| Grant number: | 22/03161-4 |
| Support Opportunities: | Research Grants - Initial Project |
| Start date: | February 01, 2023 |
| End date: | January 31, 2028 |
| Field of knowledge: | Engineering - Electrical Engineering - Power Systems |
| Principal Investigator: | John Fredy Franco Baquero |
| Grantee: | John Fredy Franco Baquero |
| Host Institution: | Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil |
| Associated researchers: | Alejandra Tabares Pozos ; Carlos Francisco Sabillón Antúnez ; João André Pinto Soares ; Lucas Teles de Faria ; Maria Nataly Banol Arias ; Rubén Augusto Romero Lázaro |
| Associated scholarship(s): | 23/16829-6 - Optimal Operation of Smart Microgrids within Local Energy Markets with Uncertainties in Distributed Renewable Resources and Demand, BP.DR |
Abstract
Distributed energy resources (DERs) such as renewable distributed generation, electric vehicles, demand response, and energy storage systems must be properly integrated into the future electrical distribution system (EDS) to bring economic and environmental benefits to society. Hence, the expansion and operational planning of EDSs should incentivize that integration, while accounting the challenge of uncertainties of DERs. Furthermore, local electricity markets (LEMs) are being developed to take advantage of DERs and facilitate the participation of all agents in the EDS. Thus, novel concepts and methods to assist the EDS planner are needed to address the challenges of integrating DERs within the context of LEMs and cope with the uncertainties inherent to those resources; this would lead to planning decisions that avoid excessive investments in network expansion, while keeping service quality for high penetration of DERs and enable the connection of microgrids, as well as the participation of prosumers, and aggregators. This research project proposes the development of a new optimization-based planning paradigm for the planning of future EDSs in the context of LEMs, in which DERs are able to make power capacity offerings and the effect of demand response programs is included. Stochastic and robust programming will be adopted to deal with the uncertainties of the parameters (electrical demand, wind and photovoltaic generation, and energy price) making it possible to find realistic solutions. The proposed paradigm will contribute to the efficient coordination of modern EDSs, allowing the integration of DERs, enabling energy alternatives and lower price options to final users, mitigation of the environmental impacts, and improvement of service quality. (AU)
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