Renewable Microgrid Research Articles

Real-Time Machine Learning-based fault Detection, Classification, and locating in large scale solar Energy-Based Systems: Digital twin simulation

The current study considers numerous renewable energy resources, distributed power generation units, energy storage, and plug-in hybrid electric vehicles (PHEV) in order to propose a reliable large-scale energy management framework that can be applied to islanded and grid-connected operations of renewable hybrid AC-DC microgrids (MGs). The framework uses a bat optimization algorithm (BOA) for minimizing the operating costs of the network and in addition introduces an intrusion detection system (IDS) according to the sequential hypothesis testing (SHT) method for detecting identity-enabled cyber-attacks (i.e classification of Sybil attacks, masquerading attacks) on the wireless-enabled advanced metering infrastructures (AMI). The suggested IDS uses the received signal strength (RSS) amount for distinguishing various signal resources and detecting cyberattacks. An IEEE 33-bus testing system has been used to construct a real-time hybrid MG in order to determine the reliability and efficiency of the suggested framework.

Frequency Control of Electric Vehicles Integrated Isolated Renewable Microgrid Using a Magnetotactic Bacteria Optimized Cascade Controller

Cascade controllers improve the frequency profiles of the microgrids during power fluctuations. In this paper, a proportional–integral-proportional-derivative (PI-PD) cascade controller is applied to minimize the frequency disturbances of a fully renewable microgrid with electric vehicles. The superiorities of the PI-PD controller are tested at different operating conditions of generation, demand, and comparisons are made with a classical controller. The test system is completely incorporated with biodiesel, biogas, and solar renewable units. In such a completely renewable environment, power balancing is a difficult task. Therefore, the effect of storage units and electric vehicles is also investigated to mitigate active power imbalances. Furthermore, the optimal power generation concept is incorporated with variable participation factors of biodiesel and biogas plants which improves the load frequency control objectives of the isolated microgrid. For all the simulation case studies, the controller’s gains are identified by using a magnetotactic bacteria optimizer using the MATLAB-SIMULINK platform.

Energy management and operational planning of renewable energy resources-based microgrid with energy saving

• Proposing an environmental/economic model for optimal energy management. • Considering renewable energy resources in the presence of Photovoltaic and battery. • Presenting Hybrid Whale and Pattern Search Algorithm for optimizing Micro-grid. • Reporting superior solutions in Short-Term Scheduling and Micro-grid Energy Management. Energy resource scheduling is one of the major problems in power systems. This issue has become even more significant as renewable sources with intermittent power output are becoming more and more prevalent. Due to their low environmental impact and low operating costs, renewable energy sources (RESs) have attracted interest. The excess power generated by such generation methods may be a negative that affects power systems, hence issues relating to such systems should be properly handled. The optimal operation of a microgrid (MG) with several distributed generation (DG) units and uncertain behavior of RESs is suggested in this research using a stochastic optimization approach. So, for an MG fitted with a solar photovoltaic (PV) unit, this research proposes a day-ahead scheduling paradigm. In this regard, the effects of various climatic circumstances on the power production of the PV unit and the optimal scheduling of the MG have been examined in this research. In order to achieve this, statistics on solar irradiance were extracted from four distinct days from each of the four seasons. The single-objective optimization framework used to design the scheduling problem states that the objective function should be to minimize the total operating cost across the scheduling period. The aforementioned day-ahead scheduling problem can be solved by the "hybrid whale optimization algorithm and pattern search (HWOA-PS)” optimization algorithm, while both renewable and nonrenewable generating units, as well as an energy storage system are present. In order to confirm the higher performance of the recommended approach, a thorough comparison between the Hybrid WOA-PS algorithm and a few well-known optimization algorithms has also been conducted.

Preserving Privacy in Nested Peer-to-Peer Energy Trading in Networked Microgrids Considering Incomplete Rationality

With the high penetration of renewable energy resources, energy prosumers and microgrids can trade energy directly with each other in a hierarchical way. This paper develops a nested market clearing algorithm that alternately produces optimal trading results in both inter- and intra-microgrid markets. The inter-microgrid market refers to the energy exchange among microgrids in distribution network. The intra-microgrid market is the energy sharing among prosumers inside microgrids. We use a distributionally robust optimization approach that is based on prospect theory (PT) to account for the complexity of prosumers’ behavior. The prosumers’ irrational behavior refers to the incomplete rationality in the market. The objective uncertainty and risk preference inside microgrids are modeled uniformly, based on which the alternating direction multiplier method (ADMM) algorithm is employed to solve this problem while preserving privacy. By filtering the marginal energy prosumers in each microgrid, the privacy of microgrids in the inter-microgrid market is preserved as well. Moreover, we prove that the proposed nested market clearing algorithm can reach the global Nash equilibrium. Numerical simulations demonstrate that the condensed equilibrium representation (CER) successfully selects energy prosumers from an intra-microgrid market to participate in an inter-microgrid market. The impact of risk preference parameters on the total utility is also analyzed.

Modeling and optimization of micro grid supply and demand system for renewable thermal energy

The economic benefit of microgrid is the key factor to realize environment-friendly power supply. With the wide application of new energy power generation, scholars have carried out a lot of research on microgrid models, but the existing models cannot reflect the important role of renewable energy in microgrid operation. Therefore, the author proposes a power generation and storage model based on renewable heat energy and microgrid. In order to minimize the cost and meet the requirements of CO2 emission limitation, the cost of power generation, storage and production in the microgrid is analyzed in detail. At the same time, the optimization method of renewable energy microgrid system operation is also studied. First of all, by analyzing the characteristics of the microgrid system, a mathematical model and simulation calculation system are established to help understand the microgrid system. Secondly, the author has carried out a separate study on the energy storage in the microgrid system, and listed the benefits and costs of the energy storage process. In the grid-connected state, the performance of each unit in the microgrid system is better, the system is more stable and safe, and the operating cost is reduced again..

Synergies between DC microgrids and hydrogen - 100% renewable hydrogen microgrids to help achieve decarbonisation

Synergies between DC microgrids and hydrogen - 100% renewable hydrogen microgrids to help achieve decarbonisation

Impact Assessment on Kenyan Minimum Energy Performance Standards and Energy Labels for Cold Chain Appliances

In addressing climate change and meeting countries National Determined Contribution (NDC) and national cooling action plan (NCAP) on energy ambitious targets in the year 2030, Kenya made several strides in drafting the appliances energy performance and labelling regulations of 2016. Energy efficiency enables distributed off-grid renewable energy systems, from solar home systems to renewable micro-grids, to deliver energy services that otherwise might be economically or technically infeasible in resource-constrained settings. This paper reviews specific multivariate econometric models over the period of 2016 to 2022 and summarizes the impact of minimum energy performance (MEPs) and the energy labels policies and regulations enacted. This paper assesses the energy efficiency label for cold chain appliances and identifies issues, potential improvements, and challenges for successfully nudging consumers towards highly energy efficiency cold chain appliances.

Energy Management for Renewable Microgrid Cooperation: Theory and Algorithm

In the microgird (MG) system, cooperation of microgrids is a very essential issue. Hence, multi-microgrid (MMG) system has been proposed to allocate the energy and information exchange for each MG. However, the uncertainties of generations and loads are very difficult to deal with when considering the utilization of renewable energy (RE) resources. To tackle this issue, we study the optimal energy management for the cooperation of multiple MGs in this work. We propose an adaptive energy scheduling algorithm for MMG systems in order to reduce the long-term time-averaged operation cost under the constraints of renewable energy resource utilization. To deal with the unused renewable energy, virtual queues are constructed and Lyapunov framework are adopted to improvement of reliability, reduction of end-user power loss, and cultivation of renewable resource penetration. The simulation results show that the proposed algorithm is effective in coordinating multiple MGs within an MMG system so as to reduce the operation cost and improve the utilization of RE resources dramatically.

A MODEL TO ASSESS THE ECONOMIC VIABILITY OF RENEWABLE ENERGY MICROGRIDS: A CASE STUDY OF IMUFU NIGERIA

This paper explores the economic viability of renewable energy microgrids in remote regions, focusing on their potential to provide reliable and sustainable energy solutions. Renewable energy microgrids, which integrate sources such as solar and wind power with advanced energy storage, offer a promising alternative to traditional energy systems, particularly for regions that lack access to conventional power grids. Remote regions often face significant challenges in accessing reliable and affordable energy. The dependence on diesel generators leads to high operational costs and environmental concerns. Renewable energy microgrids present an innovative solution to these issues by harnessing locally available renewable resources, reducing greenhouse gas emissions, and providing consistent energy supply. The assessment involves analyzing initial capital investment and operational costs, comparing the economic performance of renewable microgrids against conventional energy systems, evaluating environmental and social benefits, and reviewing government policies, incentives, and regulatory frameworks that impact the deployment of microgrids. Data is gathered from case studies, existing projects, academic research, and industry reports to develop economic models and scenarios for analysis. While the initial setup cost for renewable microgrids is relatively high, advancements in technology and increased production scale are driving costs down. Significant savings are achieved over time through reduced fuel and maintenance expenses compared to diesel generators. Microgrids can achieve a favorable return on investment (ROI) within 5-10 years, contingent upon local conditions and system scale. Adoption of renewable microgrids leads to substantial reductions in greenhouse gas emissions, supporting global climate goals. Improved energy reliability enhances the quality of life, supports economic development, and promotes social welfare in remote communities. Effective policies, subsidies, and incentives are crucial for reducing financial barriers and encouraging investment in renewable microgrids. Establishing clear and supportive regulatory environments is essential for the successful integration and scalability of microgrid systems. Despite the promising outlook, several challenges remain. The significant upfront investment required for microgrid infrastructure is a major hurdle. The lack of technical skills for installation, operation, and maintenance in remote regions can hinder successful deployment. Additionally, variability in local renewable resources like solar and wind can affect the reliability and performance of microgrids. To overcome these challenges, it is recommended to focus on reducing costs through technological advancements and enhancing local capacity through training and education. Developing policies and incentives that support renewable energy projects and reduce financial barriers is also essential. Engaging local communities in the planning and implementation process ensures the systems meet their needs and gain local support. Renewable energy microgrids are economically viable and environmentally sustainable solutions for providing reliable energy in remote regions. Despite initial cost challenges, the long-term benefits, including operational savings, emission reductions, and enhanced energy access, make them a compelling option. With strategic investments, supportive policies, and community involvement, renewable microgrids can significantly transform energy access and drive sustainable development in remote areas. Keywords: Economic Viability, Microgrinds, Sustainability, Energy, Nigeria.

Improved Whale Optimization Algorithm for Solving Microgrid Operations Planning Problems

Microgrid operations planning is one of the keys to ensuring the safe and efficient outputs of distributed energy resources (DERs) and the stable operation of a power system in a microgrid (MG). In this study, for the symmetry in renewable energy and microgrid systems, and coordinated control based on a storage battery system, an MG dispatching model with DER conditions and integrated costs is established in grid-connected mode, on the basis of MG operation costs, interaction costs, and pollutant emissions costs. Moreover, an optimization objective for minimizing integrated costs is established. Therefore, based on the original whale optimization algorithm (WOA), an improved whale optimization algorithm (IWOA) with adaptive weight strategy and Levy flight trajectory is proposed in this paper, to solve the optimal operations planning problem of MGs. Finally, in computing comparisons with methods such as the genetic algorithm (GA), particle swarm algorithm (PSO), WOA, wild horse optimizer (WHO), and enhanced whale optimization algorithm (EWOA), the results show that the IWOA computation had lower integrated costs and higher operational efficiency. Moreover, it is verified that the IWOA performed better in solving the MG operations planning problem.

Electrificación por microrredes en zonas rurales de la provincia del Azuay, Ecuador

The electrification of rural areas is an increasingly relevant issue, since in some cases they do not have access to the traditional electricity grid. For this reason, the use of renewable energy microgrids applied to these areas is being studied. It is important to consider the available energy resource in order to adequately size the microgrid system, since certain systems may not be viable. In this study, two renewable energy generation microgrid systems are proposed: the first is a wind/photovoltaic system that works with the indirect radiation of the sun [kWh/m^2/day] and the average wind speed [m/s]; the second is a purely photovoltaic system that uses the indirect radiation and the temperature of the sun, both systems are isolated and have an energy storage system (battery bank), also have as load a rural residential consumer of 160 kWh/month. The systems are simulated and modeled in HOMER Pro software. The results indicate that the photovoltaic microgrid system is the most viable, since the site has low wind speeds and therefore a wind system is not viable.

Implementation and reliability analysis of a new transformerless high‐gain DC‐DC converter for renewable energy applications

AbstractIn this paper, a new high‐gain quadratic boost DC‐DC converter is proposed for a DC microgrid. The converter has a voltage multiplier cell made up of switched inductors to obtain a high voltage at the output. It has a common ground and continuous input current, which makes the converter feasible for renewable energy and DC microgrid applications. The proposed topology consists of a single switch which makes the control simple. The converter achieves a gain of four times the traditional quadratic boost converter and can also operate in continuous and discontinuous conduction modes. The voltage stress across the switch and all the other passive components is less than the output voltage. The variation of voltage gain in the case of parasitic resistances is also shown. The reliability analysis of the proposed converter using Markov modeling is also presented by considering both open‐circuit and short‐circuit faults across the semiconductor devices. A 200 W prototype of the converter is also prepared and the hardware results of the converter are also presented in the paper. The converter operates at high efficiency of 96% at 100 W output power operation. The variation of reliability with different converter parameters like the duty cycle and the input voltage is also discussed in the paper. The experimental results in fault conditions are also shown.

Grid Connected Microgrid Optimization and Control for a Coastal Island in the Indian Ocean

For the suggested site in the Maldives, this research paper analyzes the possibility of a hybrid renewable microgrid that is dispatch strategy-governed in both off-grid and on-grid scenarios. The planned microgrid’s techno-environmental-economic-power-system responses have been assessed. Both the power system response study and the techno-environmental-economic study of the modelled microgrid were carried out using the software platforms DIgSILENT PowerFactory and HOMER Pro respectively. Cycle charging (CC) dispatch technique had the lowest performance for both on and off-grid modes, according to the research, with cost of energy (COE) of 0.135 and 0.213 dollars per kWh, and net present costs (NPC) of 132,906 and 147,058 dollars respectively. With an NPC of 113,137 dollars and a COE of 0.166 dollars/kWh, the generator order strategy operates optimally while in on-grid mode. On the other hand, load following operates at its finest in off-grid mode, with a COE of 0.024 dollars/kWh and a NPC of 141,448 dollars. The microgrid’s reactive power, different bus voltages and frequency responses demonstrate how the proposed system, which employs the dispatch approach, voltage Q droop, and input mode PQ controller, operates steadily. For the purpose of illustrating the importance of the research effort, a comparison section between the planned HOMER optimizer and other optimization approaches is also included. The research was done with the Maldives in mind, but it offers a general notion for setting up a microgrid anyplace in the world with comparable weather and load circumstances. The research was done with the Maldives in mind, but it offers a general notion for setting up a microgrid anyplace in the world with comparable weather and load circumstances.

Two-level optimal scheduling method for a renewable microgrid considering charging performances of heat pump with thermal storages

Combining compression heat pump with thermal energy storage (HPTES) allows the shifting of heat demand to off peak periods or periods with surplus renewable electricity. However, it is not clear that how the charging performances (efficiency, charging time and supply water temperature) of HPTES affect the optimal coordinated scheduling of a renewable microgrid. In this study, we proposed a two-level scheduling optimization method for a renewable grid-connected microgrid considering charging performances of heat pump with thermal storages. This method is based on an integrated nonlinear dynamic model of a renewable microgrid including photovoltaic/wind power generator, buildings and HPTES; and the time lag in energy conversion and transport process was considered. Level I in this method is for the scheduling optimization of HPTES, three different model-based dynamic optimal control strategies were developed for the charging process of HPTES to supply domestic hot water and floor radiant heating in buildings. It's found that coefficient of performance (COP) of HPTES during charging varies with the charging time and the supply water temperature. Thus at the level II, a half-hourly time interval was proposed for the optimal scheduling of microgrid, through which a hybrid charging time scheduling can be applied to the optimal control of HPTES for different supply water temperatures. Based on the microgrid model integrating different optimal control strategies of HPTES, different dynamic optimal coordinated scheduling were developed for the microgrid in three scenarios. It can be found that the charging performances of HPTES affect the optimal coordinated scheduling of heat supplies from heat pump and TES in a microgrid significantly, and heat production rates vary with time differently under different operation scheduling of a microgrid. The proposed optimal half-hourly scheduling method with hybrid charging time of HPTES leads to the reduction of the overall operating cost including the penalty cost for the microgrid, and the increase of domestic hot water temperature up to the required value. This study would be useful for the optimal scheduling of a renewable microgrid containing HPTES at a low cost in practice.

Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China

This paper proposes an optimal sizing design and cost-benefit evaluation framework for stand-alone renewable microgrid system to serve rural community load usage in Northeast China. The microgrid system combines Photovoltaic arrays (PV), Wind turbines (WT), Tidal turbines (Tid), Battery (Bat) storage and hydrogen storage, respectively. The optimal component sizing is determined based on the actual local hourly meteorological data and load demand during a year using Chameleon swarm algorithm (CSA), with minimum Total net present cost (TNPC) of the microgrid system as the optimization objective and the reliability constraint is considered as Loss of power supply probability (LPSP). Meanwhile, a cost-benefit index is further introduced for conveniently evaluating the overall effectiveness of the microgrid systems. The results of the simulation experiments under the benchmark scenario reveal that the PV/WT/Tid/Bat system is the most viable approach for local load supply among different versions of the microgrid. Additionally, a thorough sensitivity investigation of the optimal sizing of two exemplary microgrid systems based on different energy storage is carried out under different techno-economic scenarios. This study can provide a more efficient and clean electrification scheme and insightful reference for investment in the power-starved Northeast China.

Survey on microgrids frequency regulation: Modeling and control systems

• A comprehensive review of load frequency control in microgrids. • Classification of various microgrid components, models, and benchmarks. • Survey on the merits and drawbacks of model-based and model-free control strategies. • Highlight of future trends for frequency deviation in the presence of renewable energy resources. The traditional power system structure is constantly changing due to the application of renewable energy sources (RESs) and microgrids (MGs) into the power system network. Due to the variations in demand and renewable generation profiles, load frequency control (LFC) is one of the most important issues in MGs. As a consequence of the relatively low inertia of these systems, LFC is more challenging compared to absence of DERs and MGs. A comprehensive review of the LFC problem in MGs is the primary objective of this paper. The review process for this paper is undertaken from two perspectives. As a first step, different models for MG components and benchmarks for LFC studies have been described, which can ease the researchers' task of finding suitable models. The second step of this review is a discussion of various control strategies, considering the merits and limitations of each. It is helpful to researchers that this comprehensive literature review gives them an overview of previous well-researched papers in this respect and enables them to connect the dots between recent developments, challenges, and future trends in load frequency strategies for MGs.

Fuzzy logic-based energy management system for grid-connected residential DC microgrids with multi-stack fuel cell systems: A multi-objective approach

Hybrid energy storage systems (HESS) are considered for use in renewable residential DC microgrids. This architecture is shown as a technically feasible solution to deal with the stochasticity of renewable energy sources, however, the complexity of its design and management increases inexorably. To address this problem, this paper proposes a fuzzy logic-based energy management system (EMS) for use in grid-connected residential DC microgrids with HESS. It is a hydrogen-based HESS, composed of batteries and multi-stack fuel cell system. The proposed EMS is based on a multivariable and multistage fuzzy logic controller, specially designed to cope with a multi-objective problem whose solution increases the microgrid performance in terms of efficiency, operating costs, and lifespan of the HESS. The proposed EMS considers the power balance in the microgrid and its prediction, the performance and degradation of its subsystems, as well as the main electricity grid costs. This article assesses the performance of the developed EMS with respect to three reference EMSs present in the literature: the widely used dual-band hysteresis and two based on multi-objective model predictive control. Simulation results show an increase in the performance of the microgrid from a technical and economic point of view.

Design and Implementation of an 18-kW 500-kHz 98.8% Efficiency High-Density Battery Charger With Partial Power Processing

The demand for high-density, high-efficiency bidirectional battery chargers is driven by the fast development of energy storage system in renewable energy system, microgrid, and transportation electrification. Isolated dc–dc converter that interfaces a battery with a variable voltage range is one of the critical components. Input-parallel output-series (IPOS) partial power (PP) converter is considered a promising high-efficiency, high-density solution because only a fraction of power is processed via multistage converters to regulate the output voltage. However, due to the tight coupling between two dc transformers (DCXs), the design of PP converter is complicated. To solve this issue, an overall design procedure for a bidirectional soft-switching resonant-type PP converter is proposed. In the parameters design part, a decoupled design method is proposed to simplify the DCXs design. With this method, two DCXs can be designed separately, and a typical optimization method can be easily applied. As for the hardware design part, to minimize the ac loop inductance and resistance, a two-direction (2-D) flux cancellation method and an “intraleaving” winding structure are proposed for circuit layout and high-frequency (HF) transformer to obtain high operation efficiency and power density. Finally, the whole design procedure is verified by an 18-kW-rated, 25-kW peak, prototype operating at 500 kHz. The realized PP converter features a peak efficiency of 98. 8% and a power density of 142 W/in3. This article is accompanied by two videos demonstrating the dynamic voltage regulation test and the efficiency measurement.

Environmental assessment of optimized renewable energy-based microgrids integrated desalination plant: considering human health, ecosystem quality, climate change, and resources.

Using hybrid renewable energy technology is an efficient method for greenhouse gas mitigation caused by fossil fuel combustion. However, these renewable microgrids are not free from environmental damages, especially during the lifetime of hybrid renewable energy systems (HRES). The main objective of this study is to assess the environmental impacts of three optimized HRES for the Sea Water Reverse Osmosis Desalination (SWROD) plant. An objective optimization was developed using the division algorithm, and the environmental impacts of the optimized HRES were investigated by the life cycle assessment approach. The results showed that producing 1m3 freshwater by an optimal size SWROD integrated with wind turbine/battery is responsible for 3.56E - 07 disability-adjusted life year (DALY). It is significantly less than 1m3 freshwater production by an optimal size SWROD integrated with solar PV/battery (5.88E - 07 DALY) and solar PV/wind turbine/battery (5.13E - 07 DALY) energy systems. Moreover, 1m3 freshwater by a SWROD integrated with proposed microgrids in this study led to a damage of 0.089 to 0.193 potentially disappeared fraction of species (PDF)*m2*yr to ecosystem quality. It also results in an emission of 0.143 to 0.339kg CO2 eq per 1m3 freshwater. Furthermore, resources for 1m3 freshwater production by a SWROD are calculated at 2.77 to 4.806MJ primary. Freshwater production by an optimal size SWROD integrated with solar wind/battery compared with solar PV/battery and solar PV/wind turbine/battery had less damage to ecosystem quality, climate, and resources. The results showed reductions of 91.23% in human health, 73.51% in an ecosystem quality, 92.43% in climate change, and 90.08% in resources for producing 1m3 of freshwater using SWROD integrated with wind turbine/battery bank compared to fossil-based desalination. Finally, the result showed that solving the optimization problem using the division algorithm compared to other algorithms leads to less environmental damage in freshwater production.

Effect of the meta parameters on a model predictive algorithm for renewable micro-grid optimal control

Renewable energy micro-grids are often coupled with energy storage systems to balance the production variations. A common way to control such micro-grids is the Model Predictive Control (MPC) strategy that optimizes the grid behavior at a given time-step for a rolling horizon. This computation is refreshed periodically so that the algorithm can work with up-to-date measurements. This paper focuses on how the time-step, the horizon and the refresh period affect the optimal solution. The MPC algorithm is made up of a Linear Programming optimizer and an Auto Regressive Moving Average forecast. It is applied to a micro-grid with a PV array and a Battery storage that has to supply a residential complex and is able to trade energy with the main grid. Several configurations (equipment size, load profile, cost profile) are studied to ensure the results’ robustness. The MPC can reduce the energy exchange cost and can almost reach the optimal solution in most of the cases. The results show that an optimization with a time-step of 30 min and a 12-h horizon gives good performances. However, the refresh should happen at least 4 h before reaching the optimization horizon.