Optimal Design of an On-Grid MicroGrid Considering Long-Term Load Demand Forecasting: A Case Study

  • Bing Han College of Science, Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China; Institute of New Energy Science and Technology of Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China
  • Mingxuan Li The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hubei, 075000, China
  • Jingjing Song The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hubei, 075000, China
  • Junjie Li College of Science, Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China; Institute of New Energy Science and Technology of Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China
  • Jamal Faraji Energy Research Institute, University of Kashan, Kashan, Iran
Keywords: Artificial neural networks (ANNs), load forecasting, microgrids (MGs), renewable energy sources (RESs), multilayer perceptron (MLP)

Abstract

In this article, an optimal on-grid MicroGrid (MG) is designed considering long-term load demand prediction. Multilayer Perceptron (MLP) Artificial Neural Network (ANN) has been used for time-series load prediction. Yearly demand growth has also been considered in the optimization process based on the forecasted load profile. Two case studies have been performed with the forecasted and historical load profiles, respectively. It has been shown that by applying the forecasted load profile, realistic results of net present cost (NPC), cost of energy (COE) and MG configuration would be achieved. Moreover, it has been demonstrated that utilizing battery storage systems (BSSs) are not economic in the proposed system. The introduced MG also produces lower emission compared to the system with the historical load profile.

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Author Biographies

Bing Han, College of Science, Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China; Institute of New Energy Science and Technology of Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China

Bing Han (1978–) Man, Han nationality, born in Anguo, Hebei, China. Master degree, Associate professor, The research direction: Intelligent micro grid control, Electric energy quality, etc.

Mingxuan Li, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hubei, 075000, China

Mingxuan Li, (1992–) Man, Han nationality, born in Zhangjiakou, Hebei, China, Master degree, The research direction: accounting, etc.

Jingjing Song, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hubei, 075000, China

Jingjing Song (1992–) Woman, Han nationality, born in Zhangjiakou, Hebei, China, Undergraduate, The research direction: Administrative management, etc.

Junjie Li, College of Science, Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China; Institute of New Energy Science and Technology of Hebei North University, Zhang Jiakou, Hebei Province, 075000, PR China

Junjie Li (1968–) Man, Han nationality, born in Zhangjiakou, Hebei, China. Master degree, professor, The research direction: Physics, etc.

Jamal Faraji, Energy Research Institute, University of Kashan, Kashan, Iran

Jamal Faraji was born in Tehran, Iran, in 1996. He received the B.S. degree in electrical engineering from Islamic Azad University, Tehran, in 2017, and the M.Sc. degree in energy systems engineering from the University of Kashan, Kashan, Iran, in 2020. His research interests are smart grids, microgrid operation, energy markets, energy hubs, and optimization methods.

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Published
2021-04-30
Section
Articles