Comprehensive comparison on the ecological performance and environmental sustainability of three energy storage systems employed for a wind farm by using an emergy analysis

2019 ◽  
Vol 191 ◽  
pp. 1-11 ◽  
Author(s):  
Shima Yazdani ◽  
Mahdi Deymi-Dashtebayaz ◽  
Erfan Salimipour
Keyword(s):  
Energy Storage ◽  
Environmental Sustainability ◽  
Wind Farm ◽  
Storage Systems ◽  
Emergy Analysis ◽  
Energy Storage Systems ◽  
Ecological Performance ◽  
Comprehensive Comparison

scholarly journals Benefits of Energy Storage Systems for Small-Scale Wind Farm Development in Latvia

2021 ◽  
Vol 58 (2) ◽  
pp. 11-18
Author(s):  
E. Groza ◽  
M. Balodis ◽  
K. Gulbis ◽  
J. Dirba
Keyword(s):  
Energy Storage ◽  
Small Area ◽  
Wind Farm ◽  
Storage Systems ◽  
Wind Farms ◽  
Small Scale ◽  
High Wind ◽  
Energy Storage Systems ◽  
Grid Connection ◽  
Wind Potential

Abstract The paper covers the main aspects and restrictions on siting small-scale wind farms in Latvia and benefits of using energy storage systems with small-scale wind farms. The restrictions of siting have been analysed. Grid connection restrictions are addressed as the main issues for small-scale wind farm development in Latvia. Two small-scale wind farm models with similar properties have been made and analysed within the framework of the research. The paper proposes the idea for maximising the production of small-scale wind farm in a small area site with high wind potential.

scholarly journals A Joint Scheduling Optimization Model for Wind Power and Energy Storage Systems considering Carbon Emissions Trading and Demand Response

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yin Aiwei ◽  
Xu Congwei ◽  
Ju Liwei
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Demand Response ◽  
Wind Farm ◽  
Storage Systems ◽  
Thermal Power ◽  
Emission Trading ◽  
Energy Storage Systems ◽  
Load Curve ◽  
Scheduling Model

To reduce the influence of wind power random on system operation, energy storage systems (ESSs) and demand response (DR) are introduced to the traditional scheduling model of wind power and thermal power with carbon emission trading (CET). Firstly, a joint optimization scheduling model for wind power, thermal power, and ESSs is constructed. Secondly, DR and CET are integrated into the joint scheduling model. Finally, 10 thermal power units, a wind farm with 2800 MW of installed capacity, and3×80 MW ESSs are taken as the simulation system for verifying the proposed models. The results show backup service for integrating wind power into the grid is provided by ESSs based on their charge-discharge characteristics. However, system profit reduces due to ESSs’ high cost. Demand responses smooth the load curve, increase profit from power generation, and expand the wind power integration space. After introducing CET, the generation cost of thermal power units and the generation of wind power are both increased; however, the positive effect of DR on the system profit is also weakened. The simulation results reach the optimum when both DR and CET are introduced.

scholarly journals Consensus-Based SOC Balancing of Battery Energy Storage Systems in Wind Farm

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3507 ◽  
Author(s):  
Cao-Khang Nguyen ◽  
Thai-Thanh Nguyen ◽  
Hyeong-Jun Yoo ◽  
Hak-Man Kim
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Output Power ◽  
Wind Farm ◽  
Storage Systems ◽  
Consensus Algorithm ◽  
Energy Storage Systems ◽  
Battery Energy Storage ◽  
Battery Energy Storage Systems ◽  
Battery Energy

Multiple battery energy storage systems (BESSs) are used to compensate for the fluctuation in wind generations effectively. The stage of charge (SOC) of BESSs might be unbalanced due to the difference of wind speed, initial SOCs, line impedances and capabilities of BESSs, which have a negative impact on the operation of the wind farm. This paper proposes a distributed control of the wind energy conversion system (WECS) based on dynamic average consensus algorithm to balance the SOC of the BESSs in a wind farm. There are three controllers in the WECS with integrated BESS, including a machine-side controller (MSC), the grid-side controller (GSC) and battery-side controller (BSC). The MSC regulates the generator speed to capture maximum wind power. Since the BSC maintains the DC link voltage of the back-to-back (BTB) converter that is used in the WECS, an improved virtual synchronous generator (VSG) based on consensus algorithm is used for the GSC to control the output power of the WECS. The functionalities of the improved VSG are designed to compensate for the wind power fluctuation and imbalance of SOC among BESSs. The average value of SOCs obtained by the dynamic consensus algorithm is used to adjust the wind power output for balancing the SOC of batteries. With the proposed controller, the fluctuation in the output power of wind generation is reduced, and the SOCs of BESSs are maintained equally. The effectiveness of the proposed control strategy is validated through the simulation by using a MATLAB/Simulink environment.

scholarly journals Optimal Sizing of Energy Storage System for Operation of Wind Farms Considering Grid-Code Constraints

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5478
Author(s):  
Van-Hai Bui ◽  
Xuan Quynh Nguyen ◽  
Akhtar Hussain ◽  
Wencong Su
Keyword(s):  
Energy Storage ◽  
Wind Farm ◽  
Storage Systems ◽  
Storage System ◽  
Wind Farms ◽  
Energy Storage System ◽  
Transmission System ◽  
Power Constraint ◽  
Energy Storage Systems ◽  
Farm Operators

Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wind farm operators to find out the optimal size of the energy storage systems considering grid-code constraints and the local information of wind farms.

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