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Power quality (PQ) issues are direct consequences of integrating power electronics components and non-linear loads into microgrids. These issues can also be triggered by an unbalanced loading in the microgrid. Certainly, they affect the daily operation scheduling of the microgrid. This paper proposes an optimal harmonic power flow (OHPF) framework for the daily optimal scheduling of a grid-connected microgrid, which is constructed by combining the optimization formulation and harmonic power flow (HPF). Within the framework, PQ is evaluated by observing three indices including voltage magnitude, voltage total harmonic distortion (THD V), and voltage unbalance factor (VUF). A non-iterative mitigation scheme based on demand side management (DSM) is proposed to avoid PQ indices violations and is integrated into the optimization formulation part of the OHPF as a set of load constraints. The proposed constraints allow a flexible combination of different DSM actions including load shedding and interphase load transfer (ILT). Furthermore, the constraints to limit voltage magnitude, voltage THD, and VUF are integrated into the formulation in the form of penalty functions. The software implementation of the proposed OHPF involves Julia-based JuMP.jl and Gurobi solver for optimization part and OpenDSS for harmonic load flow part. The effectiveness of the proposed framework is tested using a modified IEEE 37-bus feeder for different load fluctuations, which allow different combinations of PQ indices violations. The assessment involves both normal and intentional islanding conditions. The results demonstrate that, under different random events, the proposed framework can avoid the violation of PQ indices limits in most cases without adding an excessive computational burden to the original optimization and harmonic load flow algorithms. • Power quality-constrained scheduling framework for a grid-tied microgrid is proposed. • Power quality disturbances are avoided by a set of DSM constraints. • DSM is designed to enable a flexible combination of load shedding and transfer. • Case studies are applied to the modified IEEE 37-bus feeder. • The DSM effectiveness is influenced by the tightness of the load deviation limit. [ABSTRACT FROM AUTHOR]

Distributed generation is a collective term that covers the generation of energy at micro level, distributed in a location near the end user by using renewable and nonrenewable distributed energy generation (DEG) resources including among others, solar, wind, hydro, geothermal and diesel generators. This paper presents a review on the optimization approaches for hybrid DEG systems, considering both stand-alone and grid-connected systems. There are several optimization techniques used on DEG systems, comprising of analytical and artificial intelligent (AI) and hybrid techniques. This work encompasses the selected journal papers published especially in the last five years. A brief background of the optimization approaches been highlighted, particularly identifying the most common techniques to give the basis for analysis of the approaches currently applied on hybrid DEG systems. The analysis shows that AI techniques are still dominating the techniques used for optimization of DEG systems, with particle swarm optimization (PSO) recognized as the most used AI method. The objective functions in the optimization of hybrid DEG systems are currently defined to maximize the reliability, to minimize the expected interruption cost, and to optimize operation schedule of DEG resources. [ABSTRACT FROM AUTHOR]

Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically feasible for current and future use in relation to increased demands for energy and depletion of conventional sources. It is thus important to optimize the size of hybrid microgrid system (HMS) components, including storage, to determine system cost and reliability. In this paper, optimal sizing of a PV/wind/diesel HMS with battery storage is conducted using the Multi-Objective Self-Adaptive Differential Evolution (MOSaDE) algorithm for the city of Yanbu, Saudi Arabia. Using the multi-objective optimization approach, the objectives are treated simultaneously and independently, thereby leading to a reduction in computational time. One of the main criteria to consider when designing and optimizing the HMS is the energy management strategy, which is required to coordinate the different units comprising the HMS. The multi-objective optimization approach is then used to analyze the Loss of Power Supply Probability (LPSP), the Cost of Electricity (COE), and the Renewable Factor (RF) in relation to HMS cost and reliability and is tested using three case studies involving differing house numbers. Results verify its application in optimizing the HMS and in its practical implementation. In addition, optimization results using the proposed approach provided a set of design solutions for the HMS, which will assist researchers and practitioners in selecting the optimal HMS configuration. Moreover, it is important to select optimally sized HMS components to ensure that all load demands are met at the minimum energy cost and high reliability. [ABSTRACT FROM AUTHOR]

In this paper, the potential of solar and wind energy-based distributed generation (DG) in Saudi Arabia is simultaneously analyzed with the aim of maximizing the utilization of available resources. It begins with an analysis of DG application potential for wind and solar energy resources in various regions of Saudi Arabia. The progress of DG applications in terms of research, planning, and exploitation of wind and solar energy resources is then presented. An assessment of the DG contribution to the energy sector of Saudi Arabia has been conducted and the barriers and challenges for the implementation of DG systems in the country are discussed with suggested measures to overcome the challenges. The main findings are that with the huge potential of wind and solar resources for DG applications the country has targeted 50 GW of wind and solar capacity by the year 2040. The Saudi government is expected to provide full support in the form of financial incentives for solar and wind energy projects in order to boost renewable energy development. [ABSTRACT FROM AUTHOR]

This paper discusses maximum power point tracking (MPPT) methods of PV system for normal and partial shading conditions (PSC). The selected MPPT methods were classified as artificial intelligent, hybrid, and other MPPT methods. The comparison of researches on MPPT methods under normal condition and PSC reveals that researchers have concentrated more on shading conditions since the last few years mainly due to the need of power output and efficiency improvements. It is believed that the information contained in this piece of work will be of great use for the researchers in the field under consideration. [ABSTRACT FROM AUTHOR]

A new multi-objective method called Multi-Objective Electric Charged Particles Optimization (MOECPO) is proposed to optimally place wind turbines and at the same time select their optimal heights in an extensive area of wind farm considering several scenarios. This method permits the designer/planner to get several designs in just one run where the maximum efficiency and maximum output power are the objectives. Furthermore, while dealing with an optimization problem, reducing the number of design variables helps to simplify the problem and consequently improves the final solutions. In this paper, a smart approach which is based on binary coding is proposed and implemented for design variables reduction by a high factor. Under the scope of this research work, four case studies are investigated using two different sites and considering the same or different hub heights. The obtained Pareto set of solutions is represented by 96, 95, 199 and 209 solutions, for CASE 1, CASE 2, CASE3 and CASE 4, respectively. This front is spread over a large region and offers several interesting solutions with different number of turbines in the considered wind farm. The results or findings from the proposed approach allow the designer or planner to select the best solution or layout considering many factors. In addition, it can be used to plan the future extensions. • A new method to investigate the optimal location of wind turbines was proposed. • The optimization was done using multi-objective electric charged particles algorithm. • The multi-objective optimization was used to maximize efficiency and output power. • The smart approach was proposed and implemented for reducing design variables. • The results offer various solutions with different number of turbines in a wind farm. [ABSTRACT FROM AUTHOR]

Certain environmental conditions such as accumulation of dust and change in weather conditions affect the amount of solar radiation received by photovoltaic (PV) panel surfaces and thus have a significant effect on panel efficiency. This study conducted an experimental investigation in Surabaya, Indonesia, on the effect of these factors on output PV power reduction from the surface of a PV module. The module was exposed to outside weather conditions and connected to a measurement system developed using a rule-based model to identify different environmental conditions. The rule-based model, a clear sky solar irradiance model that included solar position, and a PV temperature model were then used to estimate the PV output power, and tests were also conducted using an ARM Cortex-M4 microcontroller STM32F407 as a standalone digital controller equipped with voltage, current, temperature, and humidity sensors to measure real time PV output power. In this system, humidity was monitored to identify dusty, cloudy, and rainy conditions. Validated test results demonstrate that the prediction error of PV power output based on the model is 3.6% compared to field measurements under clean surface conditions. The effects of dust accumulation and weather conditions on PV panel power output were then analyzed after one to four weeks of exposure. Results revealed that two weeks of dust accumulation caused a PV power output reduction of 10.8% in an average relative humidity of 52.24%. Results of the experiment under rainy conditions revealed a decrease in PV output power of more than 40% in average relative humidity of 76.32%, and a decrease in output power during cloudy conditions of more than 45% in an average relative humidity of 60.45% was observed. This study reveals that local environmental conditions, i.e., dust, rain, and partial cloud, significantly reduce PV power output. [ABSTRACT FROM AUTHOR]

The tilt angle of photovoltaic (PV) panels is a major factor affecting the amount of solar radiation falling on the panel surface. The optimum tilt angle depends on the position of the sun, latitude and local geographical characteristics. This paper investigates PV panel optimum tilt angles for various cities in the Kingdom of Saudi Arabia. For simulation purposes, horizontal solar radiation data for the study cities was obtained from NASA. MATLAB software was used to optimize tilt angle by maximizing solar radiation. Experiments were conducted to validate the theoretical requirement for negative tilt angles during summer. Results demonstrate that adjusting tilt angles six times per year harvests 99.5% of the solar radiation that could be attained with daily PV panel adjustment. [ABSTRACT FROM AUTHOR]

The potential of hybrid wind/solar energy system in the west coast area of Saudi Arabia is analyzed in this paper. The investigation puts emphasis on the energy production and cost of energy from both wind turbine and photovoltaic (PV) in the hybrid system. Unmet electric load and excess electricity are taken into consideration. The annual average solar irradiation and wind speed considered in this study are 5.95 kWh/m 2 /day and 3.53 m/s, respectively. MATLAB and HOMER software are used to perform the technical and economic analyses of the hybrid system. As indicated from the simulation results, the PV array shares more electricity production than the wind turbine generator if both wind turbine and PV array are utilized in the wind/solar hybrid system with the same sizes. The wind levelized cost of energy is $0.149/kWh, which is more expensive than the solar energy of $0.0637/kWh. The energy cost of the hybrid system is dominated by battery and wind turbine expenses. [ABSTRACT FROM AUTHOR]

Uganda is gifted by nature with abundant energy resources, mainly renewables, which can potentially provide the country with sufficient capacity to meet future growth in energy demand. Surprisingly, Uganda has one of the lowest electricity penetration levels, with only 9–12% of the total population having electricity access; 2–3% of them living in rural communities. There is multitude of challenges facing the energy sector of Uganda, forcing energy demand to always exceed the supply. For decades, hydropower has been and is still the base electricity supply of the country with a supplement of limited biomass, diesel based thermal and solar electricity. The objective of this paper is to review the potential and progress of renewable based distributed generation in Uganda. The potential of the country’s natural renewable resources and existing distributed generation is described and existing government policies are assessed. The challenges facing the energy sector and the suggested remedies are discussed. Various distributed generation systems that could be incorporated into the energy system of the country to improve renewable energy (RE) utilization and possibly contribute to the electricity needs of the population are also proposed and discussed. Exploitation of abundant RE resources through distributed energy generation around the region will not only improve the electricity needs of the country but also increase the economic welfare of the growing population. [ABSTRACT FROM AUTHOR]

In this paper, investigation of the performance of a support vector machine (SVM) and artificial neural networks (ANN) in predicting solar radiation on PV panel surfaces with particular tilt angles was carried out on two sites in Saudi Arabia. The diffuse, direct, and global solar radiation data on a horizontal surface were used as the basis for predicting the radiation on a tilted surface. The amount of data used is equivalent to 360 days, averaged from the 5-min basis data. By solving the tilt angle equation, an optimum value of solar radiation was obtained using a tilt angle of 16° and 37.5° for Jeddah and Qassim locations, respectively. The evaluation of performance and comparison of results of ANN as well as SVM and the measured/calculated data are made on the basis of statistical measures including the root mean square error (RMSE), coefficient of correlation (CC), and magnitude of relative error (MRE). The speed of computation of the algorithms is also considered for comparison. Results indicate that for Jeddah, the CC for SVM is between 0.918 and 0.967 for training and in the range of 0.91981–0.97641 for testing while that of ANN is in the range of 0.517–0.9692 for training and 0.0361–0.0961 for testing. For Qassim, the results are even better with CC of 0.999 for training and 0.987 for testing ANN showed higher values of MRE ranging between 0.19 and 1.16 and SVM is between 0.33 and 0.51 for training and testing respectively. In terms of speed of computation, it is observed that SVM is faster than ANN in predicting solar radiation data with a lower speed of 2.15 s compared to 4.56 s for ANN during training. Moreover, SVM has lower values of RMSE indicating that it is robust and has the capability to minimize errors during computations. Therefore, SVM has significantly higher accuracy, robust during computation and is faster in predicting the radiation on the tilted surfaces in comparison with ANN. [ABSTRACT FROM AUTHOR]

This paper analyzes a hybrid energy system performance with photovoltaic (PV) and diesel systems as the energy sources. The hybrid energy system is equipped with flywheel to store excess energy from the PV. HOMER software was employed to study the economic and environmental benefits of the system with flywheels energy storage for Makkah, Saudi Arabia. The analysis focused on the impact of utilizing flywheel on power generation, energy cost, and net present cost for certain configurations of hybrid system. Analyses on fuel consumption and carbon emission reductions for the system configurations were also presented in this paper. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of renewable energy feed-in tariffs (REFIT) for the selected regions of the globe is done with the aim of drawing lesson for Saudi Arabia. A brief background and status of renewable energy sources (RES) utilization in Saudi Arabia is given at the beginning of this paper, followed by a review of the feed-in tariff (FIT) design models reported in literature. The application of the policy in Europe, the United States, Australia, Asia and Africa is then reviewed. Some observations from the analysis of the FIT application in different countries have been discussed and finally, lessons have been drawn from the study. Some policy recommendations have been given for Saudi Arabia. The analysis of the lessons identified shows that the application of FIT scheme in Saudi Arabia is likely to speed up the development of renewable energy resources within the area. [ABSTRACT FROM AUTHOR]

Resource optimization is a major factor in the assessment of the effectiveness of renewable energy systems. Various methods have been utilized by different researchers in planning and sizing the grid-connected PV systems. This paper analyzes the optimal photovoltaic (PV) array and inverter sizes for a grid-connected PV system. Unmet load, excess electricity, fraction of renewable electricity, net present cost (NPC) and carbon dioxide (CO 2 ) emissions percentage are considered in order to obtain optimal sizing of the grid-connected PV system. An optimum result, with unmet load and excess electricity of 0%, for serving electricity in Makkah, Saudi Arabia is achieved with the PV inverter size ratio of R = 1 with minimized CO 2 emissions. However, inverter size can be downsized to 68% of the PV nominal power to reduce the inverter cost, and hence decrease the total NPC of the system. [ABSTRACT FROM AUTHOR]

Abstract Off-grid hybrid energy systems (HESs) have become more cost-effective and reliable than single-source systems for the electrification of rural areas. This paper presents a techno-economic and environmental analysis of different hybrid systems to supply electricity to a typical Iraqi rural village. The HOMER software is utilized for the optimization of the systems using the multi-year module, which has been overlooked in the literature thus far. The analysis shows that the PV/hydro/diesel/battery HES is the most economical option with a net present cost (NPC) of $113201, in addition to having acceptable technical and environmental performance levels. Throughout the project's 20 year lifetime, PV electricity production is reduced by 9.1% while diesel electricity production, CO 2 emissions and served load are increased by 90.8%, 91.7% and 8.8%, respectively. The NPC for the multi-year module shows an increment of 22.5% in comparison with that of the single year module. Furthermore, the sensitivity analysis of some rarely reported parameters, such as water pipe losses, generator minimum load, battery roundtrip efficiency, battery setpoint state of charge, capacity shortage, PV capital cost multiplier and multi-year, demonstrated that variations in these parameters have significant effects on the system power flow and its economic analysis. Highlights • PV/hydro/diesel/battery hybrid energy systems are analyzed for different scenarios. • HOMER software is employed for the analysis using multi-year module. • Techno-economic and environmental performance of different systems are discussed. • Sensitivity analysis considering variations in several parameters is conducted. [ABSTRACT FROM AUTHOR]

HOMER software is a powerful tool for modeling and optimization of hybrid energy system (HES). The main two default control strategies in HOMER are load following (LF) and cycle charging (CC) strategies. In these strategies, the decision to use the generator or battery at each time step is made based on the lowest-cost choice. Therefore, these strategies are difficult to be implemented in practice especially in countries with continuous fuel price fluctuations. In this study, a new dispatch strategy based on HOMER-MATLAB Link Controller for an isolated wind/diesel/battery HES is proposed to overcome the limitations of the default HOMER strategies. A detailed technical, economic, and greenhouse gas emission analysis is presented for the system under LF, CC, and the proposed dispatch strategies. Besides offering more realistic optimization, the results show that the proposed strategy offers the best economic and environmental performance with a net present cost of $56473 and annual CO 2 emissions of 6838 kg. Furthermore, the sensitivity analysis reveals that the proposed strategy is not affected by the fuel price variation, in opposite to LF, and CC strategies which is affected dramatically by this variation. The findings are of paramount importance towards more realistic and efficient energy management strategies. • A new dispatch strategy for wind/diesel/battery hybrid energy systems using HOMER-MATLAB Link Controller is proposed. • Overcome HOMER default strategies limitation in dealing with continuous fuel price fluctuations. • The proposed strategy is compared with HOMER default strategies in terms of techno-economic and environmental performance. • Sensitivity analysis is conducted by considering variations in critical parameters. • The proposed strategy is more realistic and has better economic and environmental performance than HOMER default strategies. [ABSTRACT FROM AUTHOR]

Iraq has massive potential for electricity generation from solar energy. Because the country currently suffers from daily electricity shortages, a grid-connected PV system is an unsuitable option since the PV cannot serve the load during the electricity blackouts. This paper aims to analyze the techno-economic and environmental feasibility of a solar PV microgrid system which is able to supply the load during both grid availability and outage periods. A household in Baghdad was selected as a case study. HOMER software was used to carry out the overall analysis using five different control strategies. The results indicated that the most economical configuration was achieved by allowing the grid to charge the batteries at all rates, with a net present cost (NPC) of $29,713. A sustainability assessment revealed that preventing the grid from charging the battery resulted in the highest renewable fraction and the lowest CO 2 emissions with 64.9% and 4533 kg/year, respectively. Furthermore, inserting a diesel generator to an economically optimized system was found to reduce the NPC by 11.6%, while increasing the CO 2 emissions by 32.7%. This study showed that implementing this sort of project can provide clean, economical, and continuous electricity production in countries with daily blackouts. • A PV microgrid energy solution by considering the grid blackouts is investigated for a case study in Iraq. • 5 different control strategies are proposed and examined. • HOMER software is used as a tool to determine the optimum configuration. • Techno-economic and environmental analysis is carried out for the proposed system. • Sensitivity analysis is conducted considering variations in some important parameters. [ABSTRACT FROM AUTHOR]