Examinando por Autor "Cruz-de-la-Torre, Carlos"
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Ítem Dealing with contradictory objectives in energy communities: A game-oriented trilevel approach(Elsevier, 2025-09) Tostado-Véliz, Marcos; Hasanien, Hany M.; Cruz-de-la-Torre, Carlos; Jurado-Melguizo, FranciscoEnergy communities empower end users to partake actively in the operation of the system while lowering energy procurement through optimal sharing resources. The main objective of energy communities is reducing the collective bill by maximizing the usage of local assets such as photovoltaic and storage systems. However, the different community members may raise particular objectives that may eventually lie in contradiction with the reduction of the electricity cost. For example, prosumers may be interested in incrementing their consumption above a benchmark point in order to increase their comfort and satisfaction. Such contradictory objectives should be considered in energy management of communities in order to ensure its social stability and successful. To this end, a novel game-based trilevel day-ahead approach for cooperative communities is developed, in which two secondary objectives can be accommodated together with the cost minimization original target. As a sake of example, the developed tool tailors in this paper to the case in which prosumers aim at maximizing their consumption while storage pretend to minimize the degradation of assets. The original trilevel structure is reduced to a solvable single-level problem that provide an equilibrium point in the Nash sense. A number of results is provided in 5 and 15-bus cases in order to validate the new approach. Results show that the new proposal can be easily implemented in a variety of scenarios, showing a case-independent performance. The hierarchical decision-logic procedure has been illustrated and validated analysing the total community cost under different users’ preferences. Finally, it is shown that the developed methodology scales well with the storage capability and community size.Ítem Pattern-driven behaviour for demand-side management: An analysis of appliance use(Elsevier, 2024-04-01) Cruz-de-la-Torre, Carlos; Tostado-Véliz, Marcos; Palomar, Esther; Bravo, IgnacioEnergy communities play a key role in the transition to sustainable energy, helping to inform and engage end-users so that they can become active energy consumers. In practice, trials and pilots often risk failure due to misplaced expectations and unforeseen behaviours when it comes to achieving flexible energy demand resources. In order to tackle these challenges, residential electricity load profile datasets and consumer survey results emerge as powerful tools for identifying controllable loads, energy consumption models, and tailored understanding of communities' energy contexts. This paper first outlines and analyses these datasets' capabilities to leverage data-driven decision-making for more efficient deployments of demand-side management (DSM) systems. A number of appliance behaviour patterns are extracted, based on high and flexible loads for shifting, being validated over three different use cases to support turn-key DSM in the presence and absence of renewable supply and bill saving. A genetic algorithm optimization is applied to underpin flexible demand reallocation and optimal community load profiles by combining time-variable tariff of use. Experiments demonstrate that controllable and shiftable appliances can reduce average peak load by up to 29% by increasing renewable self-consumption, leading to a valuable energy bill saving of 9%. Our findings also point to the current limitations of existing load/consumption datasets, which are hindering more efficient DSM design of flexibility and demand response programmes in energy communities.