Future Grid Business Model Innovation: Distributed Energy Resources Services Platform for Renewable Energy Integration

• Published in: 2015 Asia-Pacific Conference on Computer Aided System Engineering pp. 72 - 77
• Main Authors: Sandoval, Marcelo, Grijalva, Santiago
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2015
• Subjects: Business; Density estimation robust algorithm; distributed energy resources; Economics; Energy resources; Load modeling; Mathematical model; power system economics; power system operation; Renewable energy sources
• DOI: 10.1109/APCASE.2015.20

This paper proposes a Distributed Energy Resources Services Platform as an electric grid Business Model Innovation Framework (BMIF) for coordination of distributed energy resources and renewable energy integration. The platform is based on a decentralized and layered architecture and is centered on the concept of electricity prosumers -economically motivated agents (residential, commercial, industrial) - that can produce, store or consume energy. The platform consists of six layers, including: the physical layer, local control layer, cyber layer, system control layer (economic dispatch and real-time control), market transactive layer and business layer. The main objective of the platform is to provide a framework for the coordination of several spatially distributed and heterogeneous subsystems containing energy resources at different time scales and horizons in order to conduct economic emissions dispatch and reserve scheduling to integrate higher amounts of renewable energy, while dynamically maintaining and adapting to user level of service requirements and system level constraints. Using the structure provided by the platform, the benefits of flexible distributed energy resources for different scenarios of renewable energy integration are quantified. The results show that using the platform for coordination of flexible energy, offers the opportunity to integrate higher amounts of renewable energy, reduce carbon emissions and operational costs.