Abstract
Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES) in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV) panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes) is maximized. To effectively solve this multi-objective problem (MOP), the multi-objective evolutionary algorithm based on decomposition (MOEA/D) using localized penalty-based boundary intersection (LPBI) method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified.
Highlights
The increasing consumption of fossil fuels coupled with environmental degradation has resulted in the growth of eco-friendly renewable energy resources [1]
multi-objective evolutionary algorithm (MOEA) based on decomposition (MOEA/D)-localized penalty-based boundary intersection (LPBI) is applied to solve the multi-objective hybrid renewable energy system (HRES) model after it has been examined on a set of multi-objective problem (MOP) benchmarks
This paper studies the multi-objective optimal design of hybrid PV-wind-diesel-battery system for the power-supply, considering that three objectives are simultaneously to be minimized in the specialized operational mode
Summary
The increasing consumption of fossil fuels coupled with environmental degradation has resulted in the growth of eco-friendly renewable energy resources [1]. The most popular approach proposed to solve these kinds of problems is a multi-objective evolutionary algorithm (MOEA), which has been used to design or schedule many hybrid power systems [1,5,6,7,8,9]. Energies 2017, 10, 674 research area for computational efficiency and scalability It has been applied in [13] to optimize an HRES in which the cost, CO2 and SO2 emissions are minimized and the output power is maximized. The multi-objective design of HRES that operates in both isolated-island and grid-connected modes is modelled and simulated. The optimal operational strategy for each mode is provided; and (iii) a simple yet effective algorithm, namely, MOEA/D with a localized penalty-based boundary intersection (LPBI) method (denoted as MOEA/D-LPBI) is proposed for the multi-objective design of HRES in both modes.
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