A PSO-Optimized Fuzzy Logic Control-Based Charging Method for Individual Household Battery Storage Systems within a Community
| Autor: | Andreas Jossen, Yi-Hua Liu, Cong Nam Truong, Holger C. Hesse, Yu-Shan Cheng, Maik Naumann |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Battery (electricity)
Control and Optimization Computer science 020209 energy fuzzy logic control Control (management) Energy Engineering and Power Technology 02 engineering and technology battery charging control strategy lcsh:Technology Set (abstract data type) 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Engineering (miscellaneous) PV battery system particle swarm optimization Consumption (economics) Renewable Energy Sustainability and the Environment lcsh:T Photovoltaic system Particle swarm optimization 021001 nanoscience & nanotechnology Grid Power (physics) Reliability engineering 0210 nano-technology Energy (miscellaneous) |
| Zdroj: | Energies, Vol 11, Iss 2, p 469 (2018) Energies; Volume 11; Issue 2; Pages: 469 |
| ISSN: | 1996-1073 |
| Popis: | Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC), battery state-of-charge (SOC) and the variation of SOC (∆SOC) are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO) to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year. |
| Databáze: | OpenAIRE |
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