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The application of green energy technologies (GETs) has been accepted universally due to the industrial revolution, increasing energy demand, high standard of living, population growth and fluctuation of crude oil prices. In view of this, GETs have been recognized on a global note as a promising and significant alternative to meet ever increasing power demand. This research work is aimed at optimal operation and design of hybrid renewable energy system (HRES) to enhance the performance of the power system while taking into consideration the energy produced, levelized cost of energy (LCOE), return on investment (ROI), solar fraction (SF), net present value (NPV), payback period and saved CO2 emissions based on the photovoltaic (PV) orientation. This is due to the fact that the solar panel generates more electrical output when its surface is perpendicular to the solar radiation. The PV orientation significantly affects the output of a solar farm, for this reason, fixed tilted plane, vertical axis tracking system and two axes tracking system are proposed in this research work to estimate their effects on the technical, economic and environmental performance of HRES. This paper presents a grid-connected HRES that comprises utility grid, PV, battery system (BS) and load. The modelling and simulation of HRES are implemented by using PVsyst.7 energy tools in conjunction with the meteorological data made available by the National Aeronautics and Space Administration (NASA). The research outputs show that the two axes tracking system is more techno-economic feasible when compared with the fixed tilted plane and vertical axis tracking system based on the following results: Energy obtained from the grid of 4.657 MW/yr, LCOE of 0.075 ZAR/kWh, ROI of 862.7%, SF of 0.6781, NPV of 828,881.74 ZAR, payback period of 3.5 years and carbon balance of 732.240 tons. The outcomes of the study can be used by the power system planners and designers as benchmarks to utilize the prospect of solar resources for power sector reform and the industrial revolution.

This paper presents an optimization model to minimize the fuel cost and CO2 emision on university campuses using an hybrid power system (HPS). The HPS is made up of solar photovoltaic (PV), diesel generator (DG), wind turbine (WT) and battery energy storage system (BESS). Two university campuses are used as case study to investigate the efficiency of the proposed HPS. The objective function is formulated such that each campus load is met by the renewable energy source (RES) when available and the DG only swicthes on when the output of the RES is not eneough to meet the load. The resulting non linear optimization problem is solved using a function in MATLAB called “quadprog”. The results of the simulation are analyzed and compared with the base case in which the DG is used exclusively to meet the entire load. The results show the effectiveness of the optimized HPS in saving fuel when compared to the base case and reflect the effects of seasonal variations in fuel costs.

This paper proposes the initial strategy of designing two degree of freedom proportional integral derivative (2DOF-PID) made load frequency control (LFC) action optimized using Jaya optimization algorithm for a hydro-hydro system. At first, the PID optimized through Jaya is used for hydro-dominated system, and the comparative analysis of all possible error definitions are carried out to show the benefits of selecting integral time absolute error (ITAE) for LFC. Then, 2DOF-PID is designed for the hydro governing system, and its performance is compared with other designs to show the efficacy of the present LFC about computed error values gain of the various models via graphical LFC. The results obtained through simulations are promising but oscillatory with greater settling time. Hence, the proposed controller is retuned by considering the unified power flow control (UPFC) in arrangement with the tie-line and redox flow battery (RFB) units in area-2, and it is further seen that the outcomes of the application show the prevalence of the proposed work.

The search for clean energy for transportation fuel across the globe has grown in intensity. The use of biodiesel as a fuel for compression ignition (CI) engines has shown some deficiencies, e.g., poor storage, and poor pour point. The carbon chain of biodiesel is one of the factors to be considered; the longer carbon chain length leads to decreased ignition delay, which leads to the formation of OH during the premixed combustion phase. The major challenges that render biodiesel inefficient are discussed, like higher viscosity, lower energy content, higher nitrogen oxide (NOX) emissions, lower engine speed and power, injector coking, engine compatibility, high cost, and higher engine wear. The novelty of this work is that it shows that biodiesel conversion to green diesel is possible using a biowaste heterogeneous catalyst to obtain quality and high yield of HDRD with lower cost. This renewable energy (HDRD) possesses properties that are directly compatible with CI engines and transportation engines. This research reviewed biodiesel and UCO as feedstocks for the production of HDRD, including the cost–benefit of these feedstocks. Hydrogenation of biodiesel has the potential to overcome the drawbacks of conventional chemically catalyzed processes.

The present paper discusses the integration as well as contribution of doubly fed induction generator (DFIG) based wind turbines in load frequency control (LFC) of the modern electric power system in order to supply the quality as well as pollution free electric power to the modern customers. In addition the control areas are connected via HVDC tie-line in parallel with EHVAC line with diverse sources i.e. hydro, thermal and gas based power generations in each area. Efforts have been made to propose an optimal LFC design based on the feedback of few state variables which are available for the measurement and contains good information of the complete power system. The LFC design based on few states are implemented and the obtained results are presented to show the LFC enhancement considering DFIG and parallel HVDC/EHVAC lines. Atlast, the beauty and effectiveness of LFC based on few states are compared with LFC design depends on all system states under similar working conditions and the application results are presented.

as the global population expands, the demands on energy supply consequentially increase. However, climate change means emphasis is placed on clean energy sources so we're seeing the emergence of wind power, solar power and hydropower worldwide. This paper focuses on investigating the design and development potential of a South African tidal wave barrage system. The country's expansive coastline provides ample opportunity for the development of such a system; and the constraints on the national grid make this the perfect time to generate clean energy to support the existing power plants. The design of the tidal wave barrage system has been based on tidal wave theory, laws of potential energy, as well as hydrodynamics derived from fluid mechanics. This has allowed for the calculation of potential power generation and the resultant size of the tidal wave barrage system required. These calculations were used as input for the tidal wave barrage system model which allowed for a system simulation. The system effectively consists of the barrage structure, and the power-generating plants - two components linked through mathematical models that provided the system functional diagram. The input parameters for this model were derived from the tidal wave data and the mechanical design properties of the turbine and generator. This was then used to develop a function Matlab®/Simulink® model. Using the Simulink® simulations, it was evident that the tidal barrage system can generate approximately 2MW per unit - the ideal generating capacity for which each generation unit was designed. The conclusion of the system design indicated the tidal wave barrage system has the potential to generate power from tidal waves in South Africa.

Grid-connected solar-PV schemes have become a significant part of the energy balance in the power system to satisfy the growing request for clean, affordable energy. This study attempts to link solar-PV generation with conventional thermal power plants and to integrate the control zone resulting in a hybrid solar PV-thermal electric power system using an AC tie line. An analysis of the frequency dynamics for varying load conditions of the interconnected system is studied. Diverse approaches of proportional, integral, and proportional-integral fuzzy logic built controllers are design and tested in order to match the electric power with variable loads of the system and hence to normalize the frequency of the system in shortest possible time. A comparative analysis of the design topologies is conducted out for the PV-Thermal scheme. Results obtain from the implementation are shown to justify the performance of proposed control efforts, using MATLAB software tool.

Voltage stability studies and to maintain the flat voltage profile is quite important in order to maintain the healthy operation of electric power network as well as to provide the quality and cheap electric energy to the modern power users. Further with the advancement of power electronics technologies and its application to design flexible alternating current transmission devices (FACTS) have made it easier to alleviate the voltage stability problem in a quicker and cheaper way in the modern DNs. Hence, the present research work shows an attempt to investigate and solve the problem of voltage instability in distribution network (DN). All buses and lines are calculated in terms of voltage stability index (VSI) and to identify the optimal location of FACTS. The bus or line with minimum voltage profile in terms of VSI are more sensitive to the voltage collapse and it may further lead to blackouts. The FACTS are permanently installed at the weakest point to enhance voltage profile and improve the voltage stability in the DN. The present study is test on standard IEEE-15 bus DN and application results are shown to verify the feasibility of the present studies for DN.

The interconnected energy system with merging of renewable energy sources such as solar power resulting into an extremely non-linear system and due to which the frequency and power interchange fluctuations becomes serious concerns for power system operators due to variable loading conditions of an energy delivery system. Hence, this paper seeks to study the integration of PV based power generation with thermal power plant resulting into an interconnected energy system for frequency regulation of modern energy system for variable loading conditions. Furthermore, several structures of secondary control actions are also design and checked for frequency regulation studies of interconnected solar thermal system. The gains of secondary control actions are evaluated using diverse tuning techniques and the comparative analysis of all control designs are presented to bring back the frequency and tie-line power fluctuations back to original value and to analyze the effective control action for frequency regulation of interconnected PV thermal power system.

Explored in this work is the comparison of different artificial neural network (ANN) training functions for modeling the daily average solar irradiance (DASI) forecaster. The aim of this work is to establish the comparison studies with reference to the performances of four training functions namely, the Resilient Backpropagation (TRAIN-RP), Levenberg–Marquardt (TRAIN-LM), Scaled Conjugate Gradient (TRAIN-SCG), and Quasi-Newton (TRAIN-BFGS) implemented in the training of the ANN for forecasting the DASI. Using the Levenberg–Marquardt’s learning rule the feed-forward network with back propagation architecture is implemented in the approach of the neural network design. The comparison is done by looking at the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of correlation (R) of the models. The TRAIN-LM performed better than the other models and achieved a 99.742% coefficient of correlation with a mean absolute percentage error (MAPE) of 2.394%. The training, testing, and validation of the neural network is done by utilizing the actual data from six different locations in the North West cities, and these data are mined from the NASA database. The findings in this paper will be useful in the optimizing the micro-grid and its performance.

Illovo is Africa’s largest sugar producer, within the Illovo group each operational entity has its own unique power system. Each mill faces various challenges with regards to layout, loading, operational conditions and it’s utility. It is of utmost importance that the protection settings applied to the electrical infrastructure are efficient, accurate and reliable. This paper presents the analysis and design of protection settings applied to overcurrent relays in an industrial network. This is achieved by analyzing the past protection model designed and comparing it with the current system, thus highlighting the deficiencies. A short circuit and load flow analysis is carried out on the current system, using the engineering software ETAP (Electrical Transient Analysis Program). The result produced are than used to correctly implement new relay co-ordination settings to achieve fault discrimination within the network.

Occurrence of faults in power systems is unavoidable but their timely recognition and location enhances the reliability and security of supply; thereby resulting in economic gain to consumers and power utility alike. Distribution Network (DN) is made smarter by the introduction of sensors and computers into the system. In this paper, detection and classification of faults in DN using Artificial Neural Network (ANN) is emphasized. This is achieved through the employment of Back Propagation Algorithm (BPA) of the Feed Forward Neural Network (FFNN) using three phase voltages and currents as inputs. The simulations were carried out using the MATLAB® 2017a. ANN with various hidden layers were analyzed and the results authenticate the effectiveness of the method.

The security and reliability of supply is often affected due to fault occurrence in electrical power Distribution Networks (DN). In the conventional DN, faults location takes more than the expected time, which results in economic losses to power utility companies as well as consumers. However, the advent of Intelligent Electronic Devices (IEDs) and recent advances in Information and Communication Technology (ICT) has made DN better, safer and smarter. In this paper, we present the outcome of simulation experiments carried out to locate faults in a DN. The IEEE 13 Node Test Feeder was simulated in SIMULINK with different fault conditions and the fault data acquired were utilized to develop an ANN classification model. The outcome of the experiments shows that the ANN based classification model is effective in locating faults on distribution lines with satisfactory performances.

This paper aims to provide an alternative green energy source for a remote GSM base station. To achieve this, a hybrid renewable energy (RE) plant is proposed, comprising a wind turbine, photovoltaic panels, and a fuel cell (incorporated with an electrolyzer and a hydrogen tank for the production and uniform supply of hydrogen). The system will be controlled logically by a power flow controller which will help to provide continuous power to the base station by application of economic optimization of power generation. The hybrid system and the associated load (GSM base Station) are simulated using the HOMER software and required analyses carried out. The simulation results show that renewable energy sources are feasible solutions to reducing air contaminants and pollutants (such as SO 2 & CO 2 ) produced by sources like diesel generators which also serve as an alternate source of energy for a remote GSM base station.

The increasing penetration level of wind power in electrical power system is of great concern to stability of electrical power network because of the fluctuating nature of wind. A low voltage at the point of common coupling (PCC) requires the wind farm to disconnect to prevent damage to the wind energy conversion system (WECS). This disconnection leads to decrease in active power in the network causing instability. This work implements the installation of static synchronous compensator (STATCOM) at the PCC to keep a doubly fed induction generator (DFIG) based wind farm connected to the grid during a low voltage event. The paper also investigates the use of permanent magnet synchronous generator (PMSG) instead of DFIG with a view to comparatively evaluate its low voltage ride through (LVRT) capability.

This paper aims to provide an alternative green energy source for a remote GSM base station. To achieve this a hybrid power generating system comprises a wind turbine, photovoltaic panels, and a fuel cell with the incorporation of the electrolyzer and a hydrogen tank. for the production and uniform supply of hydrogen for the fuel cell. The system will be controlled logically by a power flow controller which intern will help to provide continuous power to the base station based on the analysis of economic optimization power generation. The analytic approach of a hybrid system such the one proposed which feeds a load (Base Station) HOMER software will carry out our application. With the realization of our simulation results, what has been found is that renewable energy sources are a feasible solution to reduce air contaminants by other sources of energy like diesel generators and also applications at remote locations to distribute power generation for stand-alone base stations.