Robust optimization model for energy market operation considering distributed energy resources and prosumer technology

The future electric power grid would be characterized by power volatility, created by intermittent distributed energy resources (DERs) such as solar photovoltaics, and prosumer technology. Moreover, increase in penetration of flexible loads is also a matter of concern of energy grid operators. Furth...

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Bibliographic Details
Main Author: Ling, Yunxiao
Other Authors: Gooi Hoay Beng
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166022
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Institution: Nanyang Technological University
Language: English
Description
Summary:The future electric power grid would be characterized by power volatility, created by intermittent distributed energy resources (DERs) such as solar photovoltaics, and prosumer technology. Moreover, increase in penetration of flexible loads is also a matter of concern of energy grid operators. Further, the prosumer technology can also influence the energy market operation. Consequently, the smart grid's operation and control would be more challenging under dynamically changing scenarios without re-thinking the system optimization and economic viability. Hence, there is a need to develop the robust optimization strategy that can provide a fast response in real-time operation as well. This project aims to develop the robust optimization models for centralized and decentralized energy market operations by considering participation of DER aggregators, virtual power plants (VPPs) and prosumers. The optimization sub-module optimizes the market operation via realistic distributed energy resources such as battery energy storage systems (BESSs); coordinates the BESSs; manages their state-of-charge values; and operates DERs. In other words, it optimizes the operation of energy providers. The proposed model has been realized through co-simulations using the open-source power network simulator such as Pyomo and robust optimization tools interfaced with Python.