scholarly journals Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

2017 ◽  
Vol 05 (04) ◽  
pp. 766-773
Author(s):  
Ya-Chin Chang ◽  
Rung-Fang Chang
Keyword(s):  
Power Plant ◽  
Demand Response ◽  
Storage System ◽  
Energy Storage System ◽  
Virtual Power ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Virtual Power Plant ◽  
Power Plant Operation ◽  
Battery Energy

Techno-economics analysis of battery energy storage system (bess) design for virtual power plant (VPP)–A case study in Malaysia

2021 ◽  
Vol 38 ◽  
pp. 102568
Author(s):  
Wan Syakirah Wan Abdullah ◽  
Miszaina Osman ◽  
Mohd Zainal Abidin Ab Kadir ◽  
Renuga Verayiah ◽  
Nur Fadilah Ab Aziz ◽  
...  
Keyword(s):  
Power Plant ◽  
Storage System ◽  
Energy Storage System ◽  
Virtual Power ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Virtual Power Plant ◽  
Battery Energy ◽  
Economics Analysis

scholarly journals Adequacy Assessment of Wind Integrated Generating Systems Incorporating Demand Response and Battery Energy Storage System

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2649 ◽  
Author(s):  
Jiashen Teh
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Peak Load ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy ◽  
Generating System

The demand response and battery energy storage system (BESS) will play a key role in the future of low carbon networks, coupled with new developments of battery technology driven mainly by the integration of renewable energy sources. However, studies that investigate the impacts of BESS and its demand response on the adequacy of a power supply are lacking. Thus, a need exists to address this important gap. Hence, this paper investigates the adequacy of a generating system that is highly integrated with wind power in meeting load demand. In adequacy studies, the impacts of demand response and battery energy storage system are considered. The demand response program is applied using the peak clipping and valley filling techniques at various percentages of the peak load. Three practical strategies of the BESS operation model are described in this paper, and all their impacts on the adequacy of the generating system are evaluated. The reliability impacts of various wind penetration levels on the generating system are also explored. Finally, different charging and discharging rates and capacities of the BESS are considered when evaluating their impacts on the adequacy of the generating system.

scholarly journals A Mixed Receding Horizon Control Strategy for Battery Energy Storage System Scheduling in a Hybrid PV and Wind Power Plant with Different Forecast Techniques

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2326 ◽  
Author(s):  
Yuqing Yang ◽  
Stephen Bremner ◽  
Chris Menictas ◽  
Merlinde Kay
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Storage System ◽  
Energy Storage System ◽  
Receding Horizon Control ◽  
Wind Power Plant ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy ◽  
The Cost

This paper presents a mixed receding horizon control (RHC) strategy for the optimal scheduling of a battery energy storage system (BESS) in a hybrid PV and wind power plant while satisfying multiple operational constraints. The overall optimisation problem was reformulated as a mixed-integer linear programming (MILP) problem, aimed at minimising the total operating cost of the entire system. The cost function of this MILP is composed of the profits of selling electricity, the cost of purchasing ancillary services for undersupply and oversupply, and the operation and maintenance cost of each component. To investigate the impacts of day-ahead and hour-ahead forecasting for battery optimisation, four forecasting methods, including persistence, Elman neural network, wavelet neural network and autoregressive integrated moving average (ARIMA), were applied for both day-ahead and hour-ahead forecasting. Numerical simulations demonstrated the significant increased efficiency of the proposed mixed RHC strategy, which improved the total operation profit by almost 29% in one year, in contrast to the day-ahead RHC strategy. Moreover, the simulation results also verified the significance of using more accurate forecasting techniques, where ARIMA can reduce the total operation cost by almost 5% during the whole year operation when compared to the persistence method as the benchmark.

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