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In this paper a novel generalised modelling framework for multi-energy systems containing storage elements is combined with a multi-objective model predictive control. The control objective is to both minimise the economic cost of importing energy into the system as well as providing the service of smoothing the profile of the electrical energy imported thus levelling the load and reducing peak demand. The capabilities of the approach are demonstrated by its application to a representative case study based on two buildings at the University of Manchester. Results show that model predictive control is capable of simultaneously addressing minimisation of economic cost as well as smoothing the electrical energy import.

Abstract Thermal energy storage (TES) systems are growing to a relevant role in solar cooling applications. Hence, high energy density is a desirable property of the TES system. Phase change materials (PCM) helps to increase this characteristic. A high temperature pilot plant able to test different types of TES systems and materials was designed and built at the University of Lleida (Spain). This pilot plant is composed mainly of three parts: heating system, cooling system, and different storage tanks. Two identical storage tanks based on the shell-and-tubes heat exchanger, one of them including 196 squared fins in the bundle of the tubes and the other without, were experimentally tested. Hydroquinone was selected as the storage material, having a latent heat of 205 kJ/kg and a phase change temperature between 168 and 173 °C. The aim of this paper is to test experimentally, and compare the average effectiveness of the TES systems analyzed using PCM for solar cooling and refrigeration applications. It was found out that for the same tank configurations (shell-and-tubes) even changing drastically the dimensions of the tank or the number and the diameter of the tubes, the average effectiveness curve proposed in the literature fits well with the results showed here.

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The building and construction sector is a large contributor to anthropogenic greenhouse gas emissions and consumes vast natural resources. Improvements in this sector are of fundamental importance for national and global targets to combat climate change. In this context, vertical greenery systems (VGS) in buildings have become popular in urban areas to restore green space in cities and be an adaptation strategy for challenges such as climate change. However, only a small amount of knowledge is available on the different VGS environmental impacts. This paper discusses a comparative life cycle assessment (LCA) between a building with green walls, a building with green facades and a reference building without any greenery system in the continental Mediterranean climate. This life cycle assessment is carried according to ISO 14040/44 using ReCiPe and GWP indicators. Moreover, this study fills this gap by thoroughly tracking and quantifying all impacts in all phases of the building life cycle related to the manufacturing and construction stage, maintenance, use stage (operational energy use experimentally tested), and final disposal. The adopted functional unit is the square meter of the facade. Results showed that the operational stage had the highest impact contributing by up to 90% of the total environmental impacts during its 50 years life cycle. Moreover, when considering VGS, there is an annual reduction of about 1% in the environmental burdens. However, in summer, the reduction is almost 50%. Finally, if the use stage is excluded, the manufacturing and the maintenance stage are the most significant contributors, especially in the green wall system.

Abstract In this paper, a medium-term load forecasting model is proposed, intended to be used for the extrapolation of loads containing a small proportion of air conditioners. The main feature of the proposed model is the decomposition of weekly load observations into two independent components: trend line and seasonal variations. The trend line is described by the combination of the polynomial regression and the first-order autoregressive model. The parameters of this model are estimated with the aid of the generalized least-squares method. The seasonal component is modeled via a discrete model, where the weather sensitive cycle is separated from the weather insensitive one. A linear regression model is further proposed in order to associate weather sensitive variations with the exogenous weather variable (temperature). This procedure enabled a simple and efficient convolution of all load components into a single forecasting model. The whole methodology is verified on a real-life example of the peak-load consumption within the power system of former Yugoslavia.

Artículos en revistas In this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented. info:eu-repo/semantics/publishedVersion

Artículos en revistas Liberalization policies, the challenges of integrating distributed generation resources, and the recent flattening of electricity demand due to the economic crisis and technological change have led to lower returns for European electricity suppliers. Innovative and sustainable business models are needed to serve electricity customers while reflecting the operational needs of the system and maintaining supplier financial viability. This paper describes a novel model of Integrated Energy Services that encompasses distributed generation (DG) and demand response (DR) resources for industrial customers. We further reflect on some of the market opportunities and regulatory drivers for the development of similar schemes across Europe. info:eu-repo/semantics/publishedVersion

The development of heat transfer fluids (HTF) and heat storage materials (HSM) is crucial to design concentrating solar plant (CSP). Binary alkaline nitrate mixtures are currently used as sensible thermal energy storage materials. However, multi-component nitrate/nitrite systems were proposed as possible better candidates. In particular, ternaries mixtures containing sodium, potassium, and calcium are extremely promising as thermal fluids, given their reduced toxicity and greater cost-effectiveness. Nevertheless, very few data are present in the scientific literature regarding the correspondent phase diagram, and only the properties of specific compositions are reported. For this reason, a regular solution model was developed and employed in this work, and validated by comparing the simulation results with experimentally obtained phase change values. In particular, given that the common calorimetric techniques are impracticable for detecting the transition temperatures of calcium containing nitrate mixtur...