This article focuses on the distributed battery energy storage systems (BESSs) and the power dispatch between the generators and distributed BESSs to supply electricity and reduce electrical supply costs. The cost analysis of electrical supply from the generators and BESSs is proposed. Then, this article introduces a consensus control algorithm
Propose a charging and discharging strategy along with two price-based and voltage-based load management programs to manage the penetration of electric vehicles for economic and technical purposes.
In an uncoordinated or uncontrolled charging–discharging (CD) strategy, the CD profiles of electric vehicles are random. Research reveals that with uncontrolled CD scheduling overall impact (grid stability, charging cost, GHG emissions—in case of plug-in hybrid EV (PHEV), etc.) of EVs reduces by only 10% as compared to 40% reduction with the controlled CD
To address the challenge of optimizing the real-time scheduling for electric vehicles on a large scale, a day-ahead–intraday multi-timescale electric vehicle cluster division strategy is proposed based on the different expected charging completion times of the accessed electric vehicles. In the pre-day phase, historical travel statistics are used to model and
The integration of charging stations (CSs) serving the rising numbers of EVs into the electric network is an open problem. The rising and uncoordinated electric load because of EV charging (EVC) exacts considerable challenges to the reliable functioning of the electrical network [22].Presently, there is an increasing demand for electric vehicles, which has resulted in
In this paper, a two-stage optimization strategy for electric vehicle charging and discharging that considers elasticity demand response based on particle swarm optimization was proposed, allowing the user to respond autonomously according to the reference value of the charge and discharge demand response and select the optimization weight
The simulation results demonstrate that our proposed optimization scheduling strategy for energy storage Charging piles significantly reduces the peak-to-valley ratio of
In this paper, the EVVES optimization charging and discharging strategy is simulated for comparison under three types of scenarios, such as comparisons with irregular charging, real energy storage, and single objectives.
It assumes that 96 points of actual data are known to solve the energy storage charging and discharging strategy in method 2, which is an ideal situation. There, "actual data + 15% normal distribution deviation data"is used in method 3 to solve the energy storage charging and discharging strategy in the current period. It takes into account
In this article, we propose an approach utilizing metaheuristic algorithms to schedule the charging and discharging activities of EVs while parking, leveraging V2G technology with the goal of reducing the daily costs of EV users and addressing energy demand management challenges in smart grids.
With the rapid development of electric vehicles (EVs) and charging facilities, EV charging guidance is currently mainly based on charging incentives. Without an in-depth exploration of the superimposed benefits to charging guidance caused by discharging incentives, it is difficult to maximize the benefits of charging station operators and to stimulate the
In response to the growing demand for fast-charging electric vehicles (EVs), this study presents a novel hybrid multimodule DC–DC converter based on the dual-active bridge
The two algorithms can be applied to determine the energy storage control strategy and optimize the output of the optical energy storage system; however, both algorithms have advantages and shortcomings. The calculation results indicate that the simple charging and discharging modes of low-cost charging and high-cost discharging cannot quickly
In this paper, we provide a comprehensive overview of BESS operation, optimization, and modeling in different applications, and how mathematical and artificial intelligence (AI)-based optimization techniques contribute to
In response to the growing demand for fast-charging electric vehicles (EVs), this study presents a novel hybrid multimodule DC–DC converter based on the dual-active bridge (DAB) topology. The Journal of Logistics, Informatics and Service
Ahn et al. [35] proposed a CC-CV charging strategy that dynamically adjusts based on changes in the battery''s internal resistance, which in turn varies depending on the SOC and the charging rate. This strategy aims to optimize the charging process for batteries, ensuring both efficiency and safety. In the CV stage, as battery capacity increases
In this paper, we provide a comprehensive overview of BESS operation, optimization, and modeling in different applications, and how mathematical and artificial
In this paper, the EVVES optimization charging and discharging strategy is simulated for comparison under three types of scenarios, such as comparisons with irregular charging, real energy storage, and single objectives.
Battery energy storage systems (BESS) are essential in managing and optimizing renewable energy utilization and guarantee a steady and reliable power supply by
In this article, we propose an approach utilizing metaheuristic algorithms to schedule the charging and discharging activities of EVs while parking, leveraging V2G
Fully consider the energy generation structure of renewable energy and non-renewable energy, EV can participate in the optimal dispatch of the grid, reduce the load pressure, and the safety indicators of stable operation of the grid, this paper formulates four indicators for operating costs, pollution emissions, grid operation optimize and user charging
Battery energy storage systems (BESS) are essential in managing and optimizing renewable energy utilization and guarantee a steady and reliable power supply by accruing surplus energy throughout high generation and discharging it during demand. It diminishes power variations and keeps grid stability while plummeting the necessity for costly
The two algorithms can be applied to determine the energy storage control strategy and optimize the output of the optical energy storage system; however, both algorithms have advantages and shortcomings. The calculation results
Propose a charging and discharging strategy along with two price-based and voltage-based load management programs to manage the penetration of electric vehicles for economic and technical purposes.
Battery energy storage technology is an important part of the industrial parks to ensure the stable power supply, and its rough charging and discharging mode is difficult to meet the application requirements of energy saving, emission reduction, cost reduction, and efficiency increase. As a classic method of deep reinforcement learning, the deep Q-network is widely
Against the background of carbon neutrality, the power dispatching operation mode has undergone great changes. It not only gradually realizes the coordinated control of source–grid–load–storage, but also strives
This article focuses on the distributed battery energy storage systems (BESSs) and the power dispatch between the generators and distributed BESSs to supply electricity and reduce
Optimal sizing and energy management strategy of a grid-connected EV workplace charging stations considering PV sources and flywheel energy storage system (FESS). Specifically, PV installed power and the charging and discharging rate of flywheel in addition to its energy capacity are optimized. Moreover, two metrics are used to estimate the
The simulation results demonstrate that our proposed optimization scheduling strategy for energy storage Charging piles significantly reduces the peak-to-valley ratio of typical daily loads, substantially lowers user charging costs, and maximizes Charging pile revenue. It achieves the dual purpose of mitigating fluctuations in the power system
Based on the flat power load curve in residential areas, the storage charging and discharging plan of energy storage charging piles is solved through the Harris hawk optimization algorithm based on multi-strategy improvement.
a. Based on the charging parameters provided above and guided by time-of-use electricity pricing, the optimization scheduling system for energy storage charging piles calculated the typical daily load curve changes for a certain neighborhood after applying the ordered charging and discharging optimization scheduling method proposed in this study.
Optimal strategy for charging and discharging 4.1. Objective function Battery degradation will occur as a result of cycle charging-discharging , so the costs caused by battery degradation should be taken into account.
During peak time periods, when the remaining capacity of the energy storage system is greater than the set value, its discharging power is the energy storage discharging power. Conversely, the discharging power of the charging pile is supplied by the grid power.
Combining Figs. 10 and 11, it can be observed that, based on the cooperative effect of energy storage, in order to further reduce the discharge load of charging piles during peak hours, the optimized scheduling scheme transfers most of the controllable discharge load to the early morning period, thereby further reducing users' charging costs.
The results show that the optimized scheme can reduce the charging cost by 40%∼110%, and the load variance of the distribution network can be reduced by 19%∼100%, realizing the "win-win" benefit of the grid side and the user side.
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