STRATEGIES FOR RESIDENTIAL NATURAL GAS DEMAND RESPONSE
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STRATEGIES FOR RESIDENTIAL NATURAL GAS DEMAND RESPONSE

Abstract

Natural gas demand response (GDR) is an emerging technology that has garnered significant attention in recent years due to its potential as a tool for grid management. Despite the growing interest in GDR, a careful examination of the literature suggests that there is still much to learn about the full potential of this technology, particularly with regards to demand-side management which is the response from the customer or user side. In this thesis, we aim to address this critical research gap by proposing various actions and strategies to optimize the utilization of natural gas during Gas Demand Response events, with the goal of encouraging customers to participate in these programs.This study focuses specifically on the use of multi-source residential heating, with natural gas serving as the primary source. To calculate consumption during periods of high demand, we utilized a simulation model using Open Studio and Energy Plus software, which is funded by the Department of Energy and managed by the National Renewable Energy Laboratory. The simulation model enabled the determination of the heating energy requirements for a typical residential apartment over the course of an entire year, with the ability to break down the demand for each hour based on location and weather conditions. The generated energy requirement was utilized by an optimization tool to decide which source of energy the customer should use based on different incentive and pricing programs. Both the model and the optimization tools allowed us to test different possible solutions and modifications to quantify the energy savings, particularly during Gas Demand Response events. Through this research, we seek to contribute to the growing body of literature on GDR and advance the understanding of demand response from the demand side. By proposing various strategies to optimize natural gas utilization during Gas Demand Response events, we hope to encourage greater participation in demand response programs and promote the adoption of GDR as a reliable and sustainable solution to grid management challenges. The simulation model represents a valuable tool for testing proposed solutions and modifications, and our findings can inform the development of effective demand response strategies that enhance the overall potential of GDR as a tool for grid management.

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