An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management

Nojavan, Sayyad; Esfetanaj, Naser Nourani

doi:10.1016/j.energy.2017.07.148

Cited by 132 publications

(41 citation statements)

References 30 publications

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“…Liu et al [32] discussed the optimal sizing of SC/Battery HESS based on optimal energy management strategy for load-haul-dump vehicles (LHDs), which considered energy consumption and the total cost of HESS. Nojavan et al [33] proposed bi-objective optimization model for optimal siting and sizing of an energy storage system in a microgrid, in which the total minimization cost and minimization of loss of load expectation (LOLE) were objectives. There are significant differences in the daily output processes of PV power stations under different weather conditions, such as daily average output, fluctuation range and frequency, etc.…”

Section: Methods Of Hess Capacity Configurationmentioning

confidence: 99%

“…Compared to analytical methods, simulations in the entire configuration space may be unnecessary for obtaining the optimum solution in a computationally efficient manner. The optimization objectives among these directed search-based methods mainly include economic indicators [30][31][32][33] and stability indicators [31,33]. Berrueta et al [30] designed a battery capacity optimization model with the objective of economic revenue maximization and solved it by employing dynamic programing and a region-elimination technique algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System

Dong

Lian

et al. 2019

Sustainability

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Hybrid energy storage systems (HESS) are an effective way to improve the output stability for a large-scale photovoltaic (PV) power generation systems. This paper presents a sizing method for HESS-equipped large-scale centralized PV power stations. The method consists of two parts: determining the power capacity by a statistical method considering the effects of multiple weather conditions and calculating the optimal energy capacity by employing a mathematical model. The method fully considers the characteristics of PV output and multiple kinds of energy storage combinations. Additionally, a pre-storage strategy that can further improve stability of output is proposed. All of the above methods were verified through a case study application to an 850 MW centralized PV power station in the upstream of the Yellow river. The optimal hybrid energy storage combination and its optimization results were obtained by this method. The results show that the optimal capacity configuration can significantly improve the stability of PV output and the pre-storage strategy can further improve the target output satisfaction rate by 8.28%.

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Section: Methods Of Hess Capacity Configurationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System

Dong

Lian

et al. 2019

Sustainability

View full text Add to dashboard Cite

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“…Esmaeili et al and Amana et al proposed a framework for network reconfiguration and DG allocation simultaneously. For optimal allocation of energy storage system (ESS) in a micro‐grid, a bi‐objective optimization model is proposed in Nojavan et al with demand response program (DRP). Two different objective functions are considered by the authors: minimization of total investment and operation cost and loss of load expectation (LOLE).…”

Section: Introductionmentioning

confidence: 99%

Optimum placement of distributed generation considering economics as well as operational issues

Manna

Goswami

2020

Int Trans Electr Energ Syst

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Summary Distributed generations (DGs) are in increased use because of numerous advantages. While determining the optimum DG placement in the network, issues related to optimum operation and controls have not been taken care of in earlier literatures. The determination of optimal DG locations in distribution network for optimum operation and control in respect of Generation and Load shedding cost (GLC), voltage, and frequency control taking into account of DG type, capacity, variation of DG output power, and load has been presented in this work. A comprehensive solution algorithm has been proposed to find out the optimum set of location of DG units that suit all probable variation of load and DG output power. Lightning search algorithm (LSA) is used to find optimal allocation of DG units in this work. For the multi‐objective function optimization, the weighting factors are optimized by using artificial bee colony (ABC) technique. A comparison study with the NSGA‐II optimization technique has also been reported in this work.

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“…In [14], a planning procedure is proposed, which takes into account the minimization of the cost of energy imported from the external grid while considering voltage support and minimization of network losses. The problem of the optimal siting and sizing of EESSs in µGs is faced in [15] through the minimization of both installation and operation costs, as well as power losses. Minimization of investment and operation costs in distribution networks is considered in the planning tool proposed in [16], which accounts for constraints on bus voltages.…”

Section: Introductionmentioning

confidence: 99%

Planning of Distributed Energy Storage Systems in μGrids Accounting for Voltage Dips

et al. 2020

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This paper deals with the optimal planning of the electrical energy storage systems in the microgrids aimed at cost minimization. The optimization accounts for the compensation of the voltage dips performed by the energy storage systems. A multi-step procedure, at the first step, identifies a set of candidate buses where the installation of a storage device produces the maximum benefit in terms of dip compensation; then, the life cycle costs in correspondence of different alternatives in terms of size and location of the storage systems are evaluated by considering an optimized use of the energy storage systems. The simulations on a medium voltage microgrid allowed validating the effectiveness of the proposed procedure.

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An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management

Cited by 132 publications

References 30 publications

Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System

Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System

Optimum placement of distributed generation considering economics as well as operational issues

Planning of Distributed Energy Storage Systems in μGrids Accounting for Voltage Dips

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