Optimal sizing and techno-economic analysis of energy- and cost-efficient standalone multi-carrier microgrid

• Published in: Energy (Oxford) Vol. 178; pp. 751 - 764
• Main Authors: Lorestani, Alireza, Gharehpetian, G.B., Nazari, Mohammad Hassan
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2019; Elsevier BV
• Subjects: Algorithms; Batteries; CHP system; Computer simulation; Configurations; Cost analysis; cost effectiveness; Distributed generation; Economic analysis; Economics; electric power; Energy; Energy costs; Energy efficiency; Energy management; Energy storage; Evolutionary algorithms; Heuristic methods; Long-term planning; Maintenance costs; Metaheuristic optimization algorithms; Multi-carrier microgrid; Natural gas; Objective function; Particle swarm optimization; Photovoltaics; planning; Reliability; Renewable energy; renewable energy sources; Resource management; Sizing; system optimization; Thermal energy; Turbines; Wind power; Wind turbines; Metaheuristic optimization algorithms; Renewable energy; Multi-carrier microgrid; CHP system
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2019.04.152

The objective of this study is optimal sizing and techno-economic analysis of an energy- and cost-efficient standalone multi-carrier microgrid (SMCMG). This SMCMG is with the integration of photovoltaic-thermal (PVT), wind turbine (WT), micro-turbine (MT), electrical energy storage (EES), thermal energy storage (TES), and backup natural gas boiler (GB) units. For this aim, a long-term planning approach is put forward, taking into account battery degradation and reliability considerations. Total annual cost (TAC) is served as the objective function of the optimization problem, which covers investment, replacement, fuel, and operation and maintenance costs. A rule-based energy management system (EMS), which prioritizes the application of renewable energy (RE) resources, is introduced to administrate the SMCMG operation and maximize RE utilization. To solve the optimization problem, a robust metaheuristic optimization algorithm, called evolutionary particle swarm optimization (E-PSO), is employed, and the results are validated. The simulations are conducted based on real data from Rafsanjan, Iran. The superiority of the E-PSO algorithm is demonstrated. Various techno-economic analyses are conducted, and different configurations for SMCMG are studied. The results signify the competence of the proposed configuration for SMCMG from economic, energy efficiency, reliability, and environmental points of view. •Optimal sizing of a novel standalone multi-carrier microgrid is addressed.•A linear model for the EES degradation is integrated into the long term simulation.•A robust metaheuristic optimization algorithm is used and validated.•Effectiveness of the utilization of PVT beside the MT in SMCMG is addressed.•Comprehensive techno-economic analyses are conducted.