Integrated Multi-Criteria Planning for Resilient Renewable Energy-Based Microgrid Considering Advanced Demand Response and Uncertainty

Mark Kipngetich Kiptoo (), Oludamilare Bode Adewuyi (), Masahiro Furukakoi, Paras Mandal and Tomonobu Senjyu
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Mark Kipngetich Kiptoo: Graduate School of Science and Engineering, University of the Ryukyus, Nishihara 903-0213, Japan
Oludamilare Bode Adewuyi: Faculty of Engineering, Information and Systems, University of Tsukuba, 1 Chome-1-1 Tennodai, Ibaraki 305-8577, Japan
Masahiro Furukakoi: National Institute of Technology, Sasebo College, Sasebo 857-1193, Japan
Paras Mandal: Department of Electrical and Computer Engineering, University of Texas at El Paso, El Paso, TX 79968, USA
Tomonobu Senjyu: Graduate School of Science and Engineering, University of the Ryukyus, Nishihara 903-0213, Japan

Energies, 2023, vol. 16, issue 19, 1-25

Abstract: Weather-driven uncertainties and other extreme events, particularly with the increasing reliance on variable renewable energy (VRE), have made achieving a reliable microgrid operation increasingly challenging. This research proposes a comprehensive and integrated planning strategy for capacity sizing and operational planning, incorporating forecasting and demand response program (DRP) strategies to address microgrid operation under various conditions, accounting for uncertainties. The microgrid includes photovoltaic systems, wind turbines, and battery energy storage. Uncertainties in VREs and load fluctuations are modeled using Monte Carlo simulations (MCSs), while forecasting is based on the long short-term memory (LSTM) model. To determine the best techno-economic planning approach, six cases are formulated and solved using a multi-objective particle swarm optimization with multi-criteria ranking for these three objectives: total lifecycle costs (TLCC), reliability criteria, and surplus VRE curtailment. Shortage/surplus adaptive pricing combined with variable peak critical peak pricing (SSAP VP-CPP) DRP is devised and compared with a time-of-use VP-CPP DRP in mitigating the impacts of both critical and non-critical events in the system. The simulation results show that the integrated planning, which combines LSTM forecasting with DRP strategies, achieved about 7% and 5% TLCC reductions for deterministic and stochastic approaches, respectively. The approach allowed optimal sizing and operation planning, improving the utilization of VREs and effectively managing uncertainty, resulting in the most cost-effective and robust VRE-based microgrid with enhanced resilience and reliability.

Keywords: variable renewable energy sources (VREs); demand response program (DRP); shortage/surplus-based adaptive pricing (SSAP); deficiency of power supply probability (DPSP); variable peak critical peak pricing VP-CPP DRP (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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