Journal of Solar Energy Research
Volume:8 Issue: 2, Spring 2023

Rooftop solar PV integration into the distribution systems brings benefits to both consumers and utility organizations. These ever-increasing, unplanned generating points in the form of rooftop solar PVs can have undesirable effects on the performance of the system. From the technical point of view, maximum rooftop solar PV hosting capacity mainly depends on whether the parameters such as power loss, overvoltage, and voltage unbalance are kept within the permissible level while increasing the rooftop solar PVs' capacities.  Rooftop solar PVs are owned by individual households and their locations in the distribution system are unpredictable.  The locations and capacities of rooftop solar PVs are the two parameters that influence the above parameters. This paper proposes a stochastic approach to allocate rooftop solar PVs in a distribution system using the Monte Carlo method. An algorithm is developed to allocate rooftop solar PVs in a distribution system and assess the overvoltage and voltage unbalance of the distribution system. Practical data of possible rooftop solar PV capacities are used for the determination of probabilities of occurrence of rooftop solar PV with the given rating. The proposed method is tested using a Low Voltage distribution system in a sub-urban area. The results show that the voltage unbalance and overvoltage at feeder endpoints are mostly affected due to the increase in solar PV integration. The results also show an increase in the solar PV penetration level by more than 40%.

By adding renewable energy sources, such as solar and wind, advanced metering infrastructure, and energy storage systems, the traditional power grid is becoming a smart grid. To prevent the uneconomic operation of a smart grid and increase the penetration of renewable resources, the Demand Response (DR) method is crucial for reducing the peak load and passing critical conditions. In this context, this study presents a multi-objective optimization of the AC optimal power flow (AC-OPF) problem with respect to DR. The novelty of the proposed demand-response-based OPF approach consists of decreasing the system cost through the simultaneous participation of active and reactive power in DR, considering the physical constraints of the AC network and various renewable energy sources in the smart grid, and increasing the calculation accuracy by demand prediction based on previous data using deep learning methods. Finally, using the TOPSIS method, the best DR value was determined according to multi-objective optimization. The effectiveness and resiliency of the proposed method were validated using a modified IEEE 24-bus testing system. The results illustrate that the optimal demand response (20%) achieved not only peak reduction and valley filling in active and reactive power but also minimized the total voltage deviation and system cost.

One of the most important indicators of sustainable rural development is energy supply. Therefore, the present work has been done with the aim of identifying the potential of wind, solar and fuel cell (FC) energy in the electricity supply of Tamin village located in Sistan and Baluchistan province by HOMER 2.81 software. Different scenarios were investigated and diesel generators (DGs) and batteries were used as systems backup. The present work is the first renewable hybrid project based on a FC for a remote area in one of Iran's climates, and accurate and up-to-date technical, economic, energy and environmental analyzes have made the results very important. The results of the investigations showed that the DG-Wind turbine system is the cheapest system with the price of each kWh of electricity produced equal to $0.735. The FC-based system also significantly reduces production pollutants at a cost of $1.004 per kWh of electricity produced and uses 53% more renewable energy than the superior economic scenario. The production of hydrogen for use in a FC during the year is equal to 50.7 kg, and compared to the traditional system (DG only), the FC-based system has a payback time of 3.43 years.

Due to the increasing reduction of fossil energies such as oil and gas and the pollution caused by these fuels' consumption, nowadays the use of renewable energies to meet energy needs has been considered, and solar energy is one of the cheapest and cleanest of them. The share of energy consumption in the building sector is very high and is about 40% of the country's total energy consumption, and the implementation of projects to reduce energy consumption in this sector is very significant in terms of cost, and the goals of reducing energy consumption in this sector can be achieved at a lower price. In this study, for the first time, the production of part of the required heat of a residential building with a pool and sanitary water consumption in different climates of Iran was investigated by Valentin T*SOL 2018 R(4) software in two separate solar heating systems and 4 cities of Isfahan, Babolsar, Tabriz, and Abadan. The results showed that the city of Tabriz performed better in system #1 and Isfahan and Tabriz in system #2.  For all 4 cities, system #2 has a higher efficiency than system #1.

For desalinating seawater and brackish water, a basic and inexpensive device known as a solar still is used. The limited amount of freshwater output that can be obtained from a solar still is its primary flaw, which limits its global use and applicability. The improvement of a solar still's freshwater output is the main goal of this research. Two identical single slope solar stills are created for this purpose, and one of them is changed by adding rectangular aluminium fins and a bamboo cotton wick to the still basin. This modified still is called. The other still that hasn't been altered is known as a standard still. In this experimental study, Kurukshetra, India (29.96°N, 76.87°E) weather conditions are used to evaluate both stills. At varying water depths of 1 cm, 2 cm, and 3 cm, the performance of the modified still and the conventional still are concurrently compared. According to experimentation's findings, 1 cm of water depth is where both stills' daily productivity and optimum water temperature are attained. The daily productivity of the solar still improved by about 19% when bamboo cotton wick was spread over the rectangular fins in the still basin.

Solar energy is one of the most important sources of energy because it is a renewable and inexhaustible energy. This paper presents a new energy recovery snubber for a high step-up boost converter, which can be used in renewable energy systems such as photovoltaic. The proposed snubber enjoys useful advantages such as providing soft-switching conditions, high voltage gain, simplicity of control, and balanced voltage stresses. In this topology, the voltage stress on the diodes and switches is a small percentage of the output voltage. A simple boost and a fly-forward converter are used to increase the output voltage. A snubber circuit is used for the main switch to recover the energy of the snubber capacitor. Therefore, the main switch turns off at low voltage and it causes a reduction in turn off loss. Experimental results of a 48V to 380V and 500W laboratory prototype show efficiency greater than 95% and verify the given theoretical analysis.

In the present study, a solar air heater U shaped turbulators integrated on the absorber plate with artificial roughness has been subjected to computational fluid dynamics (CFD) analysis. For simulation, Renormalization group (RNG) k- ɛ model has been used to investigate several fluid flow properties such as flow behaviour, temperature distribution along absorber plate, and velocity distribution. By taking into account the relative roughness height (e/D) varies from 0.018 to 0.038 and a turbulence intensity of 5%, the aforementioned fluid flow properties have been investigated. Reynolds' number has a value varied in between 3800 to 18000. Also, it has been discovered that effective efficiency reaches a maximum value of around 0.7396 for relative roughness height of 0.038 at Reynolds' number of 16000. Further, results obtained from simulation suggested that there has been a considerable rise of about 22°C in temperature of air after passing through the roughened solar air heater.

The important objective of a building must be to provide a comfortable environment for people. Heating ventilation and air conditioning systems provide a comfortable environment but they have high energy consumption. Therefore, designing an energy-efficient building that balances energy performance and thermal comfort is necessary. Choosing effective parameters for energy performance is an important factor in achieving this goal. This research aims to produce a methodology for multi-objective optimization of daylight and thermal comfort in order to study the effect of wall material and shading of an office building (Tehran a basic-location). The building simulation was developed and validated by comparing predicted daylight and thermal comfort hours based on tests and training in Jupiter Notebook. The sensitivity analysis uses a multiple linear regression method. Secondly, optimization is based on a genetic algorithm with effective parameters to optimize daylight and thermal comfort performance. For this, we developed a parametric model using the Grasshopper plugin for Rhino and then used Honeybee and Ladybug plugins to simulate thermal comfort and daylight, and finally used Octopus engine to find an optimization solution. The result of this paper is essential as a preliminary analysis for building optimization in the open-plan office.

The rapid expansion of renewable energy sources (RES), especially the combination of solar photovoltaic (PV), wind turbine generating (WTG), and battery energy storage systems (BESS), has sparked significant interest in addressing global warming and climate change issues. These energy sources offer numerous advantages, such as reduced emissions and lower operational costs, but their power output is uncertain. In order to account for fluctuating energy costs, a microgrid with diverse energy sources must schedule BESS charging optimally. The proposed method uses the Artificial Rabbit Optimisation (ARO) algorithm to optimise the charging and discharging schedule for BESS, resulting in a decrease in daily energy costs and an improvement in storage state of health (SOH). The SOH is considered an ageing coefficient for conservative BESS operation in order to extend the battery's lifespan under consistent use. To further validate the effectiveness of the energy management strategy, a fixed pricing scheme and a dynamic pricing scheme are utilised to validate its efficacy. When storage degradation and time-of-use (TOU) tariffs are accounted for, the simulation results of voltage, current, and power profiles over a 24-hour period indicate that the proposed method has the capability to maximise the profitability of a grid-connected PV and WTG-based microgrid.

This paper proposes a two-stage three-phase grid-connected inverter for photovoltaic applications. The proposed inverter topology consists of a DC-DC boost converter and a three-phase grid-connected inverter. The DC-DC boost converter is used to boost the low voltage DC output of the PV array to a high voltage DC level that is suitable for feeding into the grid-connected inverter. The three-phase grid-connected inverter is used to convert the high voltage DC output of the boost converter into a three-phase AC output that is synchronized with the grid voltage. The proposed inverter topology offers several advantages over traditional single-stage inverters. Firstly, the DC-DC boost converter allows for the use of a smaller, more efficient inverter in the second stage, reducing the overall cost of the system. Secondly, the use of a boost converter allows for the maximum power point tracking of the PV array, which can increase the overall efficiency of the system. The proposed inverter topology offers improved control of the grid current, reducing the impact of the PV system on the grid. The proposed topology has been simulated using MATLAB/Simulink and the results show that the system is capable of delivering a high-quality three-phase AC output with low harmonic distortion.

A significant research focus is how to make photovoltaic (PV) systems operate as efficiently as possible. A sufficient, accurate, and detailed model of the actual PV system is needed in order to get the best performance out of solar panels. More specifically, the parameters of these models are fitted to actual data to determine the correctness of the models. In order to determine the most accurate parameters of a photovoltaic cell, module, and array using actual data, this research suggests a novel method called MSNS-HAL, which combines Halley's method with a modified social network search algorithm. A control parameter with a Gaussian and Cauchy distribution is randomly added to the search space to improve parameter estimation performance and speed up the agents' convergence to the best solution. The best estimate of currents is then determined using Halley's root-finding technique. The proposed model, which has a best root mean square error of 7.1719 x 10-4 for the RTC cell, 2.0388 x 10-3 for the Photowatt PWP module, and 0.0069 for the experimental field of 18 PV panels, has the highest accuracy when compared to 12 other current optimization approaches.

In recent years, grid-connected solar systems have become increasingly common on low-voltage grids to promote renewable energy sources. In these systems, LCL filters are commonly used to eliminate high-frequency harmonics produced by switching grid-connected inverters. However, the resonance frequency of LCL filters is highly dependent on network impedance. Variations in network impedance can shift the resonance frequency, causing instability in the system. To address this issue, this paper proposes a new method for attenuating resonance using capacitor-current feedback with positive virtual impedance shaping. It can provide a positive equivalent resistance almost within the Nyquist frequency, i.e., the entire controllable frequency range. The proposed method maintains system stability against changes in network impedance and offers good performance against changes in the production capacity of the solar array. For maximum power point tracking, the incremental conductance method and integral regulator are used. Simulation results using MATLAB/Simulink software demonstrate the effectiveness of the proposed method in injecting high-quality current into the network and maintaining stability against changes in network impedance. The proposed method can lead to improved power quality and increased efficiency of grid-connected solar systems, which can help to promote the adoption of renewable energy sources and reduce carbon emissions.

One way to increase the voltage gain and reduce the voltage stress on the switch is by utilizing coupled inductors. However, a major drawback of this technique is the occurrence of voltage spikes on the switch, which are caused by the discharge of energy from the leakage inductance.This paper proposes a zero current switching step-up converter to mitigate the voltage stress on the switch resulting from the high voltage gain of the converter. This enables the utilization of switches with lower drain-source resistance, leading to a more affordable price. The converter's auxiliary circuit requires minimal elements and does not require an additional switch, resulting in a straightforward control circuit. Another advantage of the converter is the transfer of energy from the auxiliary circuit to the output. Various operation modes of the proposed step-up converter have been investigated, and the converter's behavior has been simulated using PSpice software. To validate the accuracy of the analysis and simulation results, an 80W prototype has been implemented.

The construction industry tries to optimize energy consumption and reduce environmental damage. Lighting is an important parameter which is effective in energy consumption of buildings. The amount of light which is received on different floors of high-rise residential buildings is not the same. Therefore, it is necessary to determine the best optimal physical parameters of the atrium that can provide sufficient lighting to all building floors. This study analyses this issue in the humid subtropical climate of the Dezful city. A model was simulated by Grasshopper, then Honeybee and Ladybug plugins were used to evaluate each space lighting. Daylight autonomy and Useful daylight illuminance indices were considered to compare the proposed models. This research aimed to achieve the best position and elongation of the atrium and to optimize the dimensions as well as the setbacks of the atrium on the floors to receive the minimum light is required for residential spaces. Based on the results, the position of atriums can be selected according to occupancy hours, and east-west elongation illustrated the best performance. Using the obtained patterns can lead to introducing models that can increase the DLA value of the first floor in multi-story buildings by 3% to 8%.

Due to the increasing penetration of distributed generation systems, the desire to use DC smart grids has increased. DC smart grids are preferred to AC grids because these networks are more compatible with renewable sources that generate DC electricity. This paper presents the design of a new three-port isolated DC-DC converter for photovoltaic (PV)-battery application in the DC smart grid. In the proposed converter, by combining the required converters for PV and battery, the number of required converters has been reduced so that the function of charging/discharging the battery, as well as tracking the maximum power point of solar panels, can be done with the proposed converter. As a result, the number of required parts and the cost of the system are reduced and the efficiency of the converter increases. Finally, the converter's performance has been evaluated with the help of analysis and simulation, and the obtained results indicate the proper performance of the proposed converter.