Explore the vast range of titles available.

A renewable and distributed generation (DG)-enabled modern electrified power network with/without energy storage (ES) helps the progress of microgrid development. Frequency regulation is a significant scheme to improve the dynamic response quality of the microgrid under unknown disturbances. This paper established a maiden load frequency regulation of a wind-driven generator (WG), solar tower (ST), bio-diesel power generator (BDPG) and thermostatically controllable load (heat pump and refrigerator)-based, isolated, single-area microgrid system. Hence, intelligent control strategies are important for this issue. A newly developed butterfly algorithmic technique (BOA) is leveraged to tune the controllers’ parameters. However, to attain a proper balance between net power generation and load power, a dual stage proportional-integral- one plus integral-derivative PI − (1 + ID) controller is developed. Comparative system responses (in MATLAB/SIMULINK software) for different scenarios under several controllers, such as a proportional-integral (PI), proportional-integral-derivative (PID) and PI − (1 + ID) controller tuned by particle swarm optimization (PSO), grasshopper algorithmic technique (GOA) and BOA, show the superiority of BOA in terms of minimizing the peak deviations and better frequency regulation of the system. Real recorded wind data are considered to authenticate the control approach.

Microgrids, or distributed systems of local energy generation, transmission, and demand, are now technologically and operationally capable of providing power to communities, especially in rural and peri-urban regions of developing nations. The reliability of the system, the cost of power generation, and the operating environmental impact are the major issues when designing and evaluating the performance of an off-grid hybrid renewable energy microgrid (HREM). This paper presents an integrated method for optimal sizing and operation of an HREM for rural agricultural communities in the Southern Philippines composed of run-of-the-river hydropower, photovoltaics (PV), diesel generator, and a battery energy storage system (BESS) using multi-objective particle swarm optimization (MOPSO) and a proposed multi-case power management strategy. The three conflicting objective functions that were simultaneously minimized were: loss of power supply probability (LPSP), levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions, subject to several constraints. The optimization generated 200 non-dominated or Pareto optimal alternative solutions, 4 of which were selected as solutions of interest. Based on the results, the optimal sizes of the main components for the reliable operation of the system are 100 panels with a rating of 0.25 kW for PV, 100 kWh for BESS, and 13 kW for the diesel generator, with corresponding LCOE, LPSP, and GHG emission values of 0.1795 USD/kWh, 0.05%, and 7874 kg, respectively, for 1 year. The effectiveness of the proposed HREM design was also analyzed, and the study yielded plenty of useful findings that could aid the electrification of the area.

The hybrid AC-DC microgrid (MG) has gained popularity recently as it offers the benefits of AC and DC systems. Interconnecting AC-DC converters are necessary since the MG has both DC and AC sub-grids. Adding an extra harmonic adjustment mechanism to the interlinking converters is promising because non-linear AC loads can worsen the quality of the voltage on the AC bus. The interlinking converters’ primary function is to interchange real and reactive power between DC and AC sub-grids, so the typical harmonic controlling approach implemented for active power filters (APFs) might not be appropriate for them. When the MG’s capacity is high, it is desirable that the switching frequency be lesser than the APFs. The performance of harmonic correction or even system stability may suffer at low switching frequencies. In this study, a harmonic compensating technique appropriate for hybrid AC-DC interlinking converters with lower switching frequencies is planned. The suggested strategy, modeling techniques, stability analysis, and a thorough virtual impedance design are discussed in this work.

This study presents design, performance analysis, and optimization of a hybrid microgrid for the hospital complex located on Eskişehir Osmangazi University (ESOGU) campus using Hybrid Optimization of Multiple Energy Resources (HOMER) software. Solar energy potential of the campus and the real electricity consumption of the hospital collected over one-year period were used in the design of the microgrid. The optimization takes into account the overall performance and the economic feasibility of the microgrid system over its lifetime. The designed microgrid consisting of photovoltaic (PV) modules, diesel generators, batteries, converters, and loads is configured as a grid-connected hybrid system. In order to optimize the system, PV module failures, increase in demand, increase in fuel cost of diesel generators, and mains interruptions are defined as performance variables and realistically modelled in the HOMER simulation. Later, both the individual and the combined effects of these variables on the performance of the microgrid was investigated via simulation using five operating scenarios. The objective was to obtain reliable data from the microgrid design that reflects the realistic operation of microgrid over its 25-years of service time. Simulation results have shown that the economic feasibility and the performance of the microgrid are greatly affected by these factors. For example, in a worst case scenario where all variables are acting together, net present cost increases to 40.44%, cost of energy increases to 21.92%, and operating cost rises to 53.91%. Moreover, the results show a reduction up to 33.30% in the portion of energy that is directly transferred from renewable sources to the load. The simulation results were then used to optimize the design of the microgrid system for the best overall performance. In conclusion, it was demonstrated that the proposed hybrid microgrid system supplies the energy demand of the hospital, lowers the cost of electricity consumption, provides a reasonable payback time, and the best of all, it contributes to the clean campus concept.©2019. CBIORE-IJRED. All rights reserved   Article History: Received May 16th 2018; Received in revised form October 18th 2018; Accepted December 16th 2018; Available onlineHow to Cite This Article: Çetinbaş, I., Tamyürek, B., and Demirtaş, M. (2019) Design, Analysis, and Optimization of a Hybrid Microgrid System Using HOMER Software: Eskişehir Osmangazi University Example. Int. Journal of Renewable Energy Development, 8(1), 65-79.https://doi.org/10.14710/ijred.8.1.65-79

It is known that keeping the power balance between generation and demand is crucial in containing the system frequency within acceptable limits. This is especially important for renewable based distributed hybrid microgrid (DHμG) systems where deviations are more likely to occur. In order to address these issues, this article develops a prominent dual-level “proportional-integral-one plus double derivative PI−(1 + DD) controller” as a new controller for frequency control (FC) of DHμG system. The proposed control approach has been tested in DHμG system that consists of wind, tide and biodiesel generators as well as hybrid plug-in electric vehicle and an electric heater. The performance of the modified controller is tested by comparing it with standard proportional-integral (PI) and classical PID (CPID) controllers considering two test scenarios. Further, a recently developed mine blast technique (MBA) is utilized to optimize the parameters of the newly designed PI − (1 + DD) controller. The controller’s performance results are compared with cases where particle swarm optimization (PSO) and firefly (FF) techniques are used as benchmarks. The superiority of the MBA-PI − (1 + DD) controller in comparison to other two strategies is illustrated by comparing performance parameters such as maximum frequency overshoot, maximum frequency undershoot and stabilization time. The displayed comparative objective function (J) and JFOD index also shows the supremacy of the proposed controller. With this MBA optimized PI − (1 + DD) controller, frequency deviations can be kept within acceptable limits even with high renewable energy penetration.

Electric vehicles (EVs) are emerging as a leading option for traveling while considering the reduction in greenhouse gases (GHG) and corresponding expenditure of fossil fuels. Besides, microgrid (MG) operations pave the way for the development of renewable resources (RRs) based EV charging stations. The paper presents charging circuitry for EVs, designed with a two‐stage conversion mechanism, DC‐DC and hybrid grid in the MATLAB (SIMULINK) environment while using wide bandgap (WBG) semiconductors (SCs) like IGBTs and MESFETs. Power flow in DC and Hybrid‐microgrid (HMG) is supplied with the help of an isolated bidirectional battery charger with the potential of 1.5 kW at 120 V. The AC‐DC conversion is achieved through an inverter, while the rectification mechanism is used for DC‐DC conversion. The designed circuitry also employs four switches, operating at a high frequency, used with a PI controller to maintain the output of 120 V DC for battery charging. The remaining two controllers in the presented circuitry are used for the discharge system of the battery. The paper also presents a detailed comparative analysis of the conduction losses, measured for EV integration and future interventions while considering WBG‐SCs. The examination of the achieved results reveals that minimum losses are in the case of the DC grid system. The investigation of the results also shows lesser harmonic distortion for the DC grid in contrast to the other considered case. Results underline the insinuations of substance‐synchronized EV charging to condense adversative functioning impacts and associated ventures. This study explores how bidirectional semiconductor devices, enhanced by wide bandgap materials, significantly improve the efficiency and stability of DC and hybrid microgrids. Key findings demonstrate their potential in optimizing energy management and supporting renewable integration in advanced power systems.

The numeral of academic publications in the microgrid system field has rapidly grown. A microgrid system is a group of interconnected distributed generation, loads, and energy storage operating as a single controllable entity. Many published articles recently focused on distributed generation, system control, system stability, power quality, architectures, and broader focus areas. This work analyzes microgrid: alternating current (AC), direct current (DC), and hybrid AC/DC microgrid systems with bibliometric network analysis through descriptive analysis, authors analysis, sources analysis, words analysis, and evolutionary path based on the Scopus database between 2010 and 2021. The finding helps find out the top authors and most impact sources, most relevant and frequently used in the research title, abstract, and keyword, graphically mapping the research evolved and identifying trend topic.

Hydrogen is acknowledged as a potential and appealing energy carrier for decarbonizing the sectors that contribute to global warming, such as power generation, industries, and transportation. Many people are interested in employing low-carbon sources of energy to produce hydrogen by using water electrolysis. Additionally, the intermittency of renewable energy supplies, such as wind and solar, makes electricity generation less predictable, potentially leading to power network incompatibilities. Hence, hydrogen generation and storage can offer a solution by enhancing system flexibility. Hydrogen saved as compressed gas could be turned back into energy or utilized as a feedstock for manufacturing, building heating, and automobile fuel. This work identified many hydrogen production strategies, storage methods, and energy management strategies in the hybrid microgrid (HMG). This paper discusses a case study of a HMG system that uses hydrogen as one of the main energy sources together with a solar panel and wind turbine (WT). The bidirectional AC-DC converter (BAC) is designed for HMGs to maintain power and voltage balance between the DC and AC grids. This study offers a control approach based on an analysis of the BAC’s main circuit that not only accomplishes the function of bidirectional power conversion, but also facilitates smooth renewable energy integration. While implementing the hydrogen-based HMG, the developed control technique reduces the reactive power in linear and non-linear (NL) loads by 90.3% and 89.4%.

Hybrid stand-alone systems are extensively used to for supply power in different industries for a wide range of applications. In order to guarantee a steady supply of power to loads in spite of variations in load, wind speed, and solar irradiation, these systems need a battery storage system. In standalone power systems, maintaining power quality is essential, particularly in systems that rely on hybrid energy sources. The battery is connected to the network using bidirectional DC-DC converter with a suitable control mechanism. In this paper, wind turbines and multiple PV are used in parallel and series combinations to ascertain the proper rating of power supply systems. This system uses long short term memory (LSTM) based artificial neural network (ANN) controllers. The controller for battery has been explicitly design to guarantee that electricity is distributed equally between the load and the overall generation. Such methods can improve power quality in different areas, such as variations on the supply side from renewable sources and demand-side timescales. The performance analysis is carried out using the MATLAB/Simulink platform, and realistic results are generated by implementing Hardware-in-the-Loop through OPAL-RT modules. The results are verified with various case studies to justify the importance of adopted procedure in detail.