A scenario reduction approach for optimal sizing of energy storage systems in power distribution networks

Bucciarelli, Martina; Paoletti, Simone; Vicino, Antonio

doi:10.1109/cdc.2017.8264322

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…Morales et al [29] proposed a novel scenario reduction procedure that compares with the existing ones for electricity-market problems mitigated via two-stage stochastic programming. Bucciarelli et al [30] proposed a novel scenario reduction procedure consisting of solving a sequence of problems with scenario sets of increasing size. Compared with other scenario reduction methods, the clustering method, as an effective scenario reduction technology, can improve the efficiency and accuracy of processing large-scale scenarios significantly.…”

Section: Introductionmentioning

confidence: 99%

“…Bucciarelli et al . [30] proposed a novel scenario reduction procedure consisting of solving a sequence of problems with scenario sets of increasing size. Compared with other scenario reduction methods, the clustering method, as an effective scenario reduction technology, can improve the efficiency and accuracy of processing large‐scale scenarios significantly.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Yang

Jiang

Cai

et al. 2019

IET Renewable Power Generation

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Microgrid systems, such as solar photovoltaic (PV) and wind turbine (WT), integrated with diesel generator can provide adequate energy to supply increased demands and are economically feasible for current and future use considering depletion of conventional sources. It is, thus, important to determine the appropriate sizes of PV, WT, diesel generator, and associated energy storage system (ESS) for efficient, economic, and reliable operation of electric power system in microgrid. Stochastic nature of intermittent renewable energy (RE) resources complicate their planning, integration, and operation of electric power system. Therefore, it is critical to generate typical scenarios of wind speed, irradiation, and load time series to reflect their stochastic characteristic for microgrid system planning and operation. In this study, a wind-irradiation-load typical scenarios generation method is proposed for optimal sizing RE resources of microgrid. The teaching-learning-based optimisation (TLBO) method is used to find the best configuration of the microgrid system. Simulation results show that scenarios generated by the proposed model have ability to approximate the original scenarios and reduce planning data effectively.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Yang

Jiang

Cai

et al. 2019

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…In this context, appropriate sizing of storage systems is of importance not only for power system operation but also for economic consideration. In recent years, there has been extensive study on optimal sizing of ESSs for different applications with wind generation [2][3][4][5][6][7][8][9][10]. Analytical techniques are developed in [2,3] to determine optimal ESS capacity with wind integration.…”

Section: Introductionmentioning

confidence: 99%

“…Typical seven-scenario approximation of wind power forecast errors are modeled and used in the system tests. Authors in [8] focus on storage sizing for voltage support in low voltage distribution networks. The model is formulated as a stochastic optimization problem and a scenario reduction procedure is proposed to reduce the size of the problem.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Sizing of Energy Storage Systems for Wind Integration

Nguyen

2018

Eng. Technol. Appl. Sci. Res.

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In this paper, we present an optimal capacity decision model for energy storage systems (ESSs) in combined operation with wind energy in power systems. We use a two-stage stochastic programming approach to take into account both wind and load uncertainties. The planning problem is formulated as an AC optimal power flow (OPF) model with the objective of minimizing ESS installation cost and system operation cost. Stochastic wind and load inputs for the model are generated from historical data using clustering technique. The model is tested on the IEEE 39-bus system.

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Time-Coupled Probabilistic Modelling of Electric Vehicle Charging Station Load and its Application

Jiang

Lin

et al. 2018

2018 International Conference on Power System Technology (POWERCON)

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A scenario reduction approach for optimal sizing of energy storage systems in power distribution networks

Cited by 3 publications

References 18 publications

Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Stochastic Sizing of Energy Storage Systems for Wind Integration

Time-Coupled Probabilistic Modelling of Electric Vehicle Charging Station Load and its Application

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