An Improved ABC Algorithm for Energy Management of Microgrid

Authors

  • Ren Gao
  • Juebo Wu 1. Department of Geography, National University of Singapore Arts Link, Singapore 117570 2. ZTE Corporation No.55, Science and Technology South Road, Shenzhen, China
  • Wen Hu Hubei University of Economics No. 8, Yangqiaohu Avenue, Jiangxia District, Wuhan, China
  • Yun Zhang Wuhan University No. 299, Bayi Road, Wuchang District, Wuhan, China

Keywords:

Artificial Bee Colony (ABC), optimization, economic dispatch, microgrid, swarm intelligence

Abstract

Microgrids are an ideal way of electricity generation, distribution, and regulation for customers by means of distributed energy resources on the community level. However, due to the randomness of photovoltaic and wind power generation, it is a crucial and difficult problem to achieve optimal economic dispatch in microgrids. In this paper, we present an optimal economic dispatch solution for a microgrid by the improved artificial bee colony (ABC) optimization, with the aim of satisfying load and balance demand while minimizing the cost of power generation and gas emission. Firstly, we construct a mathematical model according to different characteristics of distributed generation units and loads, and improve the performance of global convergence for ABC in order to fit such model. Secondly, we explore how to solve the optimal economic dispatch problem by the improved ABC and give the essential steps. Thirdly, we carry out several simulations and the results illustrate the benefits and effectiveness of the proposed approach for optimal economic dispatch in microgrid.

Author Biography

Ren Gao

Dean of School of Information Engineering, HBUE Assistant Professor, School of Information Engineering, Hubei University of Economics

References

Abid, S.; Zafar, A. (2017); Managing Energy in Smart Homes Using Binary Particle Swarm Optimization, Conference on Complex, Intelligent, and Software Intensive Systems, pp.189- 196, 2017.

Ahmad, M.; Khan, A. et al. (2017); A Hybrid Genetic Based on Harmony Search Method to Schedule Electric Tasks in Smart Home, International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp.154-166, 2017.

Al-Saadi, M.; Luk, P.; Economou, J. (2017); Integration of the Demand Side Management with Active and Reactive Power Economic Dispatch of Microgrids, International Conference on Intelligent Computing for Sustainable Energy and Environment, pp.653-664, 2017.

Ali, W.; Rehman, A. et al. (2017); Home Energy Management Using Social Spider and Bacterial Foraging Algorithm, International Conference on Network-Based Information Systems, pp.245-256, 2017.

Azeem, M.; Amin, S. (2017); Scheduling of Appliances in Home Energy Management System Using Elephant Herding Optimization and Enhanced Differential Evolution, International Conference on Intelligent Networking and Collaborative Systems, 132-142, 2017.

Banerjee, B.; Jayaweera, D.; Islam, S. (2016); Micro Grid Planning and Operation, Smart Power Systems and Renewable Energy System Integration, 29-47, 2016.

Batool, S.; Khalid, A. et al. (2017); Pigeon Inspired Optimization and Bacterial Foraging Optimization for Home Energy Management, Advances on Broad-Band Wireless Computing, Communication and Applications, 14-24, 2017.

Chen, B.; Yang, Z.; Huang S. et al. (2017); Cyber-Physical System Enabled Nearby Traffic Flow Modelling for Autonomous Vehicles, 36th IEEE International Performance Computing and Communications Conference, Special Session on Cyber Physical Systems: Security, Computing, and Performance (IPCCC-CPS 2017), 2017.

Das, V.; Karuppanan, P. et al. (2017); Energy Grid Management, Optimization and Economic Analysis of Microgrid, Smart Energy Grid Design for Island Countries, 289-325, 2017.

Hongze, L.; Sen, G.; Bao, W. (2011); Analysis of sensitivity of the environmental value of wind power, Energy Procedia 5, 2576-2580, 2011. https://doi.org/10.1016/j.egypro.2011.03.442

Hu, B.; Wang, H.; Yao, S. (2017); Optimal economic operation of isolated community microgrid incorporating temperature controlling devices, Protection and Control of Modern Power Systems, 2-6, 2017.

Jadav, K. A.; Karkar, H. M.; Trivedi, I. N. (2017); A Review of Microgrid Architectures and Control Strategy, Journal of The Institution of Engineers (India): Series B, 98(6), 591-598, 2017.

Jansen, R.; Karki, R. (2017); Sustainable Energy Optimization in a Smart Microgrid, Sustainable Power Systems, 111-132, 2017.

Khan, S.; Khan, A. et al. (2017); Genetic Algorithm and Earthworm Optimization Algorithm for Energy Management in Smart Grid, International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 447-459, 2017.

Kremljak, Z.; Palcic, I.; Kafol, C. (2014); Project Evaluation Using Cost-Time Investment Simulation, International Journal of Simulation Modelling, 13(4), 447-457, 2014 https://doi.org/10.2507/IJSIMM13(4)5.279

Reddy, S. S.; Park, J. Y.; Jung, C. M. (2016); Optimal operation of microgrid using hybrid differential evolution and harmony search algorithm, Frontiers in Energy, 10(3), 355-362, 2016. https://doi.org/10.1007/s11708-016-0414-x

Sharma, T. K.; Pant, M.; Singh, V. P. (2011); Artificial Bee Colony Algorithm with Self Adaptive Colony Size, International Conference on Swarm, Evolutionary, and Memetic Computing, 593-600, 2011.

Trivedi, I. N.; Jangir, P.; Bhoye, M.; Jangir, N. (2016); An economic load dispatch and multiple environmental dispatch problem solution with microgrids using interior search algorithm, Neural Computing and Applications, 1-17, 2016.

Xu, L. Z.; Yang, G. Y. et al. (2017); A Coordinated Heat and Electricity Dispatching Model for Microgrid Operation via PSO, Life System Modeling and Intelligent Computing, 213-219, 2017.

Zhang, D.; Liu, S.; Papageorgiou, L. G. (2016); Energy Management of Smart Homes with Microgrid, Advances in Energy Systems Engineering, 507-533, 2016.

Zupancic, D.; Buchmeister, B.; Aljaz, T. (2017); Reducing the Time of Task Execution with Existing Resources ¨C Comparison of Approaches, International Journal of Simulation Modelling, 16(3), 484-496, 2017 https://doi.org/10.2507/IJSIMM16(3)10.394

Published

2018-07-25

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.