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Volatility and sharp increases in the price of electricity are serious economic problems in the primary sector because they affect modernization investments for irrigation systems in Spain. This paper presents a new virtual power plant (VPP) model that integrates all available full-scale distributed renewable generation technologies. The proposed VPP operates as a single plant in the wholesale electricity market and aims to maximize profit from its operation to meet demand. Two levels of renewable energy integration in the VPP were considered: first, a wind farm and six hydroelectric power plants that inject the generated electricity directly to the distribution network, and second, on-site photovoltaic plants associated with each of the electricity supply points in the system that are designed to prioritize self-consumption. The proposed technicaleconomic dispatch model was developed as a mixed-integer optimization problem that determines the hourly operation of distributed large-scale renewable generation plants and on-site generation plants. The model was applied to real data from an irrigation system comprising a number of water pumping stations in Aragon (Spain). The results of the VPP model demonstrate the importance of the technical and economic management of all production facilities to significantly reduce grid dependence and final electricity costs.

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.

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