Yang et al. constructed a multi-objective model that takes into account microgrid operation costs, environmental treatment costs, and charging and discharging costs
This paper proposes a strategy to coordinate the exchange of energy between the grid and a large charging station equipped with energy storage system and photovoltaic
Flywheel energy storage system (FESS) is an energy conversion device designed for energy transmission between mechanical energy and electrical energy. There are high
Analyze the impact of battery depth of discharge (DOD) and operating range on battery life through battery energy storage system experiments.
Optimizing the energy storage charging and discharging strategy is conducive to improving the economy of the integrated operation of photovoltaic-storage charging. The existing model
The charging/discharging station (CDS) with V2G as a transfer station for the energy interaction between EVs and MG, whose capacity planning directly affects the effect of
Section 4 discusses the effectiveness of the strategy in different energy storage system, where the capacity and maximum charging/discharging power of battery varies, in the light of
Abstract Against the backdrop of global energy transition, the research on renewable energy sources such as wind and solar in the power system is particularly crucial.
In this paper, an EV charging load model that considers multiple information was developed, and a two-stage optimization strategy for coordinated charging and discharging of
The widely used flywheel energy storage (FES) system has such advantages as high power density, no environment pollution, a long
The distributed energy storage device units (ESUs) in a DC energy storage power station (ESS) suffer the problems of overcharged and undercharged with uncertain initial
1. INTRODUCTION In the context of the rapid growth of electric vehicle ownership, integrated solar energy storage and charging power station has become a research hotspot in the field of
As large-scale renewable energy systems are integrated into the power grid, their inherent power fluctuations and adverse impacts on grid stability can be mitigated using energy storage
Formulate a reasonable and orderly charging/discharging strategy for EVs to use their idle energy to provide power for MG and reduce MG''s daily operation and
Here, a charging and discharging power scheduling algorithm solved by a chance constrained programming method was applied to an electric vehicle charging station
Charging and discharging strategy of battery energy storage in the charging station with the presence of photovoltaic [J]. Energy Storage Science and
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
Electric vehicle Coordinated charging-discharging Optimization strategy Elasticity demand response of EV a of in of EV of of of b,
To address these issues, this paper first proposes a vehicle-to-grid (V2G) optimization framework that responds to regional dynamic pricing. It
This paper proposes a method of coordinated control for multiple battery energy storage systems located at electrical vehicle charging parks in a
Optimizing the energy storage charging and discharging strategy is conducive to improving the economy of the integrated operation of photovoltaic-storage charging.
In order to improve the power system reliability and to reduce the wind power fluctuation, Yang et al. designed a fuzzy control strategy to control the energy storage charging
In this study, to investigate the energy storage characteristics of EVs, we first established a single EV virtual energy storage (EVVES) model
This paper addresses the challenge of charging and discharging scheduling for large-scale electric vehicles (EVs) in the Vehicle-to-Grid (V2G) mode by proposing a user
Their findings revealed that the rate of arrival charging/ discharging EVs, the values of cut-off, and the busy number of sockets at each public charging station significantly
The energy consumption state, charging and discharging behavior, reward function, and neural network structure are designed to meet the flexible scheduling of charging
Energy storage has become a fundamental component in renewable energy systems, especially those including batteries. However, in charging and
To reduce the charging and discharging costs of gravity energy storage systems, this paper proposes a dynamic adjustment method and an initial sequence recombination method based
Charging and discharging strategy optimization of linear machine gravity energy storage systems [J]. Energy Storage Science and Technology, 2025, 14 (9): 3476-3487.
Secondly, an optimal battery energy storage configuration model considering the impact of charging and discharging strategy on energy storage life is established to ensure the design
The strategy aims to optimize the timing of EV charging and discharging activities when vehicles are parked, to reduce daily charging costs for EV owners, and help
The widely used flywheel energy storage (FES) system has such advantages as high power density, no environment pollution, a long service life, a wide operating temperature
The model is trained by the actual historical data, and the energy storage charging and discharging strategy is optimized in real time based on the current period status. Finally, the proposed method and model are tested, and the proposed method is compared with the traditional model-driven method.
Intelligent charging–discharging refers to a system whereby a data connection is shared between an EV and a charging station, and the charging station is connected to a transmission/distribution system operator.
This paper reviews several controlled charging–discharging issues with respect to system performance, such as overloading, deteriorating power quality, and power loss. Thus, it highlights a new approach in the form of multistage hierarchical controlled charging–discharging.
The charging/discharging station (CDS) with V2G as a transfer station for the energy interaction between EVs and MG, whose capacity planning directly affects the effect of EVs participating in scheduling and MG energy storage devices' capacity elasticity. Many EVs will lead to underutilization of power resources during idle periods.
The uncertainty of photovoltaic power generation output, electric vehicle charging load, and electricity price are considered to construct the IRL model for the optimal operation of the energy storage system. A double-delay deep deterministic policy gradient algorithm are utilized to solve the system optimization operation problems.
Depending on the types of control parameters, established charging–discharging can be incorporated into indirect controlled, intelligent controlled, and bi-directional controlled. In indirect controlled approach, the design does not constrain the charging parameters such as the charger's control, loading time, and charging extent.
