Accuracy Improvement Method of Energy Storage Utilization with DC Voltage Estimation in Large-Scale Photovoltaic Power Plants

Yeuntae Yoo, Gilsoo Jang, Jeong-Hwan Kim, Iseul Nam, Minhan Yoon and Seungmin Jung
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Yeuntae Yoo: School of Electrical Engineering, Korea University, Seoul 136-713, Korea
Gilsoo Jang: School of Electrical Engineering, Korea University, Seoul 136-713, Korea
Jeong-Hwan Kim: Department of Electrical Engineering, Hanbat National University, Daejeon 305-719, Korea
Iseul Nam: Department of Electrical Engineering, Hanbat National University, Daejeon 305-719, Korea
Minhan Yoon: Department of Electrical Engineering, Tongmyong University, Busan 48520, Korea
Seungmin Jung: Department of Electrical Engineering, Hanbat National University, Daejeon 305-719, Korea

Energies, 2019, vol. 12, issue 20, 1-15

Abstract: In regard to electric devices, currently designed large-scale distributed generation systems require a precise prediction strategy based on the composition of internal component owing to an environmental fluctuating condition and forecasted power variation. A number of renewable resources, such as solar or marine based energies, are made up of a low voltage direct current (DC) network. In addition to actively considering a power compensation plan, these generation systems have negative effects, which can be induced to a connected power system. When a storage is connected to a DC-based generation system on an inner network along with other generators, a precise state analysis plan should back the utilization process. This paper presents a cooperative operating condition, consisting of the shared DC section, which includes photovoltaic (PVs) and energy storage devices. An active storage management plan with voltage-expectation is introduced and compared via a commercialized electro-magnetic transient simulation tool with designed environmental conditions. Owing to their complexity, the case studies were sequentially advanced by dividing state analysis verification and storage device operation.

Keywords: PV diagnosis; ESS application; DC power flow; DC system dynamics; hybrid generation system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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