Optimizing Smart Grid Flexibility and Resilience with Demand Response, Renewable Integration and Energy Storage

Abstract

Traditional power networks' reliability and adaptability are facing serious problems as a result of the growing use of renewable energy sources and the electrification of heating system. This thesis examines how integrating photovoltaic (PV) system, battery energy storage system (BESS) and demand response (DR) technique might improve the flexibility and resilience of smart grid. Two sample Finnish distribution networks, 02_Porkholm (rural) and 03_Centrum (semi urban), are the subject of this study which is carried out under the EU funded PEAK project in cooperation with the University of Vaasa and Esse Elektro-Kraft Ab. Using hourly smart meter data, a Python based modelling and simulation framework has been developed to determine hosting capacity, optimize PV and BESS installation and size and analyze the possibility of demand response technique. Analysis of hosting capacity showed that feeder length, voltage drop and load pattern, all had an impact on the significant regional variance in PV integration potential. Peak shaving and grid dependability were all significantly improved by BESS deployment particularly when it was placed strategically close to nodes that were high voltage sensitive and had high demand. To assess the flexibility potential of residential and commercial consumers, heating optimisation, heating level DR and appliance level DR modelling were carried out on the demand side. The results showed that load shifting algorithm, smart thermostat and TOU pricing signal might lower peak loads by as much as 20% especially during the winter heating season. Smart control solutions that match energy usage with PV generation and dynamic tariff were shown to be essential for attaining demand side flexibility in heating system. The research provides a thorough, data driven methodology for improving smart grid efficiency via flexible demand management and DER integration. The technique and insight are flexible and scalable. This provides distribution system operators with useful tools to accelerate the shift to low carbon, resilient and decentralised energy system.