degree in North China Electric Power University and Ph.D.in Tsinghua University.He is working in Global Energy Interconnection Development and Cooperation Organization.His research interests include the optimal operation of microgrid, renewable energy, et al.

Chenxi Zang

Chenxi Zang is currently working towards the bachelor degree at Xiamen University,Xiamen, China.His research interests include automation technology, renewable energy, et al.

Shurong Li

Shurong Li received his bachelor and master degrees from Shandong University, Jinan,China, in 2011 and 2019, respectively.He is currently working in the China State Grid,Xiongan New Area Electric Power Supply Company, Hebei, P.R.China.His research interests include the optimal operation of microgrid.

Xinyang Jiang

Xinyang Jiang is about to pursue the master degree at Tianjin University, Tianjin, China,in 2022.His research interests include the integration of 5G base stations and power grids and the base station backup energy storage.

Meng Cui

Meng Cui received her bachelor degree from the China Three Gorges University,Yichang, China, in 2018.She is currently an administrator at the electric power dispatching and control center of the State Grid Baoding Electric Power Supply Company.Her research interests include the automatic operation of smart grid, et al.

编辑：王彦博

审核：王伟

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Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm

【论文推荐】天津大学 马晓燕等：基于改进鸟群算法的微电网多目标优化调度

郑重声明

【论文推荐】天津大学马晓燕等：基于改进鸟群算法的微电网多目标优化调度