
This dissertation addresses the need for large energy consumers with local multi-energy systems (L-MESs) to transition to renewable energy and use demand response (DR) for operational flexibility. DR, where consumers adjust energy use based on incentives, can help integrate renewables and reduce costs and emissions. However, quantifying DR’s economic and environmental potential is challenging. This research introduces tools to evaluate DR’s impacts, including the Elmada and DRAF software, and applies them to real-world case studies. Results show that flexibility reduces decarbonization costs and emissions. The thesis provides valuable methods and insights to promote non-residential DR adoption.
carbon price, decision support, industry, decarbonization, energy system optimization, carbon emission factor, sustainability, marginal emissions, merit order, distributed energy resources, energy system modeling, Engineering, Sustainability, demand response, electricity market, Physical Sciences and Mathematics, energy flexibility, demand reponse, Environmental Sciences
carbon price, decision support, industry, decarbonization, energy system optimization, carbon emission factor, sustainability, marginal emissions, merit order, distributed energy resources, energy system modeling, Engineering, Sustainability, demand response, electricity market, Physical Sciences and Mathematics, energy flexibility, demand reponse, Environmental Sciences
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