The electric power system is currently undergoing a major transition due to growing numbers of distributed energy resources (DERs) and increased distribution automation. If optimally managed and operated, DERs could… Click to show full abstract
The electric power system is currently undergoing a major transition due to growing numbers of distributed energy resources (DERs) and increased distribution automation. If optimally managed and operated, DERs could provide flexibility and highly valuable grid services such as restoration, peak shaving, voltage regulation, and frequency support to maintain grid reliability. Different applications and enterprises, such as distributed energy resources management systems (DERMS), are being developed for coordinated and optimal operation of DERs. However, to attract sufficient DER participation and achieve the coordinated operation of DERs, systems and components must be interoperable and information exchange must be secure. Along this line, the Portland State University power engineering group is developing Energy Grid of Things (EGoT) DERMS prototype. The proposed application requires the coordinated dispatch of large numbers of DERs and testing such a system presents a challenge; it is not practical to test system prototypes using thousands of real DERs. Hence, the modeling environment (ME) is designed as a co-simulation tool to model interactions between a DERMS and a mass of simulated DERs. The ME is expected to address the scalability issue inherent to hardware-in-the-loop DERMS simulation; many assets are needed to observe effects on the grid from deployment and dispatch of DERs. To enable the development and testing of such advanced applications for power distribution system planning and operations, the U.S Department of Energy developed GridAPPS-Dâ„¢, an open-source, standards-based platform at Pacific Northwest National Laboratory. This paper introduces the proposed ME for testing a DERMS application. The architecture of the ME is presented, and the GridAPPS-D features for a such simulation environment are discussed. Additionally, the procedure for developing the ME within the GridAPPS-D platform and use of different APIs for efficient and timely integration are discussed in detail.
               
Click one of the above tabs to view related content.