Browsing by Keyword "demand response"
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Item HOLISDER Project: Introducing Residential and Tertiary Energy Consumers as Active Players in Energy Markets(2021-01-25) Romero-Amorrortu, Ander; Agustín-Camacho, Pablo de; Eguiarte, Olaia; Huitema, George B.; Morcillo, Laura; Vukovic, Milan; Tecnalia Research & InnovationAlthough it has been demonstrated that demand-side flexibility is possible, business application of residential and small tertiary demand response programs has been slow to develop. This paper presents a holistic demand response optimization framework that enables significant energy costs reduction for consumers. Moreover, buildings are introduced as main contributors to balance energy networks. The solution basis consists of a modular interoperability and data management framework that enables open standards-based communication along the demand response value chain. The solution is being validated in four large-scale pilot sites, which have diverse building types, energy systems and energy carriers. Furthermore, they offer diverse climatic conditions, and demographic and cultural characteristics to establish representative results.Item Residential load forecasting under a demand response program based on economic incentives(2015-08-01) Ruiz, Nerea; Claessens, Bert; Jimeno, Joseba; Lopez, Jose Antonio; Six, Daan; POWER SYSTEMSThis paper describes a tool for an Aggregator to forecast the aggregated load demand response of a group of domestic customers subscribed to an indirect load control program based on price/volume signals. The tool employs a bottom-up approach based on physical end-use load models where the individual responses of a random sample of customers are combined in order to build the aggregated load demand response model. Simulation of the individual responses is carried out with an optimization algorithm based on mixed integer linear programming that minimizes the electricity bill whilst maintaining consumer's comfort level. To improve the performance of the model, a genetic algorithm for fitting the input parameters according to measured data is also provided. The tool is intended to allow the Aggregator rehearsing the impact of different control strategies and therefore choosing the most appropriate ones for market participation and portfolio optimization. To exemplify the methodological applicability of the developed algorithm, a case study based on an actual power system in eastern Spain is considered.