An increasing interest is emerging on the development of smart grid cyber-physical system testbeds. As new communication and information technologies emerge, innovative cyber-physical system testbeds need to leverage realistic and scalable platforms. Indeed, the interdisciplinary structure of the smart grid concept compels heterogeneous testbeds with different capabilities. There is a significant need to evaluate new concepts and vulnerabilities as opposed to counting on solely simulation studies especially using hardware-in-the-loop test platforms. In this paper, we present a comprehensive survey on cyber-physical smart grid testbeds aiming to provide a taxonomy and insightful guidelines for the development as well as to identify the key features and design decisions while developing future smart grid testbeds. First, this survey provides a four step taxonomy based on smart grid domains, research goals, test platforms, and communication infrastructure. Then, we introduce an overview with a detailed discussion and an evaluation on existing testbeds from the literature. Finally, we conclude this paper with a look on future trends and developments in cyber-physical smart grid testbed research.

Energy storage systems provide viable solutions for improving efficiency and power quality as well as reliability issues in dc/ac power systems including power grid with considerable penetrations of renewable energy. The storage systems are also essential for aircraft powertrains, shipboard power systems, electric vehicles, and hybrid electric vehicles to meet the peak load economically and improve the system's reliability and efficiency. Significant development and research efforts have recently been made in high-power storage technologies such as supercapacitors, superconducting magnetic energy storage (SMES), and flywheels. These devices have a very high-power density and fast response time and are suitable for applications with rapid charge and discharge requirements. In this paper, the latest technological developments of these devices as well as advancements in the lithium-ion battery, the most power dense commercially available battery, are presented. Also, a comparative analysis of these high-power storage technologies in terms of power, energy, cost, life, and performance is carried out. This paper also presents the applications, advantages, and limitations of these technologies in a power grid and transportation system as well as critical and pulse loads.

In this paper, a real-time energy management algorithm (RTEMA) for a grid-connected charging park in an industrial/commercial workplace is developed. The charging park under study involves plug-in hybrid electric vehicles (PHEVs) with different sizes and battery ratings as well as a photovoltaic (PV) system. Statistical and forecasting models were developed as components in the developed RTEMA to model the various uncertainties involved such as the PV power, the PHEVs, arrival time, and the energy available in their batteries upon their arrival. The developed energy management algorithm aims at reducing the overall daily cost of charging the PHEVs, mitigating the impact of the charging park on the main grid, and contributing to shaving the peak of the load curve. Hence, the benefits of implementing this RTEMA is shared among the customers, the charging park considering all customers as a bulk of power connected to the grid, and the ac grid. This makes it applicable for various business models. The developed RTEMA utilizes a fuzzy controller to manage the random energy available in the PHEVs' batteries arriving at the charging park and their charging/discharging times, power sharing among individual PHEVs that is commonly known as vehicle-to-vehicle functionality, and vehicle-to-grid service between the charging park and the main ac grid. The developed RTEMA was simulated using the standard IEEE 69-bus system at different penetration and distribution levels. The obtained results verify the effectiveness and validity of the developed RTEMA.

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies.

The increased rate of cyber-attacks on the power system necessitates the need for innovative solutions to ensure its resiliency. This work builds on the advancement in the IoT to provide a practical framework that is able to respond to multiple attacks on a network of interconnected microgrids. This paper provides an IoT-based digital twin (DT) of the cyber-physical system that interacts with the control system to ensure its proper operation. The IoT cloud provision of the energy cyber-physical and the DT are mathematically formulated. Unlike other cybersecurity frameworks in the literature, the proposed one can mitigate an individual as well as coordinated attacks. The framework is tested on a distributed control system and the security measures are implemented using cloud computing. The physical controllers are implemented using single-board computers. The practical results show that the proposed DT is able to mitigate the coordinated false data injection and the denial of service cyber-attacks.