ElsevierEscrivá-Escrivá, G.; Segura Heras, I.; Alcázar-Ortega, M. (2010). Application of an energy management and control system to assess the potential of different control strategies in HVAC systems. Energy and Buildings. 42(11):2258-2267. doi:10.1016/j.enbuild.2010 AbstractThe significant and continuous increment in the global electricity consumption is asking for energy saving strategies. Efficient control for heating, ventilation and air-conditioning systems (HVAC) is the most cost-effective way to minimize the use of energy in buildings. In this framework, an energy management and control system (EMCS) has been developed to schedule electricity end-uses in the campus of the Universidad Politécnica de Valencia (UPV), Spain. This paper presents an evaluation performed by using the EMCS of different control strategies for HVAC split systems. It is analyzed the effect of different schedules for a common air-conditioning device and demand response strategies are tested in several situations. The economic saving is calculated taking into account the electricity contract clauses.Finally, a test is made for the control of a group of similar devices in order to reduce the maximum peak power in consumption and to obtain a flexible load shape with the HVAC loads.The studies are then extrapolated to a larger system, the whole University campus, for which energy and economic savings are quantified.

Renewable energies are a central element in the search for energy sustainability, so they are 7 becoming a substantial component of the energy scenario of every country, both as systems 8 connected to the grid or in stand-alone applications. Feasibility of these renewable energy 9 systems could be necessary not only in their application in isolated areas, but also in systems connected to the grid, in this last case when their contribution reaches a substantial fraction of the total electricity demand. To overcome this reliability problem, hybrid renewable systems could become essential and activities to optimize their design should be addressed, both in the simulation and in the experimental areas. In this paper, a laboratory to simulate and verify the reliability of hybrid renewable systems is presented and its application to the feasibility analysis of multicomponent systems including photovoltaic panels, wind generator and biomass gasification plant, plus energy storage in a battery bank, are described.

Due to the current high energy prices it is essential to find ways to take advantage of new energy resources and enable consumers to better understand their load curve. This understanding will help improve customer flexibility and their ability to respond to price or other signals from the electricity market. In this scenario, one of the most important steps is to carry out an accurate calculation of the expected consumption curve, i.e. the baseline. Subsequently, with a proper baseline, customers can participate in demand response programs and verify performed actions. This paper presents an artificial neural network (ANN) method for short-term prediction of total power consumption in buildings with several independent processes. This problem has been widely discussed in recent literature but a new point of view is proposed. The method is based on two fundamental features: total consumption forecast based on independent processes of the considered load or end-uses; and an adequate selection of the training data set in order to simplify the ANN architecture. Validation of the method has been performed with the prediction of the whole consumption expressed as 96 active energy quarterhourly values of the Universitat Politècnica de València, a commercial customer consuming 11,500 kW.

ElsevierAlcázar Ortega, M.; Álvarez Bel, CM.; Escrivá Escrivá, G.; Domijan, A. (2012). Evaluation and assessment of demand response potential applied to the meat industry. Applied Energy. 92:84-91. doi:10.1016Energy. 92:84-91. doi:10. /j.apenergy.2011.040.-1 - EVALUATION AND ASSESSMENT OF DEMAND RESPONSE Abstract 15Demand Response has proven to be a useful mechanism that produces important benefits for 16 both the customer and the power system. In the context of an increasingly competitive electricity 17 market, where prices are constantly rising and the presence of renewable energy resources is 18 gaining prominence, this paper analyzes the flexibility potential of customers in the meat industry, 19 based on the management of the most energy consuming process in this type of segment: cooling 20 production and distribution. 21The effectiveness of the proposed actions has been successfully tested and validated in an 22 active factory that produces cured ham in Spain, where savings of about 5% in the total annual cost 23 of electricity have been assessed, together with power reductions in the range of 50% of the total 24 * Corresponding Author: Manuel Alcázar-Ortega. Institute for Energy Engineering. Universidad Politécnica de Valencia.Camino de Vera, s/n, edificio 8E, escalera F, 5ª planta. and they open the door to an innovative perspective on the evaluation of flexibility among customers 26 which are traditionally considered rigid, providing a novel approach to the management of customer 27 infrastructures in order to exploit their flexibility in electricity markets. 28 29

Elsevier Álvarez, C.; Alcázar-Ortega, M.; Escrivá-Escrivá, G.; ANTONIO GABALDON MARIN (2009) AbstractThe authors present a methodology to evaluate and quantify the economic parameters (costs and benefits) attached to customer electricity consumption by analyzing the service provided by the different "pieces" of absorbed electricity. The first step of this methodology is to perform a process oriented market segmentation to identify segments according to their flexibility potential. After that, a procedure based on comprehensive simulations to identify and quantify the actual demand that can be managed in the short term is presented and, finally, the required economic analysis is performed. The methodology, which is demonstrated with some applications to the commercial sector, not only helps the customers to integrate in flexible distribution systems but also offers the necessary economical parameters for them to integrate in electricity markets.

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The industry sector has a significant responsibility for the depletion of fossil fuels and emission of carbon dioxide. Thus, several initiatives have been implemented by the industry sector to mitigate those issues. One initiative corresponds to the implementation of energy efficiency strategies. In particular, the food industry is heavily dependent on fossil fuels, and the food demand is expected to grow significantly in the coming years. Therefore, developing energy efficiency strategies for this particular industrial sector is crucial. This paper investigates the different opportunities for energy efficiency in the food industry. It first provides a brief overview of the various food industries and related energy consumption. Then, the different options for energy efficiency in the thermal and electric sector are discussed. New trends and opportunities, arising from industry 4.0 and demand response, are also presented.INDEX TERMS Energy efficiency, food industry, industry 4.0, renewable energy, waste-to-energy.

In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.