Optimal battery energy storage system control in microgrid with renewable energy generation

In microgrid operation, one of the most vital tasks of the system control is to wiselydecide between selling excess power to the local grid or charge the Battery Energy Storage System (BESS). Our study uses Mixed-Integer Linear Programming to investigate the impact of storage system on the operational cost of a microgrid. The results suggested that the presence of BESS would relieve the pressure on the utility grid but not the cost of electricity due to the expensive nature of the storage plant. In view of this, it will be more beneficial to sell excess renewable generated power to the utility grid than to invest in a storage system for larger microgrids.

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Optimal Operation and Management for Smart Grid Subsumed High Penetration of Renewable Energy, Electric Vehicle, and Battery Energy Storage System

ENERGYO ◽

10.1515/energyo.0034.00426 ◽

2018 ◽

Author(s):

Ryuto Shigenobu ◽

Ahmad Samim Noorzad ◽

Cirio Muarapaz ◽

Atsushi Yona ◽

Tomonobu Senjyu

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Storage System ◽

Energy Storage System ◽

Optimal Operation ◽

Battery Energy Storage System ◽

Battery Energy Storage ◽

High Penetration ◽

Battery Energy ◽

Operation And Management

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Battery Energy Storage System for Aggregated Inertia-Droop Control and a Novel Frequency Dependent State-of-Charge Recovery

Energies ◽

10.3390/en13082003 ◽

2020 ◽

Vol 13 (8) ◽

pp. 2003 ◽

Cited By ~ 5

Author(s):

Ujjwal Datta ◽

Akhtar Kalam ◽

Juan Shi

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Storage System ◽

Energy Storage System ◽

State Of Charge ◽

Battery Energy Storage System ◽

Frequency Dependent ◽

Battery Energy Storage ◽

Battery Energy ◽

Dependent State

To deal with the technical challenges of renewable energy penetration, this paper focuses on improving the grid voltage and frequency responses in a hybrid renewable energy source integrated power system following load and generation contingency events. A consolidated methodology is proposed to employ a battery energy storage system (BESS) to contribute to voltage regulation through droop-type control and frequency regulation by assimilated inertia emulation (IE) and droop-type control. In addition, a novel frequency-dependent state-of-charge (SOC) recovery (FDSR) is presented to regulate BESS power consumption within the FDSR constraints and recharge the battery during idle periods whenever needed. The efficacy of the proposed BESS controller is demonstrated in an IEEE-9 bus system with a 22.5% photovoltaics (PV) and wind penetration level. The simulation results obtained manifest the satisfactory performance of the proposed controller in regulating simultaneous voltage and frequency in terms of lower rate of change of frequency and better frequency nadir. Furthermore, the proposed FDSR demonstrates its superiority at the time of SOC recovery compared to the conventional approach.

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Effects of a Battery Energy Storage System on the Operating Schedule of a Renewable Energy-Based Time-of-Use Rate Industrial User under the Demand Bidding Mechanism of Taipower

Sustainability ◽

10.3390/su13063576 ◽

2021 ◽

Vol 13 (6) ◽

pp. 3576

Author(s):

Cheng-Ta Tsai ◽

Yu-Shan Cheng ◽

Kuen-Huei Lin ◽

Chun-Lung Chen

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Storage System ◽

Energy Storage System ◽

Battery Energy Storage System ◽

Peak Shaving ◽

Battery Energy Storage ◽

Operating Schedule ◽

Bidding Mechanism ◽

Battery Energy

Due to the increased development of the smart grid, it is becoming crucial to have an efficient energy management system for a time-of-use (TOU) rate industrial user in Taiwan. In this paper, an extension of the direct search method (DSM) is developed to deal with the operating schedule of a TOU rate industrial user under the demand bidding mechanism of Taipower. To maximize the total incentive obtained from the Taiwan Power Company (TPC, namely Taipower), several operational strategies using a battery energy storage system (BESS) are evaluated in the study to perform peak shaving and realize energy conservation. The effectiveness of the proposed DSM algorithm is validated with the TOU rate industrial user of the TPC. Numerical experiments are carried out to provide a favorable indication of whether to invest in a BESS for the renewable energy-based TOU rate industrial user in order to execute the demand bidding program (DBP).

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