94591 20210902121741.0 doi 10.3390/en13112900 sideral 118652 ART-2020-118652 eng Naval, Natalia (orcid)0000-0002-1968-6300 Water-energy management for demand charges and energy cost optimization of a pumping stations system under a renewable virtual power plant model 2020 Access copy available to the general public Unrestricted The effects of climate change seriously affect agriculture at different latitudes of the planet because periods of drought are intensifying and the availability of water for agricultural irrigation is reducing. In addition, the energy cost associated with pumping water has increased notably in recent years due to, among other reasons, the maximum demand charges that are applied annually according to the contracted demand in each facility. Therefore, very efficient management of both water resources and energy resources is required. This article proposes the integration of water-energy management in a virtual power plant (VPP) model for the optimization of energy costs and maximum demand charges. For the development of the model, a problem related to the optimal operation of electricity generation and demand resources arises, which is formulated as a nonlinear mixed-integer programming model (MINLP). The objective is to maximize the annual operating profit of the VPP. It is worth mentioning that the model is applied to a large irrigation system using real data on consumption and power generation, exclusively renewable. In addition, different scenarios are analyzed to evaluate the variability of the operating profit of the VPP with and without intraday demand management as well as the influence of the wholesale electricity market price on the model. In view of the results obtained, the model that integrates the management of the water-energy binomial increases the self-consumption of renewable energy and saves electricity supply costs. info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.004 2020 ENERGY & FUELS 70 / 114 = 0.614 2020 Q3 T2 0.597 2020 Control and Optimization 2020 Q2 Electrical and Electronic Engineering 2020 Q2 Renewable Energy, Sustainability and the Environment 2020 Q2 Energy Engineering and Power Technology 2020 Q2 Fuel Technology 2020 Q2 Energy (miscellaneous) 2020 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Yusta, José M. Universidad de Zaragoza (orcid)0000-0003-3174-9703 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 13, 11 (2020), 2900 [21 pp.] ENERGIES Energies 1996-1073 2250248 http://zaguan.unizar.es/record/94591/files/texto_completo.pdf Versión publicada 476690 http://zaguan.unizar.es/record/94591/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:94591 articulos driver 2021-09-02-09:42:31 ARTICLE