• Energy Research

Distributed generators (DGs) are increasingly employed in radial distribution systems owing to their ability to reduce electrical energy losses, better voltage levels, and increased dependability of the power supply. This research paper deals with the utilization of a Particle Swarm Optimization algorithm by handling its random constraints to determine the most appropriate size and location of photovoltaic-based DG (PVDG) to keep the asymmetries of the phases minimal in the grid. It is thus expected that this algorithm will provide an efficient and consistent solution to improve the overall performance of the power system. The placement and sizing of the DG are done in a way that minimizes power losses, enhances the voltage profile, i.e., bringing symmetry in the voltage profile of the system, and provides maximum cost savings. The model has been tested on an IEEE 33-bus radial distribution system using MATLAB software, in both conditions, i.e., with and without PVDG. The simulation results were successful, indicating the viability of the proposed model. The proposed PSO-based PVDG model further reduced active power losses as compared to the models based on the teaching–learning artificial bee colony algorithm (TLABC), pathfinder algorithm (PFA), and ant lion optimization algorithm (ALOA). With the proposed model, active power losses have reduced to 17.50%, 17.48%, and 8.82% compared to the losses found in the case of TLABC, PFA, and ALOA, respectively. Similarly, the proposed solution lessens the reactive power losses compared to the losses found through existing TLABC, PFA, and ALOA techniques by an extent of 23.06%, 23%, and 23.08%, respectively. Moreover, this work shows cost saving of 15.21% and 6.70% more than TLABC and ALOA, respectively. Additionally, it improves the voltage profile by 3.48% of the power distribution system.

The focus of this research is to design a ground-mounted photovoltaic system at optimal tilt angle and interrow space to meet high demand of electrical energy. The Department of Electrical Engineering and Technology, GC University Faisalabad has been considered to perform the simulation test. This study is conducted using Meteonorm software for solar resource assessment. Furthermore, HelioScope software is used for modeling of a ground-mounted photovoltaic system, study of PV system’s performance in terms of annual generation, system losses and performance ratio and analysis of photovoltaic module’s performance, current-voltage and power-voltage curves for different irradiance levels. From SLD, it is seen that 11 strings are connected to each inverter and inverters output power are combined by using 20.0 A circuit interconnects. The performance of photovoltaic systems is impacted by tilt angle and interrow spacing. From simulation results of all cases, it is concluded that the PV system installed at 15° tilt angle with 4 feet interrow spacing are more efficient than the other installed PV systems, because total collector irradiance is maximum (1725.0 kWh/m2) as compared to other tilt angles. At 15° tilt angle, the annual production of photovoltaic system is 2.265 GWh and performance ratio of PV system is 82.0%. It is envisioned that this work will provide the guidance to energy system designers, planners and investors to formulate strategies for the installation of photovoltaic energy systems in Pakistan and all over the world.

This study investigates the potential application of Stateflow (SF) to design an energy management strategy (EMS) for a renewable-based hybrid energy system (HES). The SF is an extended finite state machine; it provides a platform to design, model, and execute complex event-driven systems using an interactive graphical environment. The HES comprises photovoltaics (PV), energy storage units (ESU) and a diesel generator (Gen), integrated with the power grid that experiences a regular load shedding condition (scheduled power outages). The EMS optimizes the energy production and utilization during both modes of HES operation, i.e., grid-connected mode and the islanded mode. For islanded operation mode, a resilient power delivery is ensured when the system is subjected to intermittent renewable supply and grid vulnerability. The contributions of this paper are twofold: first is to propose an integrated framework of HES to address the problem of load shedding, and second is to design and implement a resilient EMS in the SF environment. The validation of the proposed EMS demonstrates its feasibility to serve the load for various operating scenarios. The latter include operations under seasonal variation, abnormal weather conditions, and different load shedding patterns. The simulation results reveal that the proposed EMS not only ensures uninterrupted power supply during load shedding but also reduces grid burden by maximizing the use of PV energy. In addition, the SF-based adopted methodology is envisaged to be a useful alternative to the popular design method using the conventional software tools, particularly for event-driven systems.

Currently, uninterrupted charging of Electric Vehicle (EV) is not possible due to grid overloading during day-time. The interruptions during charging causes uncertainty for users. This work proposes a solution to this vehicle charging problem by introducing a combination of Energy Storage Unit (ESU) and Photovoltaic (PV) panel charging along with the grid. The proposed solution is efficient in providing charging for EVs without any interruption in an office parking scenario. The important benefit of the proposed system is the rapid fulfillment of the charging demand of all EVs in parallel to lessening the added grid burden. The control algorithm is designed according to deterministic rule-based schemes. The proposed work is valid for the areas where parity level has already been reached. The efficacy of the proposed technique is evaluated under different charging situations using Matlab simulations. The results show that all connected EVs are charged fully without interruption. Moreover, the simulation results prove that EV charging using the proposed system lowers the added burden from the grid up to 98.6%. This work is envisioned to offer stimulating research prospects in the area of vehicle charging using grid-connected renewable sources.

Wind resource potential is strongly influenced by the exposure, orientation of the terrain and the wind direction. In Pakistan, the northern areas have very attractive sites for wind power plants. However, due to non-standardized masts installed, the collected data are not reliable. Due to the unreliable nature of available data, the investors normally avoid the investing in the wind power projects. Various software and tools have been used so far for the feasibility analysis but due to unreliable data, the proper feasibility analysis is still out of sight. To overcome this deficiency, a feasibility study of a wind power project in the Hunza Valley of Pakistan using reliable data is presented in this paper. For this purpose, the RETScreen is used by exploiting the standard NASA’s (National Aeronautics and Space Administration) database. Since the developing countries are facing problems in the development of wind projects, it is envisaged that this approach will give an easy way to launch new clean energy projects.

The aim of this research is to perform an in-depth performance comparison of ground-mounted and rooftop photovoltaic (PV) systems. The PV modules are tilted to receive maximum solar irradiance. The efficiency of the PV system decreases due to the mutual shading impact of parallel tilted PV modules. The mutual shading decreases with the increasing interrow distance of parallel PV modules, but a distance that is too large causes an increase in land cost in the case of ground-mounted configuration and a decrease in roof surface shading in the case of rooftop configuration, because larger sections of roof are exposed to sun radiation. Therefore, an optimized interrow distance for the two PV configurations is determined with the aim being to minimize the levelized cost of energy (LCoE) and maximize the energy yield. The model of the building is simulated in EnergyPlus software to determine the cooling load requirement and roof surface temperatures under different shading scenarios. The layout of the rooftop PV system is designed in Helioscope software. A detailed comparison of the two systems is carried out based on energy output, performance ratio, capacity utilization factor (CUF), energy yield, and LCoE. Compared to ground-mounted configuration, the rooftop PV configuration results in a 2.9% increase in CUF, and up to a 23.7% decrease in LCoE. The results of this research show that installing a PV system on a roof has many distinct advantages over ground-mounted PV systems such as the shading of the roof, which leads to the curtailment of the cooling energy requirements of the buildings in hot regions and land cost savings, especially for urban environments.