Search Results (88)

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

This research focuses on optimizing a grid-connected hybrid microgrid system (HMGS) for The Neotia University (TNU), West Bengal, India, utilizing renewable energy sources to improve sustainability and energy efficiency. The system integrates solar panels, wind turbines, and an existing diesel generator (DG) to meet campus energy demands, including electric vehicle (EV) charging facilities for residents and staff. The pelican optimization algorithm (POA) is employed to determine the optimal capacity of PV and wind turbine units for reducing energy costs, enhancing reliability, and minimizing carbon emissions. The results reveal a substantial decrease in the cost of energy (COE) from INR 11.74/kWh to INR 5.20/kWh. Full article

In a smart microgrid (SMG) system that deals with unpredictable loads and incorporates fluctuating solar and wind energy, it is crucial to have an efficient method for controlling frequency in order to balance the power between generation and load. In the last decade, cyberattacks have become a growing menace, and SMG systems are commonly targeted by such attacks. This study proposes a framework for the frequency management of an SMG system using an innovative combination of a smart controller (i.e., the Fuzzy Logic Controller (FLC)) with three conventional cascaded controllers, including Fractional-Order PI (FOPI), Tilt Integral Fractional Derivative (TID^μ), and Proportional Integral Derivative Acceleration (PIDA). The recently released Eel and Grouper Optimization (EGO) algorithm is used to fine-tune the parameters of the proposed controller. This algorithm was inspired by how eels and groupers work together and find food in marine ecosystems. The Integral Time Squared Error (ITSE) of the frequency fluctuation (ΔF) around the nominal value is used as an objective function for the optimization process. A diesel engine generator (DEG), renewable sources such as wind turbine generators (WTGs), solar photovoltaics (PVs), and storage components such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) are all included in the SMG system. Additionally, electric vehicles (EVs) are also installed. In the beginning, the supremacy of the adopted EGO over the Gradient-Based Optimizer (GBO) and the Smell Agent Optimizer (SAO) can be witnessed by taking into consideration the optimization process of the recommended regulator’s parameters, in addition to the optimum design of the membership functions of the fuzzy logic controller by each of these distinct algorithms. The subsequent phase showcases the superiority of the proposed EGO-based FFOPI-TID^μ-PIDA structure compared to EGO-based conventional structures like PID and EGO-based intelligent structures such as Fuzzy PID (FPID) and Fuzzy PD-(1 + PI) (FPD-(1 + PI)); this is across diverse symmetry operating conditions and in the presence of various cyberattacks that result in a denial of service (DoS) and signal transmission delays. Based on the simulation results from the MATLAB/Simulink R2024b environment, the presented control methodology improves the dynamics of the SMG system by about 99.6% when compared to the other three control methodologies. The fitness function dropped to 0.00069 for the FFOPI-TID^μ-PIDA controller, which is about 200 times lower than the other controllers that were compared. Full article

This study presents a systematic approach to designing and optimizing a 100% renewable hybrid microgrid system for sustainable rural electrification in Khlong Ruea, Thailand, using HOMER Pro software (Version 3.15.3). The proposed system integrates photovoltaic (PV) panels (20 kW), pico hydro (9.42 kW), and lithium-ion battery storage (264 kWh) to provide a reliable, cost-effective, and environmentally sustainable energy solution for a remote village of 306 residents. The methodology encompasses site-specific resource assessment (solar irradiance, hydro flow), load demand analysis, and techno-economic optimization, minimizing the net present cost (NPC) and cost of energy (COE) while achieving zero emissions. Simulation results indicate the optimal configuration (S1) achieves an NPC of USD 362,687 and COE of USD 0.19/kWh, with a 100% renewable fraction, outperforming the current diesel–hydro system (NPC USD 3,400,000, COE USD 1.85/kWh, 61.4% renewable). Sensitivity analysis confirms robustness against load increases (1–5%), though battery capacity and costs rise proportionally. Compared to regional microgrids, the proposed system excels in terms of sustainability and scalability, leveraging local resources effectively. The lifecycle assessment highlights the battery’s embodied emissions (13,200–39,600 kg CO₂e), underscoring the need for recycling to enhance long-term sustainability. Aligned with Thailand’s AEDP 2018–2037 and net-zero goals, this model offers a replicable framework for rural electrification in Southeast Asia. Stakeholder engagement, including community input and EGAT funding, ensures practical implementation. The study demonstrates that fully renewable microgrids are technically feasible and economically viable, providing a blueprint for sustainable energy transitions globally. Full article

This study presents analysis and optimization of a standalone hybrid renewable energy system (HRES) for Adama Science and Technology University’s ICT center in Ethiopia. The proposed hybrid system combines photovoltaic panels, wind turbines, a battery bank, and a diesel generator to ensure reliable and sustainable power. The objectives are to minimize the system’s total annualized cost and loss of power supply probability, while energy reliability is maintained. To optimize the component sizing and energy management strategy of the HRES, we formulated a mathematical model that incorporates the variability of renewable energy and load demand. This optimization problem is solved using a hybrid genetic algorithm (HGA). Simulation results indicate that the HGA yielded the best solution, characterized by the levelized cost of energy of USD 0.2546/kWh, the loss of power supply probability of 0.58%, and a convergence time of 197.2889 s. Full article

Isolated microgrids have long been considered alternative power system entities that can integrate various types of distributed energy sources such as diesel and renewable power generators including energy storage. Renewable energy sources, such as wind and solar PV, introduce low inertia and high intermittency to the microgrid. For this reason, coordinated control and frequency stabilisation are crucial for maintaining higher service levels in the microgrid. This paper reports on the design and development of two proposed methods for virtual inertia provision, namely model-based and filter-based methods, which support the frequency stability of AC/DC microgrids. The inertial power produced by these methods was implemented through power-controlled voltage source converters, associated with a Li-ion battery energy storage system. To derive and develop the functions for the virtual inertia providers using these methods, a new electromechanical power-speed model was developed to represent the interaction between the microgrid AC/DC-sides and its generators. Small-signal analysis using the linearised form of this model was carried out, in addition to deriving the law for the model-based virtual inertia method. Detailed physical-system simulation and tests were performed, and performance analysis of the resulting generator speed-responses using the proposed methods illustrated their merits compared with other methods, namely the standard $df/dt$ and frequency-event techniques. Full article

This paper deals with the design of an advanced optimal strategy to enhance power management and frequency control in marine microgrids. The investigated system incorporates a mix of renewable energy sources coordinated with hybrid energy storage devices. A new robust optimal PIDN controller is employed to tackle the intermittency challenges associated with wind and marine power generation, ensuring precise frequency control via time-domain simulations. A multiple-energy storage system, which includes SMES/batteries/ultra-capacitors (UCs) and fuel cells (FCs), was implemented to manage frequency variations and optimize the charge/discharge cycles of batteries. To further mitigate power fluctuations and extend the life of batteries, a low-pass filter was applied, inspired by optimization techniques for hybrid storage systems. A notable innovation of this study is the introduction of an offshore photovoltaic (PV) array into the system, enhancing the diversity and capacity for renewable energy production in the microgrid. A comprehensive comparative study was conducted, exploring a range of scenarios: with and without energy storage, with the integration of PV energy, excluding the use of diesel, and implementing battery filtering. This approach allowed for an evaluation of the impact of each configuration on the overall performance of the marine microgrid, underscoring significant enhancements in sustainability, efficiency, and a reduction in the dependence on fossil fuels. Preliminary results point to a considerable improvement in the energy management of isolated marine environments, showcasing the potential of this strategy for future marine microgrid applications. This research makes a significant contribution to the advancement of renewable energy management systems, presenting a viable and sustainable option for powering marine microgrids. Full article

This study focuses on microgrid systems incorporating hybrid renewable energy sources (HRESs) with battery energy storage (BES), both essential for ensuring reliable and consistent operation in off-grid standalone systems. The proposed system includes solar energy, a wind energy source with a synchronous turbine, and BES. Hybrid particle swarm optimizer (PSO) and a genetic algorithm (GA) combined with active disturbance rejection control (ADRC) (PSO-GA-ADRC) are developed to regulate both the frequency and amplitude of the AC bus voltage via a load-side converter (LSC) under various operating conditions. This approach further enables efficient management of accessible generation and general consumption through a bidirectional battery-side converter (BSC). Additionally, the proposed method also enhances power quality across the AC link via mentoring the photovoltaic (PV) inverter to function as shunt active power filter (SAPF), providing the desired harmonic-current element to nonlinear local loads as well. Equipped with an extended state observer (ESO), the hybrid PSO-GA-ADRC provides efficient estimation of and compensation for disturbances such as modeling errors and parameter fluctuations, providing a stable control solution for interior voltage and current control loops. The positive results from hardware-in-the-loop (HIL) experimental results confirm the effectiveness and robustness of this control strategy in maintaining stable voltage and current in real-world scenarios. Full article

The rapid progress in renewable energy sources and the increasing complexity of energy distribution networks have highlighted the need for efficient and intelligent energy management systems. This paper presents a comparative analysis of two optimisation algorithms, P and M70, used for the optimal control of the operation of microgrids in islanded mode. The main objective is to minimise production costs while ensuring a reliable energy supply. Algorithm P prioritises the use of photovoltaic (PV) and battery storage and operates the diesel generator at minimum capacity to reduce fuel consumption and maximise the use of renewable energy sources. Algorithm M70, on the other hand, uses a heuristic approach to adaptively manage energy resources in real time. In this study, the performance of both algorithms is evaluated through simulation in different operating scenarios. The results show that both algorithms significantly improve the efficiency of the microgrid, with the M70 algorithm showing better adaptability and cost efficiency in dynamic environments. This research contributes to ongoing efforts to develop robust and scalable energy management systems for future smart grids. Full article

This research paper introduces an optimization methodology for the strategic electric sources’ placement at multiple positions in a DC islanded microgrid characterized by a mesh network, aiming to minimize line losses while considering minimal cable weight. The DC microgrid studied in this paper is composed of PV panels, batteries, a diesel generator, and 20 residential loads. Employing Dijkstra’s algorithm, a graph algorithm used in Google Maps, the study identifies the shortest path (resistance) between potential source nodes and various variable loads within a predefined electric distribution mesh network topology. This study focuses on active power considerations and offers valuable insights into the placement optimization of multiple sources’ positions in DC microgrid mesh networks. A key contribution of this paper lies in the ranking of source node positions based on minimal to maximal line losses, taking into consideration optimal cable weights, while using MATPOWER to validate sources’ ranking based on Dijkstra’s hypothesis. The research further includes a techno-economic study to assess the viability of sources’ placement at multiple positions within the mesh network, comparing it with the optimal placement scenario involving a single position for all sources. This methodology serves as a valuable resource for system designers and operators aiming to minimize line losses and optimize energy distribution in DC microgrids in a mesh topology. Full article

Amidst a growing global focus on sustainable energy, this study investigates the underutilization of renewable resources in the southern region of Saudi Arabia, with a specific emphasis on the Najran Secondary Industrial Institute (NSII). This research presents an in-depth analysis of installing a hybrid microgrid (MG) system on the roofs of NSII buildings, exploring six cases with varying tilt and azimuth angles. The study innovatively integrates architectural design and system administration, a novel approach for this location, and benchmarks the optimal angles against Hybrid Optimization of Multiple Energy Resources (HOMER) software defaults. The proposed system consists of solar photovoltaic (PV) panels, a battery storage system (BSS), a converter, a diesel generator (DG), and a grid. The selected model balances technological and economic viability with environmental considerations, ensuring a reliable power supply within the NSII’s roof area constraints. An extensive sensitivity analysis evaluates the system’s resilience across different scenarios. The current system, which is grid-only, has an estimated Net Present Cost (NPC) of about USD 7.02M and emits 1.81M kg/yr of CO₂. The findings point to installing a microgrid with a 20.97° tilt and 50° azimuth angle as optimal, demonstrating 54.69% lower NPC and 92% lower CO₂ emissions, along with zero kWh/year unmet electrical load when applying the resilience assessments. This outcome highlights Saudi Arabia’s southern region’s renewable energy potential, aligning with national mega-projects and energy initiatives. Full article

Microgrids have been widely used due to their advantages, such as flexibility and cleanliness. This study adopts the hierarchical control method for microgrids containing multiple energy sources, i.e., photovoltaic (PV), wind, diesel, and storage, and carries out multi-objective optimization in the tertiary control, i.e., optimizing the economic cost, environmental cost, and the degree of energy utilization of microgrids. As the traditional multi-objective particle swarm algorithm is prone to local convergence, this study introduces variable inertia weight and learning factors to obtain a modified particle swarm algorithm, which is more advantageous in multi-objective optimization. Compared to the traditional particle swarm algorithm, the modified particle swarm algorithm increased the photovoltaic absorbed rate from 0.7724 to 0.8683 and the wind energy absorbed rate from 0.6064 to 0.7158 in one day, which resulted in an increase in energy utilization by 14.89%, and a reduction in financial environmental costs from RMB 135,870 to RMB 132,230. The simulation of the optimization effect of the conventional particle swarm algorithm and the modified particle swarm algorithm on the microgrid were carried out, respectively, in MATLAB, which verifies the advantage of the modified particle swarm algorithm on the optimization of microgrids. Then, the optimization results, i.e., the data of the power scheduling process of the four power sources, were made into a table and imported into the microgrid model in Simulink. The simulation results indicated that the microgrid was able to output stable voltage, current, and frequency. Finally, the changes in microgrids affected by the external environment were further investigated from the aspects of the market environment and natural environment. Moreover, we verified the presence of a contradiction between the optimization of the microgrid economy and environmental protection. Thus, microgrids need to adjust their optimization focus according to the natural conditions in which they are located. Full article

Microgrids, with integrated PV systems and nonlinear loads, have grown significantly in popularity in recent years, making the evaluation of their transient behaviors in grid-connected and islanded operations paramount. This study examines a microgrid’s low-voltage ride-through (LVRT) and high-voltage ride-through (HVRT) capabilities in these operational scenarios. The microgrid’s behavior was analyzed using both electromagnetic transient (EMT) and RMS simulation methods. Two operational modes, grid-connected and islanded, were considered. A three-phase diesel generator acted as a reference machine in islanded mode. Findings highlighted distinct behaviors in the two operational modes. The EMT simulation revealed in-depth characteristics of electrical parameters, showing high-frequency oscillations more precisely than the RMS simulation. Additionally, the transient recovery times were longer in islanded mode compared to grid-connected mode. The EMT simulation offers a more detailed portrayal of transient behaviors than the RMS simulation, especially in capturing high-frequency disturbances. However, its completion time becomes significantly extended with longer simulation durations. Microgrids showcase distinct transient behaviors in grid-connected versus islanded modes, especially in LVRT and HVRT scenarios. These findings are critical for the design and operation of modern microgrids. Full article

Energy resiliency plays an important role in the proper functioning of data centers as they heavily rely on an uninterrupted power supply to ensure smooth operation. In the case of a power outage, the data center’s operation might be hampered, which results in system downtime, data, and economic loss. This issue is severe in developing countries where power supply infrastructures are inadequate and conventional. Microgrids can be an effective solution in this regard. Although several studies developed microgrids to observe the energy resilience benefit for some critical facilities, critical facilities like data centers are often overlooked. In addition, sustainability analysis of a microgrid is also scarce in the present literature. Therefore, one new resilience and sustainability indicator has been developed and implemented in this analysis to fill this gap. For this, new indicators, such as the resilience cost index (RCI) and renewable energy penetration (REP), were used in this study. This study used HOMER version 3.13.3 and REopt software to simulate a robust photovoltaic (PV) and battery microgrid for a hypothetical data center in Bangladesh. A random (48 h) outage was assigned to witness the adaptability of the modelled micro-grid. The suitable size of PV and battery was found to be 249,219 kW and 398,547 kWh, respectively. The system’s USD 18,079,948 net present value (NPV) demonstrates the economic potential of utilizing PV and battery microgrids for data centers. The RCI of the system is found to be 35%, while the REP is 87%. The energy consumption saving of the system is USD 21,822,076. The system emits 652% less CO₂ than the grid. The result of this system is also compared with a diesel-based system. After comparison, it is found that the developed PV/battery microgrid provides better environmental and economical service than the diesel generator. During blackouts, the system keeps the data center powered up without interruption while improving energy resilience and lowering carbon emissions. The outcome of this current analysis can serve as a blueprint for other microgrid projects in Bangladesh and other developing countries. By integrating PV/battery microgrids, data centers can cut costs, reduce emissions, and optimize energy use. This will make data centers less reliant on grid services and more flexible to forthcoming development. Full article

The increased unavailability of electricity from the National Utility in South Africa, coupled with the extreme conditions of rural areas and general lack of infrastructure, leads to the setup of unique microgrids to utilize the conditions available. One such unique microgrid, a scalable photovoltaic (PV)-Diesel generator microgrid, is situated in the Phuthaditjhaba district on the University of the Free State (UFS) Qwaqwa campus in South Africa. Waste heat and greenhouse gas (GHG) emissions are considered inherent by-products of campus hybrid PV—Diesel generator microgrids with high utilization opportunities for both heat exchange and carbon offsets. This paper presents confirmation that available waste heat from a typical rural campus microgrid can be stored through the use of a rock bed thermal energy storage (TES) system. It was identified that, through the temperature profile of the stored waste heat, thermal energy can be utilized through deferable (time-independent) and non-deferable (time-dependent) strategies. Both utilization strategies are dependent on the type of application or applications chosen through demand-side management. Carbon emission reduction takes place through the reduction of diesel consumption due to the utilization of waste heat for applications previously served by diesel generators. Design novelties are presented using the concept of rock bed TES within a microgrid setup. Full article