The energy hub concept and modeling methodology are widely employed tools for solving resource conversion and storage scheduling problems. For instance, industrial clusters might benefit from determining the suitable time to operate their facilities and to sell electricity to the public power grid, according to legal, economic or environmental factors. In this paper, novel elements are introduced in order to more accurately represent real plants and to reduce the amount of decision variables. The major innovation is to consider devices consuming a resource which is not related to the quantity of output produced, by attaching binary decision variables to certain energy hub outputs. Secondly, a path vector is defined to take into account the flows of resources within the system instead of employing a variable for each branch between the components. The third innovation consists of an additional vector to express the amount of output resources sold from the energy hub, including constraints for those resources which are exported and imported through the same medium. An extended energy hub model is first proposed and then applied to a real plant example, including multiple and heterogeneous resources and performing a comparison between days with different demands, weather conditions and electricity prices. The results obtained in the selected scenarios demonstrate a logical operation scheduling, and therefore validate the proposed approach.

The dispatch of energy and resources in agricultural systems often involves the definition and resolution of optimization problems. This paper presents a novel tool composed of a set of MATLAB® and Simulink® files that has been developed to ease such tasks. In contrast to other alternatives, it allows the consideration of multiple kinds of resources in the problem and the relationships between the inputs and outputs of the system; its parametrization can be defined graphically in Simulink® without requiring third party software, and the entire package is freely available on Github. The package can generate the constraints in MATLAB® code and can get the optimal dispatch schedule for the deterministic mixed-integer linear problem that represents the defined system. Its main functions and blocks as well as a case study based on a traditional Mediterranean greenhouse and a photovoltaic parking lot located in Almeria (Spain) are included to demonstrate its use and clarify how the problem is formulated. The simulation performed validates the tool as being useful for decision-making (schedule irrigation and CO2 enrichment, as well as managing storage systems) in these and similar environments. Future implementations are intended to incorporate the interconnection of agents with opposed interests and robust optimization strategies for uncertain scenarios.

In this work, the optimal management of the water grid belonging to a pilot agro-industrial district, based on greenhouse cultivation, is analyzed. Different water supply plants are considered in the district, some of them using renewable energies as power sources, i.e., a solar thermal desalination plant and a nanofiltration facility powered up by a photovoltaic field. Moreover, the trade with the water public utility network is also taken into account. As demanding agents, a greenhouse and an office building are contemplated. Due to the different water necessities, demand profiles, and the heterogeneous nature of the different plants considered as supplier agents, the management of the whole plant is not trivial. In this way, an algorithm based on the energy hubs approach, which takes into account economic terms and the optimal use of the available resources in its formulation, is proposed for the pilot district with a cropping area of 616 m2. Simulation results are provided in order to evidence the benefits of the proposed technique in two cases: Case 1 considers the flexible operation of the desalination plant, whereas in Case 2 the working conditions are forced to equal the plant’s maximum capacity (Case 2). A flexible operation results in a weekly improvement of 4.68% in profit, an optimized use of the desalination plant, and a reduction of the consumption of water from the public grid by 58.1%.

Determining the static overall efficiency of inverters is sometimes necessary for control o design purposes. As getting this information from the manufacturers’ datasheets or certified laboratories might not be always viable, this paper addresses its estimation from direct measurements under actual operating conditions. Particularly, the Sandia Inverter Model has been taken as a paradigm of methodology and adapted to deal with the available data for an office building’s photovoltaic system over the 2013- 2017 period. Two unidimensional and two bidimensional models have been selected and compared to assess their goodness of fit on three inverters of the same kind of which the system consists. The best-case scenario corresponds to an exponential curve fitting, in which the R-square value increases over 0.95, outperforming the other models.

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