Multi-objective optimization for component capacity of the photovoltaic-based battery switch stations: Towards benefits of economy and environment

Liu, Nian; Chen, Zheng; Liu, Jie; Tang, Xiao; Xiao, Xiangning; Zhang, Jianhua

doi:10.1016/j.energy.2013.10.090

Cited by 54 publications

(22 citation statements)

References 22 publications

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“…Previous component capacity planning works for swapping station only consider and deal with battery configuration problem. The jointed configuration problem for both batteries and chargers are investigated recently, such as models in [13] and [21]. This paper further conducts on configuration problems for batteries, chargers and swapping robots together.…”

Section: Introductionmentioning

confidence: 99%

“…Previous works [16,17] used queuing theory to solve the EVs' swapping facilities configuration problem, while the expectation result is not applicable for some extreme cases. A multi-objective optimization problem for component capacity of PV based battery swapping station is solved in [13], aiming at maximizing the benefits of economy and environment. A capacity optimization method for PV-based BSS considering second-use of EV batteries is studied in [14].…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies such as [12][13][14][15] have identified the need for combined facility configuration problem and operation strategy of BSS. The investment return of BSS is closely related to the operation strategy and schedule for daily swapping service.…”

Section: Introductionmentioning

confidence: 99%

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Configuration and operation combined optimization for EV battery swapping station considering PV consumption bundling

Cheng

Zhang

2017

Prot Control Mod Power Syst

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Integration of electric vehicles (EVs), demand response and renewable energy will bring multiple opportunities for low carbon power system. A promising integration will be EV battery swapping station (BSS) bundled with PV (photovoltaic) power. Optimizing the configuration and operation of BSS is the key problem to maximize benefit of this integration. The main objective of this paper is to solve infrastructure configuration of BSS. The principle challenge of such an objective is to enhance the swapping ability and save corresponding investment and operation cost under uncertainties of PV generation and swapping demand. Consequently this paper mainly concentrates on combining operation optimization with optimal investment strategies for BSS considering multiscenarios PV power generation and swapping demand. A stochastic programming model is developed by using state flow method to express different states of batteries and its objective is to maximize the station's net profit. The model is formulated as a mixed-integer linear program to guarantee the efficiency and stability of the optimization. Case studies validate the effectiveness of the proposed approach and demonstrate that ignoring the uncertainties of PV generation and swapping demand may lead to an inappropriate batteries, chargers and swapping robots configuration for BSS.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Configuration and operation combined optimization for EV battery swapping station considering PV consumption bundling

Cheng

Zhang

2017

Prot Control Mod Power Syst

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“…Charging model of double objective optimization considering load shifting to minimizing the charging cost and reducing the load fluctuation was presented in [11] and the simulation results show that 30% of the optimized charging cost can be saved with the sharpening peak effect. To determine the capacity of BSS with consideration of the efficiency of photovoltaic (PV) energy, multi-objective model of PV-based BSS towards benefits of economy and environment was provided in [12]. EV users' swapping behaviors were studied in [13] to determine the swapping load impacts on the power grid side and generation side.…”

Section: Introductionmentioning

confidence: 99%

A New Method to Plan the Capacity and Location of Battery Swapping Station for Electric Vehicle Considering Demand Side Management

Liu

Niu

et al. 2016

Sustainability

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Compared to electric vehicle (EV) charging mode, battery swapping mode can realize concentrated and orderly charging. Therefore battery swapping stations (BSS) can participate in the demand side management (DSM) as an integrated form. In this context, a new method to plan the capacity and location of BSS for EV, considering DSM, is proposed in this paper. Firstly, based on the original charging power of BSS with the rule of "First-In First-Out", a bi-level optimal configuration model of BSS, in which net profit of BSS is maximized in the upper model and operating cost of Distribution Company is minimized in the lower model, is developed to decide the rated power, number of batteries, contract pricing and dispatched power of BSS for DSM. Then, the optimal locating model of BSS with the objective of minimizing network loss is built. A mesh adaptive direct search algorithm with YALMIP toolbox is applied to optimize the bi-level model. Simulation calculation was carried on IEEE-33 nodes distribution system and the results show that participating in DSM can improve the economic benefits of both BSS and distribution network and promote the consumption of distributed generation, verifying the feasibility and effectiveness of the proposed method.

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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

Self Cite

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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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Multi-objective optimization for component capacity of the photovoltaic-based battery switch stations: Towards benefits of economy and environment

Cited by 54 publications

References 22 publications

Configuration and operation combined optimization for EV battery swapping station considering PV consumption bundling

Configuration and operation combined optimization for EV battery swapping station considering PV consumption bundling

A New Method to Plan the Capacity and Location of Battery Swapping Station for Electric Vehicle Considering Demand Side Management

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

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