Optimal Sizing of a Vanadium Redox Battery System for Microgrid Systems

Nguyen, Tu A.; Crow, M.L.; Elmore, Andrew Curtis

doi:10.1109/tste.2015.2404780

Cited by 175 publications

(86 citation statements)

References 15 publications

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“…The impact of the DES size on the microgrid operation cost is further investigated. An iterative based method is implemented in [23][24][25][26] to determine the optimal DES size. The microgrid unit commitment problem is solved for different DES sizes within predetermined minimum and maximum values, as shown in Figure 2.…”

Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

“…The microgrid unit commitment problem is solved for different DES sizes within predetermined minimum and maximum values, as shown in Figure 2. The unit commitment problem is solved by implementing dynamic programming (DP) in [23], knowledge based expert system controller (KBES) in [24], mixed integer nonlinear programming (MINLP) in [25], and MILP in [26]. The work in [23] focuses on determining the optimal power rating and energy rating of a Vanadium Redox Battery (VRB), taking into account the nonlinear relationship between the VRB power and efficiency.…”

Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

“…The unit commitment problem is solved by implementing dynamic programming (DP) in [23], knowledge based expert system controller (KBES) in [24], mixed integer nonlinear programming (MINLP) in [25], and MILP in [26]. The work in [23] focuses on determining the optimal power rating and energy rating of a Vanadium Redox Battery (VRB), taking into account the nonlinear relationship between the VRB power and efficiency. Different DES technologies are considered in [24] and it is found that the minimum energy cost is obtained when a lead acid battery is installed which makes it the optimal DES technology choice for the considered microgrid.…”

Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

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State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

et al. 2017

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Distributed energy storage (DES) plays an important role in microgrid operation and control, as it can potentially improve local reliability and resilience, reduce operation cost, and mitigate challenges caused by high penetration renewable generation. However, to ensure an acceptable economic and technical performance, DES must be optimally sized and placed. This paper reviews the existing DES sizing methods for microgrid applications and presents a generic sizing method that enables microgrid planners to efficiently determine the optimal DES size, technology, and location. The proposed method takes into consideration the impact of DES operation on its lifetime to enhance the obtained results accuracy and practicality. The presented model can be used for both grid-tied (considering both grid-connected and islanded modes) and isolated microgrids.

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Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

Section: Cost-based Des Sizing Methodsmentioning

confidence: 99%

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State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

et al. 2017

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“…Therefore, the reasonable optimal sizing of BESS system in PV-MG has become one of the focus researches of many scholars. At present, research of BESS capacity optimization is mainly focused on: (1) BESS optimal sizing method under two scenarios of single and hybrid BESS systems [3,4]; (2) BESS optimal sizing principle under the off-grid and gird-connected operation of MG [5,6]; (3) BESS optimization analysis methods, such as the difference supplement method, fluctuation smoothing analysis method [7,8]; (4) for particular types of PV-MG, such as industrial and commercial MG, quantitative analysis is carried out on the economic benefits of BESS system optimal sizing [9,10]. [10] focused on the optimization of the capacities of components in the PV-based BSS (battery switch stations) with consideration of battery swapping requirement and maximally utilizing PV energy.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response

et al. 2016

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Abstract:In order to solve the influence of uncertain photovoltaic power (PV) on the stable operation of microgrid (MG), demand response (DR) and battery energy storage system (BESS) need to be introduced simultaneously into the operation optimal scheduling of PV-based microgrid (PV-MG). Therefore, it is of great significance for commercial investment decisions of PV-MG to consider the influence of DR on BESS optimal sizing. Under the peak-valley time-of-use (TOU) price, this paper builds cross-time DR models based on price elasticity matrix. Furthermore, through the introduction of DR and BESS into PV-MG scheduling optimization, the MG investment and benefit model is proposed. Considering the constraint condition such as co-ordination of supply and demand, electricity price elasticity and energy loss of storage system, the improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimal allocation model of the BESS with the target of maximum PV consumptive rate and annual net profits. The optimization method was applied to a PV-MG in Guangdong. Through the regulation and control effect of demand response and BESS on load distribution, the uncertainties PV power can be suppressed so as to improve the PV system consumptive level, which is of great guiding significance for BESS optimal sizing under this situation.Keywords: time-of-use (TOU) price; multi-period demand response (DR); battery energy storage system (BESS); photovoltaic consumptive rate; investment and benefit model; multi-objective optimization; non-dominated sorting genetic algorithm II (NSGA-II) algorithm

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“…The power fluctuation is decomposed into high-frequency component and low-frequency component, then ES and diesel generators are assigned to these two parts of power correspondingly for power smoothing according to their respond characteristics. The authors of [30] proposed an optimal sizing method of a Vanadium Redox battery in MG and the cost-effective solution is obtained based on the optimal ratings for the battery in both short-term (one-day) and long-term (entire year) scenarios proposed in the paper.…”

Section: Introductionmentioning

confidence: 99%

Optimized Planning of Power Source Capacity in Microgrid, Considering Combinations of Energy Storage Devices

et al. 2016

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Since renewable energy resource is universally accepted as a promising method to solve the global energy problem, optimal planning and utilization of various distributed generators (DG) and energy storage (ES) devices deserve special concern. ES devices possess various characteristics in power density, energy density, response speed (switching speed) and lifetime. Besides, as different load types have various requirements on power supply reliability according to their importance, coordinated planning with consideration of reasonable matching between power source and load can efficiently improve power supply reliability and economic efficiency via a customized power supply and compensation strategy. This paper focuses on optimization of power source capacity in microgrid and a coordinated planning strategy is proposed with integrated consideration of characteristics of DG, ES and load. An index named additional compensation ratio (ACR) for balancing economic efficiency and reliability is proposed and considered in the strategy. The objective function which aims to minimize life cycle cost (LCC) is established considering economic efficiency, reliability and environmental conservation. The proposed planning strategy and optimizing model is calculated and verified through case study of an autonomy microgrid.

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Optimal Sizing of a Vanadium Redox Battery System for Microgrid Systems

Cited by 175 publications

References 15 publications

State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response

Optimized Planning of Power Source Capacity in Microgrid, Considering Combinations of Energy Storage Devices

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