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Renewable energy is a promising solution to combat the scarcity of electricity, particularly in isolated and rural areas. Microgrids (MG) can be employed for installing systems with different energy sources, such as renewable energy components and conventional energy sources like utility grids or grid-connected inverter systems. The amount of energy produced by renewable sources depends on their location, which has implications for energy production. This research aims to explore MG and their challenges for efficient operation. The study discusses various AI models used by researchers to mitigate problems associated with MG planning. Additionally, the paper presents a case study based on the most beneficial ML tool like clustering to gain insights into an existing MG system. The paper also delves into the issues related to PV, a connected distributed energy resource (DER), such as forecasting, and predictive management to reduce maintenance costs, and how AI tools can address them. Furthermore, forecasting methods such as LSTM and GRU models are discussed because of the stochastic nature of PV production. [ABSTRACT FROM AUTHOR]

Optimising energy use in systems and buildings is crucial to reduce climate change. This paper aims to address the gap in knowledge for pico-hydropower (

This paper presents a simulation of an insulated micro-grid system based on the three-level converters control for energy management. Different renewable power sources (wind turbine and Photovoltaic (PV) energy systems) are used to energize the micro-grid. However, a battery energy storage system (BESS) and a variable diesel generator are also used to improve the reliability of the system. The contribution of this research is focused on the power control method based on improving the quality of energy transfer, mastering dynamic interactions and maximum energy production from renewable energies to reduce the fuel consumption by the diesel. Firstly, the proposed control model for each renewable energy was carried out through simulation in the environments of Matlab and Simulink to test the robustness and performance. The second part of this research is dedicated to managing the sharing of power between load, generators, and storage systems by extracting the references of power. The three-level PWM rectifiers for variable speed diesel generators was used to maintain and control the DC bus voltage of the isolated micro-grid. The results obtained from simulations show a good correlation between static and dynamic systems even for fluctuating sun power and wind speed. [ABSTRACT FROM AUTHOR]

Solar grid systems are widely used especially in remote locations where electricity accessibility from the grid is limited. The major issue frequently encountered in microgrid-connected photovoltaic (PV) systems are voltage overshoots, transient response and steady state errors causing instability of microgrid during unsymmetrical temporary faults in the distribution network and damages the sensitive loads. PV-grid solely depends on solar hours per day and is not reliable at location with variable weather conditions. Therefore, the generated power per day is reduced as per daily demand and would create power quality issues in a distribution line. Additionally, the PV-grid system exposed to weather experiences unsymmetrical faults due to severe weather conditions that affects the reliability of the grid and electricity supplies. This study presents a technique to enhance the stability of microgrid by using dynamic voltage restorer in a three-phase grid connected system to mitigate power quality issues arising from PV-grid side in a harsh weather condition. The most significant extreme weather conditions such as thunderstorms and high winds are potential causes affecting the instability of transmission network by generating faults such as double line-to-ground, single line-to-ground, lightning strike or impulse transients, and power outage in a distribution line. The proposed technique enhances the transient stability of microgrid and provides symmetrical operating conditions for the load. The control mechanism extracts the fault signal and stabilize the error signal. In the proposed configuration, hysteresis-band PWM generator drives the inverter with the PV based battery storage system connected at DC-Link. The simulation results are verified by using IEEE519 standards limits in four case studies to mitigate power quality issues arising due to severe weather conditions by injecting compensating voltage to protect load and act as microgrid in case of power outage.

In renewable energy micro-source applications, a wide range of voltage conversion of the step-up converter is an essential part to equalize the typical low voltage of micro-source with DC-bus voltage of Inverter or motor drives. In order to meet this purpose, an ultra-voltage gain step-up DC-DC converter is proposed in this paper. The proposed converter has made an arrangement of the regenerative-boost fed switched inductor and capacitor configurations. Thereby, due to such an organization of structure, the proposed converter can develop an extremely high voltage-gain even at lower duty ratios. In addition, it has the advantage of lower switching stress across all power semi-conductive diodes. Furthermore, this paper describes the steady-state analysis and comparative features of the converter with existing recent literature. Finally, to validate theoretical analysis and test the feasibility and suitability of the proposed ultra-gain converter, the experimental results were observed by a 500 W fabricated prototype. [ABSTRACT FROM AUTHOR]

Combined cooling, heating, and power system has been widely applied in the micro-grid system. However, the micro-grid system reliability and safety may be adversely affected when renewable energy resources are connected to the grid. This has made the power distribution system more challenging to manage for grid operators. The proposed energy optimization management model aims to maintain a stable and reasonable power grid distribution due to biogas power, photovoltaic power, and micro gas turbine involvement to realize better utilization. For this reason, the improved chameleon swarm algorithm is developed to solve the optimal operation cost of the system by integrating different improvement strategies. Therefore, the operation strategy can achieve both economic and environmental costs more effectively. It is verified by the objective function constructed by the economic cost, environmental cost, and renewable energy utilization. Based on the specific arithmetic analysis, the use of the strategy proposed in this study can reduce the economic cost by 1.67% in summer, 6.89% in winter, and 3.42% in transition season compared to the traditional strategy, which confirms the operational cost-effectiveness of the combined cooling, heating, and power micro-grid system in different scenarios. [ABSTRACT FROM AUTHOR]

Optimization of the stand‐alone micro‐grid is needed to minimize energy generation cost and environmental impacts. Protect the environment and saving cost can be obtained by choosing renewable energy sources as the power generation, such as photovoltaic (PV) and wind turbine. In this paper, authors investigate the hybridization utility and size optimization of a stand‐alone micro‐grid using the genetic algorithm. The considered micro‐grid consists on PV generator, wind turbines and storage batteries. This study is based on a bi‐objective optimization process. The life cycle cost (LCC) and the loss of power supply probability are respectively the economic criterion and the system reliability criterion under constraints. The energy modeling of the system's components enables energy flows simulation and further objective functions evaluation. The meteorological data of the location situated in Tunisia are considered. In order to study the resources randomness impact on systems optimal design, the data relating to December and August are used as references respectively to winter and summer. According to hybridization study, the hybrid PV/wind/battery system is the most appropriate system configuration for the studied location for both seasons compared to PV/battery or wind/battery. Results showed the significant influence of the battery bank design on the systems reliability and LCC. [ABSTRACT FROM AUTHOR]

Our objective through this work is to have a cogeneration system integrated into a hybrid production system, coupled to the public grid and equipped with an ecological production system (photovoltaic) with a storage system (accumulator), and to establish rules and tools for optimizing energy management as well as the dimensioning of an energy system. The optimizations will be carried out on the basis of consumption and production data. The optimization criterion will be economic with a view to minimizing the total cost of the system to meet the energy demand of a typical profile during a basic test period. However, "optimal" sizing requires coordination with effective energy management to identify the optimum power references, the minimum and maximum powers provided by each source and to estimate the depth of discharge of the storage element. The parts presented concern the dimensioning and management of energy transfers on the basis of consumption data and tariffs are: - Establishing reliable and adapted electrical models of the subsystems. In order to be able to determine, at each moment, for a given consumption and a given deposit, the power that the production systems can provide. These models must be sufficiently accurate to account for energy transfers and fast enough to allow calculations over long periods of time. - Establish economic models of the different modules of the system. Climate deposits, consumption profiles, fuel consumption, energy efficiency of the systems. - Finally, carry out economic and energy optimization studies of the energy system using microgrid management algorithms based on different configurations of the system. [ABSTRACT FROM AUTHOR]

Even though solar power generation has become an emerging trend in the world, its penetration into the utility grid as a distributed generation source is not a satisfactory measure due to the inherent issues related to solar photovoltaic systems (SPVSs). In addressing these issues, microgrids have been identified as suitable integrating platforms for distributed, clean energy resources such as SPV. Different SPV and microgrid architectures are available for different applications depending on the resource availability and controllability. Reconfigurability is a concept that makes a system adaptable to two or more different environments by effectively utilizing the available resources. The review explains the applications of reconfigurable approaches on solar PV systems such as reconfigurable PV arrays, power conditioning unit (DC/DC converter, DC/AC inverter), microgrid controller and topology of distribution network with relevant studies. An analysis is also presented considering the unique features of reconfigurable systems in comparison to the static systems.

Currently, many remote communities rely on costly diesel engine (DE) generators as their only energy resource. Therefore, to reduce cost and CO2 emissions, renewable energy such as photovoltaic (PV) power is widely used. However, such integration may have reliability issues due to intermittency and uncertainty of PV power. Hence, energy storage is further implemented to compensate for the variability of PV output. As a result, the critical problem is to find an optimized PV-storage control strategy and capacity considering the techno-economic aspects, cost, and reliability. Previous research has not provided convincing results due to the little attention paid to the practical operational constraints of existing DEs (time delay management, spinning reserve strategies, ramp rate, etc.), and rough hourly usage data in a time-series model. Besides, no applicable systematic evaluation method has been established. This paper develops a new model which fully considers the DE generator's operational characteristics. Furthermore, based on the recorded 1-min load and PV generation data in a real microgrid, a systematic evaluation method is proposed, which searches for the best results for both control strategies and capacities of all components. This method can be utilized for the integration of high renewable (PV) penetration into existing DE powered remote networks. [ABSTRACT FROM AUTHOR]

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This study focuses on the sizing and optimization of a micro-grid with storage, which is destined to supply the load of an economic activity zone (EAZ) in Sidi Bouzid, Tunisia. To solve this problem, a genetic algorithm is established and programmed into MATLAB. The objective functions are considered by providing three minimums, namely Greenhouse Gas emissions (GHG), Life Cycle Cost (LCC) and Embodied Energy (EE), for three values of loss of power supply probability (LPSP) previously fixed. The sizing and optimization results are found and evaluated using a time series exchange of energy during a year to determine the optimal component size of a photovoltaic/wind/battery system (PV/WT/Bat). The simulation results show that the lowest ratio of LPSP values corresponds to the higher GHG, EE, LCC, photovoltaic panels area (APV), battery storage capacity (Cn), wind turbines area (AWT) and vice versa. This means that demanding higher energy reliability leads to higher energy cost and pollution. A comparative analysis was made, showing the cons and pros of each LPSP value in order to allow the owner of the plant to choose the most suitable PV/WT/Bat configuration.

The optimal operation of micro-grids has attracted the attention of many developed societies considering different objectives, such as the operational cost, pollution rate, and the increasingly extensive use of renewable energy resources in this field. The aggregation of these mostly contradictory goals in an optimization problem can provide an appropriate response for the users of these systems. In this study, in order to manage energy in systems with various micro-grids that differ in quality, we aim to apply the multi-objective particle swarm optimization method to obtain the optimal distribution of energy resources in a sample micro-grid, while simultaneously satisfying economic and pollution related operational objectives. [ABSTRACT FROM AUTHOR]

Energy access remains a challenge for many countries, as recognized by sustainable development goal 7 of the United Nations Development Programme. Although the Myanmar government has set a target of 100% electrification by 2030, less than half of the households are currently connected to the national grid. To expedite electrification, decentralized approaches should be considered. Mini-grids are an effective alternative that can fill the gap between a solar home system and the national grid; however, many of the existing mini-grids in Myanmar are powered by diesel generators. Diesel fuel is significantly more expensive in rural areas than in urban areas due to high transportation costs. Although mini-grids powered by solar photovoltaics and batteries are cost-competitive with diesel generators, the deployment of renewable energy-based mini-grids is slow. In this study, we analyzed the barriers to mini-grid deployment and prioritized the barriers. We conducted a questionnaire survey with stakeholders using the analytic hierarchy process to identify the prioritization of each barrier factor. The K-means clustering method was used to determine tendencies and showed that there was no single, dominant solution. Our results confirm the difficulty of mini-grid deployment and suggest multi-pronged approaches that go beyond economic considerations.

Integration of different energy networks will increase additional flexibility to system operation. The key component in such a coupled infrastructure is the energy router, which plays an important role in energy transition and storage to smoothing the prediction error both in renewables and load. The router has the multi-carrier energy generation capability, and builds physical linkages among the power network, heat network, and other networks in the micro energy internet. The economic dispatch problem of the micro energy internet is formulated as a bi-objective optimization problem. Golden section search method is adopted to locate a compromising solution in the sense of Nash Bargaining. Case studies on a typical test system verify the effectiveness of the proposed bi-objective dispatch model and solution method. [ABSTRACT FROM AUTHOR]

This manuscript discuss about the various DC-DC converter configurations with high voltage conversion ratio utilized in DC micro-grid structures. The presented DC-DC converter topologies play a major role globally in the power generation sector including micro-grid, because of its decreased number of semiconductor devices, maximum conversion efficiency, small in size and cost of manufacturing is less. In this manuscript the DC-DC converter are categorized in to isolated and Non-isolated topologies. The first group topography works with the presence of transformer and the second group works without the transformer. These converters are capable to provide the various stages of output range. Researchers utilize these converters in the area of renewable energy generation, electric vehicle, micro sources, charge pumping applications etc. Hence they also work to improve the efficiency and reliability with reduction in components numbers and economical aspect. In this manuscript, the various topography of DC-DC converter topologies utilized in micro-grid are reviewed and comparison is made based on voltage conversion ratio, duty ratio, efficiency along with the basic operating principle. This review also reveals the research gaps, current trends, and challenges in the last part. [ABSTRACT FROM AUTHOR]

A micro-grid with the capacity for sustainable energy is expected to be a distributed energy system that exhibits quite a small environmental impact. In an independent micro-grid, “green energy,” which is typically thought of as unstable, can be utilized effectively by introducing a battery. In the past study, the production-of-electricity prediction algorithm (PAS) of the solar cell was developed. In PAS, a layered neural network is made to learn based on past weather data and the operation plan of the compound system of a solar cell and other energy systems was examined using this prediction algorithm. In this paper, a dynamic operational scheduling algorithm is developed using a neural network (PAS) and a genetic algorithm (GA) to provide predictions for solar cell power output. We also do a case study analysis in which we use this algorithm to plan the operation of a system that connects nine houses in Sapporo to a micro-grid composed of power equipment and a polycrystalline silicon solar cell. In this work, the relationship between the accuracy of output prediction of the solar cell and the operation plan of the micro-grid was clarified. Moreover, we found that operating the micro-grid according to the plan derived with PAS was far superior, in terms of equipment hours of operation, to that using past average weather data.

• Multi-objective particle swarm optimization was employed on a renewable micro-grid. • Minimum LPSP value was acquired for the micro-gird with CHP, wind and PV systems. • Minimum Cost of Energy was acquired for the micro-gird with CHP and PV systems. • PV system is found to be more efficient for the climate as compared to wind energy. • Increasing the renewable energy incentives could justify the use of wind energy. Global warming and energy security concerns have attracted research efforts toward renewable micro grids. Since micro grids possess multiple energy sources with different availability states and required costs, optimization practices could be helpful in their sizing and scheduling. In this study, multi-objective particle swarm optimization algorithm was employed on three renewable micro grid configurations for Shiraz climate, Iran. The considered micro grid configurations were wind turbine (WT) and combined heat and power (CHP) system, photovoltaic (PV) and CHP and PV, WT and CHP. The micro grid was assumed to be connected to gas and electricity networks and excess produced electricity was considered to be sold to the grid. Loss of power supply probability and the cost of energy per unit were considered as the optimization objective functions. The acquired results revealed that only employing WT could significantly increase the reliance on the power grid due to the low availability of wind energy in the climate. Since the climate possesses high levels of solar insolation, adding a PV system to the configuration significantly decreased the electrical load supplied by the grid. The cost of energy per unit for each scenario was acquired to be 0.266 USD, 0.235 USD, and 0.247 USD. The calculated optimum loss of power supply values were 0.285, 0.3218, and 0.207 for the three scenarios, respectively. While the cost of each energy unit was higher for the third scenario as compared to the second scenario by 5%, the share of demand load supplied by renewable sources increased by 20%. Simultaneous utilization of wind and solar energy was shown to be more beneficial, especially if carbon tax policies or renewable energy incentives were to be considered for future applications. [ABSTRACT FROM AUTHOR]

Micro-grid systems utilizing renewable energy sources (RES) have emerged as a viable technology for addressing the present global climate crisis. Nonetheless, the considerable uncertainty of RES and the climatic variability make it challenging to build a suitable system. To understand the implications of climate on the optimal micro-grid design, we present a techno-economic analysis of 13,488 regions. On the basis of climatic similarities, the locations were divided into nine groups, and the correlations between climates and optimal designs were analyzed. Based on their climate sensitivity and the change trend of two climates, we discovered that they fell into four separate categories. In climate-sensitive places where PV module size increases 6.79 ± 0.13% and wind turbine size increases at the same rate, the overall cost increases 7.6%, which is 2–4 times that of other types. On the other side, climate-insensitive locations with same/opposite tendencies experience the least change in overall micro-grid system size due to climate change. Although total system sizes are most sensitive in climate-sensitive regions with opposing tendencies, their total costs vary the least due to a trade-off between PV module and wind turbine size variations. The analyses reveal the effects of climate on the sizes and costs of micro-grid systems and emphasize the importance of considering climatic fluctuations when designing micro-grid systems. • A micro-grid based on renewable energy is readily influenced by climate variability. • It is necessary to integrate the climatic variability in the design of a micro-grid. • Global analysis of the impact of climatic patterns on economic designs of micro-grids. • Sensitivity analysis of real climate changes to designs of micro-grids. • The strategies for design and operation applicable to real-regions. [ABSTRACT FROM AUTHOR]

Ever-increasing price of conventional energy resources and related environmental concern enforced to explore alternative energy sources. Inherent uncertainty of power generation and demand being strongly influenced by the electricity market has posed severe challenges for DRPs (Demand Response Programs). Definitely, the success of such uncertain energy systems under new market structures is critically decided by the advancement of innovative technical and financial tools. Recent exponential growth of DG (distributed generations) demanded both the grid reliability and financial cost–benefits analysis for deregulated electricity market stakeholders. Based on the SGT (signaling game theory), the paper presents a novel user-aware demand-management approach where the price are colligated with grid condition uncertainties to manage the peak residential loads. The degree of information disturbances are considered as a key factor for evaluating electricity bidding mechanisms in the presence of independent multi-generation resources and price-elastic demand. A correlation between the cost–benefit price and variable reliability of grid is established under uncertain generation and demand conditions. Impacts of the strategies on load shape, benefit of customers and the reduction of energy consumption are inspected and compared with Time-of-Used based DRPs. Simulation results show that the proposed DRP can significantly reduce or even eliminate peak-hour energy consumption, leading to a substantial raise of revenues with 18% increase in the load reduction and a considerable improvement in system reliability is evidenced. [ABSTRACT FROM AUTHOR]

Highlights: [•] An effective operation model is proposed for islanded micro-grids (MGs). [•] A new optimization algorithm is presented to solve MG optimization problem. [•] A new binary handling procedure is proposed for MG unit commitment problem. [•] The proposed approach is extensively compared with 21 recent optimitation methods. [•] The comparisons confirm the validity of the developed approach. [ABSTRACT FROM AUTHOR]