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Economic evaluation model for the energy Demand Response

handle: 11386/4670294 , 11591/380801
Abstract The need for new solutions for the generation, transmission, and distribution of electricity has become apparent with advancements of technology worldwide. This disposition has been revealed by the deregulation of the electricity market, the technological processes in constant evolution, the focus on environmental problems, and the need to manage and protect energy loads that are more sensitive to disturbances in the grid. Numerous significant research and development efforts, involving a large number of technology areas and requiring a highly interdisciplinary design vision, have led to the emergence of a new concept called “Smart Grids.” In this context, attention is emphasized toward the Demand Response (DR), a particular tactic for the intelligent management of users' electrical loads. This paper aims to present an algorithm that helps the aggregator of energy loads in carrying out its daily decisions, using an economic objective function. A mathematical model for this goal was developed, and a heuristic solution was used to calculate the configuration of load distributions. Conclusively, the model was tested to understand its effectiveness and to determine the capability of an aggregator to have revenues from the application of a DR tactic.
Demand response; Economic evaluation model; Energy; Smart grid; Pollution; Energy (all), Demand response; Economic evaluation model; Energy; Smart grid; Energy (all); Pollution
Demand response; Economic evaluation model; Energy; Smart grid; Pollution; Energy (all), Demand response; Economic evaluation model; Energy; Smart grid; Energy (all); Pollution
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).39 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
