Abstract
Optimal sizing of power systems has a tremendous effective role in reducing the total system cost by preventing unneeded investment in installing unnecessary generating units. This paper presents an optimal sizing and planning strategy for a completely hybrid renewable energy power system in a remote Japanese island, which is composed of photovoltaic (PV), wind generators (WG), battery energy storage system (BESS), fuel cell (FC), seawater electrolysis plant, and hydrogen tank. Demand response programs are applied to overcome the performance variance of renewable energy systems (RESs) as they offer an efficient solution for many problems such as generation cost, high demand peak to average ratios, and assist grid reliability during peak load periods. Real-Time Pricing (RTP), which is deployed in this work, is one of the main price-based demand response groups used to regulate electricity consumption of consumers. Four case studies are considered to confirm the robustness and effectiveness of the proposed schemes. Mixed-Integer Linear Programming (MILP) is utilized to optimize the size of the system’s components to decrease the total system cost and maximize the profits at the same time.
Highlights
Emissions of greenhouse gases (GHGs) are increasing every day, and the awful impacts of GHGs are often regarded as one of the greatest dangers to the world’s biological framework and human race [1]
This paper discusses the optimal sizing of a renewable microgrid in a remote Japanese island, with the introduction of demand response and seawater electrolysis facilities
The mixed-integer linear programming technique is utilized for sizing with maximization of system revenues compared to the total cost as an objective function
Summary
Emissions of greenhouse gases (GHGs) are increasing every day, and the awful impacts of GHGs are often regarded as one of the greatest dangers to the world’s biological framework and human race [1]. Instead of combining all functions in a single device into a UFC, the electrolysis cycle and power generation are separated into two devices in a DFC network [19] Smart grid these days utilizes hydrogen storage technologies. Many authors have studied the optimum operation of hybrid microgrids, including demand response and renewable energy. In [26], the authors used Genetic Algorithms (GAs) with multi-objectives, which are integrated in HOMER software for optimal sizing of hybrid renewable systems with wind and solar energy generators and compared the results with HYRES tool in MATLAB. The optimal integration of renewable energy conversion systems, including PV and wind generators in microgrid with reversible solid oxide cells (rSOC), is presented in [27].
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