| Title |
Techno-Economic Evaluation Software for Optimal Business Model and Sizing of Photovoltaic Power Station-Linked Energy Storage System |
| Authors |
조경희(Kyeong-Hee Cho) ; 김슬기(Seul-Ki Kim) ; 조형철(Hyung-Chul Jo) ; 손완빈(Wanbin Son) ; 김응상(Eung-Sang Kim) ; 박준호(June Ho Park) |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.9.1338 |
| Keywords |
Distributed Energy Resource; Energy Storage System; Optimal Business Model; Optimal Sizing; Photovoltaic power station; PV-ESS |
| Abstract |
Under the Korea government’s Energy Transition Roadmap, energy transition is underway with the gradual reduction of nuclear power plants and the expansion of renewable energy. Moreover, in the Third Energy Master Plan, the target share of renewable energy by 2040 was increased to 30-35%. The increase in the capacity of small-and medium-sized photovoltaic power stations (PV) is the highest among different renewable energy sources. As the output of PV power stations varies considerably, linking them with energy storage systems(ESSs)is attracting attention. When designing a PV-ESS, as the investment costs are high and the applicable support policies vary with the purpose of operation, it is important to review the economic feasibility of various models before installation. However, conducting this review might be very complex and difficult for the operator. Accordingly, the present study introduces a design program for distributed resources (MODDER) that can select the optimal capacity and business model considering the domestic policies and the operating characteristics of the distributed resources. The program comprises a database of weather information, load patterns according to application, sales unit costs, electricity rate unit costs, and renewable energy system specifications and can conveniently analyze the economic feasibility of a PV-ESS by selecting and configuring it according to the user’s purpose. Accordingly, the program helps determine the optimal capacity and business model. To verify the effectiveness of the proposed program, through a case study, simulations of a demand side management business and a renewable energy generation sale business were conducted based on actual industrial customers, and the results were analyzed. The developed program can be used to maximize the return on investment of renewable power generation and ESSs, thereby reducing investment risk and contributing to improving the acceptance of renewable energy. |