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Abstract: This paper presents the calculation of the power of solar rays that pass through the window of an observed room and their impact on warming up and lighting of the room. The calculations were performed using a mathematical model that takes into account the geographical position of the object, time zone, orientation of windows, day of the year, and current time. This paper also includes the calculation of geometry of the solar radiation and its intensity, artificial light and cooling/heating demands. Based on data from above, the optimization of blind tilt angle was performed to achieve the best possible brightness of the room and energy savings when heating or cooling, depending on ambient temperature. Optimization was performed using a genetic algorithm and fuzzy logic. After an analysis of the results obtained from optimization of the blind tilt angle, an algorithm for blinds control was developed in order to achieve energy savings and comfort in the observed room. Based on the derived conclusions, an UML diagram was made that describes the algorithm for determining optimal blind tilt angle. [Copyright &y& Elsevier]

Abstract: In this paper, a methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system is presented. This approach makes use of a deterministic algorithm to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the total cost of the system is minimized while guaranteeing the availability of the energy. The collection of 6months of data of wind speed, solar radiation and ambient temperature recorded for every hour of the day were used. The mathematical modeling of the main elements of the hybrid wind/PV/diesel system is exposed showing the more relevant sizing variables. A deterministic algorithm is used to minimize the total cost of the system while guaranteeing the satisfaction of the load demand. A comparison between the total cost of the hybrid wind/PV/diesel energy system with batteries and the hybrid wind/PV/diesel energy system without batteries is presented. The reached results demonstrate the practical utility of the used sizing methodology and show the influence of the battery storage on the total cost of the hybrid system. [Copyright &y& Elsevier]

Abstract: This paper deals with the development of methods for non steady state test of solar thermal collectors. Our goal is to infer performances in steady-state conditions in terms of the efficiency curve when measures in transient conditions are the only ones available. We take into consideration the method of identification of a system in dynamic conditions by applying a Graybox Identification Model and a Dynamic Adaptative Linear Neural Network (ALNN) model. The study targets the solar collector with evacuated pipes, such as Dewar pipes. The mathematical description that supervises the functioning of the solar collector in transient conditions is developed using the equation of the energy balance, with the aim of determining the order and architecture of the two models. The input and output vectors of the two models are constructed, considering the measures of 4 days of solar radiation, flow mass, environment and heat-transfer fluid temperature in the inlet and outlet from the thermal solar collector. The efficiency curves derived from the two models are detected in correspondence to the test and validation points. The two synthetic simulated efficiency curves are compared with the actual efficiency curve certified by the Swiss Institute Solartechnik Pufung Forschung which tested the solar collector performance in steady-state conditions according to the UNI-EN 12975 standard. An acquisition set of measurements of only 4 days in the transient condition was enough to trace through a Graybox State Space Model the efficiency curve of the tested solar thermal collector, with a relative error of synthetic values with respect to efficiency certified by SPF, lower than 0.5%, while with the ALNN model the error is lower than 2.2% with respect to certified one. [Copyright &y& Elsevier]