Efficient Model for Accurate Assessment of Frequency Support by Large Populations of Plug-in Electric Vehicles

In recent years, plug-in electric vehicles (PEVs) have gained immense popularity and are on a trajectory of constant growth. As a result, power systems are confronted with new issues and challenges, threatening their safety and reliability. PEVs are currently treated as simple loads due to their low penetration. However, as their numbers are growing, PEVs could potentially be exploited as distributed energy storage devices providing ancillary services to the network. Batteries used in PEVs are developed to deliver instantaneously active power, making them an excellent solution for system frequency support. This paper proposes a detailed dynamic model that is able to simulate frequency support capability from a large number of PEVs, using an innovative aggregate battery model that takes into account the most significant constraints at PEV and aggregate battery levels. The cost optimization algorithm, which is the most time-consuming process of the problem, is executed only at the aggregate battery level, thereby reducing the computational requirements of the model without compromising the obtained accuracy. The proposed method is applied to the power system of Crete exploiting detailed statistical data of EV mobility. It is proven that PEVs can effectively support power system frequency fluctuations without any significant deviation from their optimal operation.

Strategies for Controlling Microgrid Networks with Energy Storage Systems: A Review

Distributed Energy Storage Systems are considered key enablers in the transition from the traditional centralized power system to a smarter, autonomous, and decentralized system operating mostly on renewable energy. The control of distributed energy storage involves the coordinated management of many smaller energy storages, typically embedded within microgrids. As such, there has been much recent interest related to controlling aspects of supporting power-sharing balance and sustainability, increasing system resilience and reliability, and balancing distributed state of charge. This paper presents a comprehensive review of decentralized, centralized, multiagent, and intelligent control strategies that have been proposed to control and manage distributed energy storage. It also highlights the potential range of services that can be provided by these storages, their control complications, and proposed solutions. Specific focus on control strategies based upon multiagent communication and reinforcement learning is a main objective of this paper, reflecting recent advancements in digitalization and AI. The paper concludes with a summary of emerging areas and presents a summary of promising future directions.

Orderly grid-connected cooperative scheduling control strategy based on distributed energy storage for electric vehicles

Aiming at the problem that large-scale disorderly grid connection of electric vehicles negatively affects grid operation and causes a large amount of abandoned wind and abandoned light, an orderly grid connection cooperative scheduling control strategy based on distributed energy storage of electric vehicles is proposed. The strategy takes the charging and discharging price as the lever to guide the users to charge and discharge in an orderly manner, takes the optimal economics on the user side and the optimal cost of power generation on the grid side as the objective function, and uses linear weighting normalization to convert the multi-objective function into a single objective function for simulation solution. The simulation results show that the effect of peak shaving and valley filling can be achieved on the basis of satisfying users’ demand, and renewable energy can be effectively consumed.

Investigation of behavior of BESS with PV using MATLAB/Simulink

As renewable energy penetration rises, integrating it will become a major issue that will necessitate new generating support infrastructure; an energy storage system is one answer to this problem. Battery technologies, in particular, have a wide range of energy and power output capabilities, making them perfect for integration. In many regions where renewable energy generation systems will be implemented, distributed energy storage on distribution grids may be required. When the sun is not shining or the weather is cloudy, an energy storage system is required for solar photovoltaic systems. For PV applications, a battery is used as an energy storage system. Keywords: Energy storage system, Battery, Simulink and modelling.