Photovoltaic systems are a sustainable environment-friendly means of furnishing electricity. Building-Integrated Photovoltaic (BIPV) is a concept with growing popularity. This paper explains design principles for a BIPV system and describes different types of such systems such as roof-integrated, façade-integrated, etc. Then the impact of building form and location on the performance of BIPV systems are mentioned to provide recommendations for choice of an appropriate BIPV system.

Increasing of word demand load caused a new Distributed Generation (DG) to enter to power system. One of the most renewable energy is the Photovoltaic System. It is beneficial to use this system in both separately as well as connected to power system using power electronics interface. In this paper an optimal PID controller for Photovoltaic System systems has been developed. The optimization technique is applied to PID optimal controller in order to control the voltage of Photovoltaic System against load variation, is presents. Nonlinear characteristics of load variations as plant input, Photovoltaic System operational behavior demand for high quality optimal controller to ensure both stability and safe performance. Thus, Honey Bee Mating Optimization (HBMO) is used for optimal tuning of PID coefficients in order to enhance closed loop system performance. In order to use this algorithm, at first, problem is written as an optimization problem which includes the objective function and constraints, and then to achieve the most desirable controller, HBMO algorithm is applied to solve the problem. In this study, the proposed controller is applied to the closed loop Photovoltaic system behavior. Simulation results are done for various loads in time domain, and the results show the efficiency of the proposed controller in contrast to the previous controllers.

This study aims to report on the application of Linear Quadratic Integral (LQI) based global maximum power point tracker (GMPPT) method for transferring the available maximum power from Photovoltaic (PV) systems to load in unshaded and shaded conditions. For the maximum power transmission under varying the environmental conditions and partially shaded conditions, MPPT technologies are utilized in PV systems. For the improvement of functioning MPPT, a new two-level control structure which decreases difficulty in the control process and efficiently deals with the uncertainties in the PV systems is introduced. In the proposed approach, the reference voltage at the global maximum power point (GMPP) is estimated by a new scanning algorithm. The difference between the reference voltage and the voltage of the PV array is then used by LQI controller to generate the duty cycle for a boost converter. The design process of the proposed approach is explained as step by step. The benefits of the approach are quicker tracking capability, transferring maximum deliverable power and simple implementation. To verify the proposed method, several irradiation profiles that create several peaks in the P-V curve are used. The simulation results show that the proposed method causes PV systems to track the GMPP immediately so that no oscillation around the GMPP is observed. Therefore, maximum efficiency can be derived from the PV system.

Using DC micro-grid to connect more efficiently with DC output has increased. The sources are Photovoltaic and energy storage systems. The conversion losses of the sources for supplying the loads are reduced compared to the AC micro-grid. This method aims at combining the above methods to achieve maximum use of Renewable Energy and Energy Storage and enhancing the efficiency of the grid by using the Active power Filter and applying the DC to DC converter to boost the conversion efficiency and load management with having island inputs and the way to manage the inputs in the state of load disturbance and exit of one of the island inputs from the circuit is rapid injection of energy stored into the grid in the quickest time and the coordinated control between grid and Photovoltaic system and battery have been studied in MATLAB/SIMULINK software. The amount of simulation time will be considered 0. 5 seconds.

This study was conducted during summer and winter of 2018- 2019 in the agricultural research field of Shahid Chamran University. Experimental design was split- plot based on RCBD with three replications. The main plot was the type of agricultural system in three levels including conventional (Conv), organic (Org) and sustainable (Sust) (integrated between Conv and Org) and sup- plot was the type of pre- cultivated crop in sequence with wheat including cultivation of mung bean (M- W), corn (C- W), sesame (S- W) and fallow (F- W). Yield quantity (yield and its component) and quality (grain protein), an estimate of photosynthesis matter transfer index of wheat and soil organic carbon (SOC) after one double-cropping were measured. The result showed that the highest (545.04 g/m2) and the lowest (409.28 g/m2) seed yields were obtained in Conv and Org respectively. In contract, with the changing type of system from Conv to Org, grain protein was increased significantly (from 8.3 to 9.6 %). In addition, the highest (535.47 g/m2) yield of wheat was obtained from M- W double cropping. On the other hands the highest remobilization and current photosynthesis matter were obtained in the organic agricultural system with M- W and conventional with M- W double cropping. The situation of SOC showed that the highest (33.18 mg/g) SOC was obtained in the organic agricultural system with C- W double cropping. The reason for improving SOC in the organic and sustainable agricultural system was application of organic matter (compost and vermicompost) and crop residue management. Totally, from the crop ecology point of view, sustainable agricultural method with a sequence of M- W was the most desirable system.

Photovoltaic (PV) systems have been gaining great attention during the last decade. One of the main faults in PV arrays is partial shading, affecting its electrical parameters. Failure to detect this fault may result in optimal generated power reduction and hot spotting leading to damage to cell encapsulant and second breakdown. This paper develops a partial shading detection algorithm that only requires the available measurements of array voltage and current. By quantifying the wave-shape of the super-imposed component of PV array power by the skewness function, it can discriminate a partial shading condition from the short-circuit and high-resistance faults. The developed scheme is implemented in a central intelligent electronic device and does not require a communication link and training data set. The merits of the proposed partial shading detection algorithm are demonstrated through several fault scenarios using a 5×5 grid-connected PV generation system.

Due to the negative environmental effects of fossil fuel combustion, there is a growing interest in both improved efficiency in energy management and a large-scale transition to renewable energy systems. Using both of these strategies, a large institutional-scale hybrid energy system is proposed here, which incorporates both solar Photovoltaic energy conversion to supply renewable energy and cogeneration to improve efficiency. In this case, the Photovoltaic reduces the run time for the cogeneration to meet load, particularly in peaking air conditioning times. In turn, however, the cogeneration system is used to provide power back up for the Photovoltaic during the night and adverse weather conditions. To illustrate the operational symbiosis between these two technical systems, this study provides a case study of a hybrid Photovoltaic and cogeration system for the Taleghani hospital in Tehran. Three design scenarios using only existing technologies for such a hybrid system are considered here:1) single cogeneration + Photovoltaic, 2) double cogeneration + Photovoltaic, 3) single cogeneration + Photovoltaic + storage. Numerical simulations for Photovoltaic and cogeneration performance both before and after incorporating improved thermal energy management and high efficiency lighting were considered. The results show that the total amount of natural gas required to provide for the hospitals needs could be lowered from the current status by 55 % for scenario 1 and 62 % for both scenarios 2 and 3, respectively. This significant improvement in natural gas consumption illustrates the potential of hybridizing solar Photovoltaic systems and cogeneration systems on a large scale.

This paper provides an overview of the current innovations in Building Integrated Photovoltaic Thermal systems. This paper briefly describes varying performance evaluation techniques, optimisation techniques, and the environmental impact and cost implication of Building Integrated Photovoltaic Thermal systems. The results reveal high energy-pin efficiency with Building Integrated Photovoltaic Thermal systems of over 50% and more efficient than when the two systems are incorporated separately. Exergy analysis is a more insightful means of analyzing system effectiveness than energy analysis. The paper covers the current algorithms for various optimisation algorithms such as Genetic Algorithms and Particle Swarm Optimisation that provide enhanced utilization improvements. An evaluation of the environmental impact of Building Integrated Photovoltaic Thermal in terms of carbon dioxide emission reduction and building energy optimisation is made. The results of the life cycle cost studies show that, even though the initial cost is higher than conventional solutions, the overall economic profit is more significant in the future. Some of the challenges described in the paper include increased initial costs and sophisticated integration procedures. In contrast, possible future developments include new materials, Building Integrated Photovoltaic Thermal system standardization, and integration in smart grids. This review is intended to be a state-of-the-art source of information for researchers, engineers, architects, and policymakers involved in enhancing sustainable building technologies using building-integrated Photovoltaic thermal systems.