Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation

Xiao, Jun; Zhang, Zequn; Bai, Linquan; Liang, Haishen

doi:10.1049/iet-gtd.2015.0130

Cited by 126 publications

(91 citation statements)

References 20 publications

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“…Based on (13), if direct-sequence, inverse-sequence and zero-sequence currents change simultaneously, to obtain the maximum variation of ∆V inv , the analysis above reported should be performed taking into account (13) and, then, with respect to the spectral decomposition of all coupling sub-matrices ( In what follows, the three subsets are indicated as Ω 2 , Ω 3 and Ω 4 . Also in this case, to determine the subsets Ω 2 , Ω 3 and Ω 4 the criterion expressed by (12) can be applied and their dimensions will depend on the choice of the percentage threshold value.…”

Section: Z Inv−invmentioning

confidence: 99%

A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids

et al. 2018

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This paper deals with the problem of optimal allocation (siting and sizing) of storage resources in unbalanced three-phase low voltage microgrids. The siting and sizing problem is formulated as a mixed, non-linear, constrained optimization problem whose objective function deals with economic issues and whose constraints involve technical limitations of both network and distributed resources. Emphasis is given to the power quality issue with particular attention to unbalance reduction and voltage profile improvement. Technological issues, such as those related to the preservation of batteries' lifetime, were also taken into account. The planning problem is solved by means of a genetic algorithm which includes an inner algorithm based on sequential quadratic programming. In order to limit the processing time while maintaining reasonable accuracy, the genetic algorithm search space is significantly reduced identifying a subset of candidate buses for the siting of the storage resources. The Inherent Structure Theory of Networks and the Loading Constraints Criterion were used to identify the candidate buses. The proposed method has been applied to a low voltage test network demonstrating the effectiveness of the procedure in terms of computational burden while also preserving the accuracy of the solution.

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Section: Z Inv−invmentioning

confidence: 99%

A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids

et al. 2018

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“…Capital recovery factor (CRF) is the ratio used to calculate the present value of equal annual cash flows, shown as (15), and subjected to the interest rate r during the life time T ESS .…”

Section: Objective Function Of Upper Levelmentioning

confidence: 99%

“…Optimal planning of ESS has been previously studied in the literature of different fields, such as MGs [9][10][11], distribution networks [12][13][14][15][16][17][18], and large-scale power plants [19][20][21][22]. In terms of MGs, an optimal sizing method in [9] is proposed for the wind solar battery hybrid power system, considering two working modes of stand-alone and gridconnected.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning of energy storage system in active distribution system based on fuzzy multi-objective bi-level optimization

Wang

Chen

et al. 2017

J. Mod. Power Syst. Clean Energy

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A fuzzy multi-objective bi-level optimization problem is proposed to model the planning of energy storage system (ESS) in active distribution systems (ADS). The proposed model enables us to take into account how optimal operation strategy of ESS in the lower level can affect and be affected by the optimal allocation of ESS in the upper level. The power characteristic model of micro-grid (MG) and typical daily scenarios are established to take full consideration of time-variable nature of renewable energy generations (REGs) and load demand while easing the burden of computation. To solve the bi-level mixed integer problem, a multi-subgroup hierarchical chaos hybrid algorithm is introduced based on differential evolution (DE) and particle swarm optimization (PSO). The modified IEEE-33 bus benchmark distribution system is utilized to investigate the availability and effectiveness of the proposed model and the hybrid algorithm. Results indicate that the planning model gives an adequate consideration to the optimal operation and different roles of ESS, and has the advantages of objectiveness and reasonableness.

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“…Authors of [26] proposed an optimal planning approach for distributed energy storage to achieve better economic solution considering total power losses, but, without analyzing environmental effects. In [27], an optimization model is presented to minimize the net present value (NPV) of BESS and energy losses while reduction of environmental emission is not considered. Optimal location, capacity, and power rating of batteries are calculated in [28] to determine the 6 economic technology by considering high RES penetration.…”

Section: Introductionmentioning

confidence: 99%

Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration

et al. 2018

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Early version, also known as pre-print Link to publication from Aalborg University Citation for published version (APA): Jannesar, M. R., Sedighi, A., Savaghebi, M., & Guerrero, J. M. (2018). Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration. Applied Energy, 226, 957-966. https://doi.org/10.1016/j.apenergy.2018.06.036 General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. ? You may not further distribute the material or use it for any profit-making activity or commercial gain ? You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access to the work immediately and investigate your claim. can mitigate these disadvantages and as a result, improve the system operation.For this purpose, battery energy storage system is charged when production of photovoltaic is more than consumers' demands and discharged when consumers' demands are increased. Since the price of battery energy storage system is high, economic, environmental, and technical objectives should be considered together for its placement and sizing. In this paper, optimal placement, sizing, and daily (24 hours) charge/discharge of battery energy storage system are performed based on a cost function that includes energy arbitrage, environmental emission, energy losses, transmission access fee, as well as capital and maintenance costs of battery energy storage system. All simulations are carried out in DIgSILENT and MATLAB linked together. Results show that by using the proposed approach, overvoltage 2 and energy losses are decreased, reverse power flow is prevented, environmental emission is reduced, and economic profit is maximized.

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Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation

Cited by 126 publications

References 20 publications

A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids

A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids

Optimal planning of energy storage system in active distribution system based on fuzzy multi-objective bi-level optimization

Optimal placement, sizing, and daily charge/discharge of battery energy storage in low voltage distribution network with high photovoltaic penetration

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