TY - JOUR
T1 - Multi-Objective Optimization of System Configuration and Component Capacity in an AC Mini-grid Hybrid Power System
AU - Mohammad-Alikhani, Arta
AU - Mahmoudi, Amin
AU - Khezri, Rahmat
AU - Kahourzade, Solmaz
PY - 2022
Y1 - 2022
N2 - This paper proposes a two-stage optimization algorithm to effectively determine the system configuration at one stage, as well as the capacity of components at the other stage in the middle of the former. This algorithm fits in best with the hybrid systems with more possible types of components. The studied system, in this paper, includes diesel generators, wind turbines, photovoltaic arrays, and tidal generators as the power generation components, as well as battery banks and flywheels as the energy storage components. It also includes fuel cells and electrolyzers that either work like batteries or generate electricity in the presence of biomass. When the number of components (decision variables) increase, it becomes difficult to find an optimal solution by the conventional methods. Therefore, in this study, a two-stage multi-objective optimization algorithm is applied to design a cost-effective and environmental-friendly AC mini-grid hybrid power system. In each iteration of the proposed algorithm, first, renewable energy sources and energy storage components are selected to form a hybrid power system along with the diesel generator. Then, the capacities of the components are optimized based on the two objective functions, including levelized cost of electricity and emissions. The optimization model uses real annual data in hourly time intervals for the load, solar insolation, ambient temperature, and wind speed. It is found that the proposed algorithm decreases the susceptibility of the solutions to multiple runs compared to conventional algorithms and achieves a better optimized power system design.
AB - This paper proposes a two-stage optimization algorithm to effectively determine the system configuration at one stage, as well as the capacity of components at the other stage in the middle of the former. This algorithm fits in best with the hybrid systems with more possible types of components. The studied system, in this paper, includes diesel generators, wind turbines, photovoltaic arrays, and tidal generators as the power generation components, as well as battery banks and flywheels as the energy storage components. It also includes fuel cells and electrolyzers that either work like batteries or generate electricity in the presence of biomass. When the number of components (decision variables) increase, it becomes difficult to find an optimal solution by the conventional methods. Therefore, in this study, a two-stage multi-objective optimization algorithm is applied to design a cost-effective and environmental-friendly AC mini-grid hybrid power system. In each iteration of the proposed algorithm, first, renewable energy sources and energy storage components are selected to form a hybrid power system along with the diesel generator. Then, the capacities of the components are optimized based on the two objective functions, including levelized cost of electricity and emissions. The optimization model uses real annual data in hourly time intervals for the load, solar insolation, ambient temperature, and wind speed. It is found that the proposed algorithm decreases the susceptibility of the solutions to multiple runs compared to conventional algorithms and achieves a better optimized power system design.
KW - Batteries
KW - battery bank
KW - Costs
KW - Generators
KW - hybrid power system
KW - Hybrid power systems
KW - Hydrogen
KW - Optimization
KW - optimization
KW - power system configuration
KW - Power systems
KW - renewable energy
KW - sizing
UR - http://www.scopus.com/inward/record.url?scp=85126713746&partnerID=8YFLogxK
U2 - 10.1109/TIA.2022.3160411
DO - 10.1109/TIA.2022.3160411
M3 - Article
AN - SCOPUS:85126713746
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
SN - 0093-9994
ER -