The system-level consideration of intermittent renewable energy sources (RES) and small-scale energy storage in power systems remains a challenge as either type is incompatible with traditional operation concepts. Noncontrollability and energy constraints are still considered contingent cases in market-based operation. The design of operation strategies for up to 100% RES power systems requires an explicit consideration of nondispatchable generation and storage capacities, as well as the evaluation of operational performance in terms of energy efficiency, reliability, environmental impact, and cost. By abstracting from technology-dependent and physical unit properties, the power nodes modeling framework presented here allows the representation of a technologically diverse unit portfolio with a unified approach, while establishing the feasibility of energy-storage consideration in power system operation. After introducing the modeling approach, a case study is presented for illustration.

The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions.

A novel concept for system-level consideration of energy storage in power grids with dispatchable and non-dispatchable generators and loads is presented. Grid-relevant aspects such as power ratings, ramp-rate constraints, efficiencies, and storage capacities of the interconnected units are modeled, while technology-dependent and physical unit properties are abstracted from. This allows the modeling of a technologically diverse unit portfolio with a unified approach. The concept can be used for designing operation strategies for power systems, especially in the presence of non-dispatchable generation and significant storage capacities, as well as for the evaluation of operational performance in terms of energy efficiency, reliability, environmental impact, and cost. After introducing the modeling approach and a taxonomy of unit types, a simulation example is presented for illustration.

It is well understood that the electric vehicle as a distributed energy resource can provide valuable services to the power system. Such services, however, would have to co-exist with hard constraints imposed by EV user demands and distribution grid operation constraints. This paper aims to address the interactions between the stakeholders involved, mainly considering the distribution grid congestion problem, and conceptualize several approaches by which their diverse, potentially conflicting, objectives can be coordinated. A key aspect to be considered is the relationship between the operational planning and the handling of real-time events for reliable grid operation. This paper presents an analysis of key stakeholders in terms of their objectives and key operations. Three potential strategies for congestion management are presented and evaluated based on their complexity of implementation, the value and benefits they can offer as well as possible drawbacks and risks.