Reliable Electricity Supply Research Articles

Techno-econo-environmental analysis of sustainable hybrid solar-wind-biogas using municipal solid waste-based grid independent power plant with dual mode energy storage strategy

In the contemporary landscape characterized by escalating energy issues and growing worldwide environmental apprehensions, the transition towards sustainable energy assumes a critical role in enhancing the standard of living. Hybrid renewable energy systems (HRES) are increasingly seen as crucial, particularly in off-grid communities, due to their provision of dependable and sustainable electrical alternatives to conventional fossil fuels. This study evaluates the viability of an autonomous system incorporating dual-mode energy storage, as well as explores the possibilities of converting municipal solid waste (MSW) into biogas to achieve both energy and environmental advantages. This research employs NSGA-II in MATLAB environment, optimizing novel HRES for size and performance where the fundamental goals include cost-effectiveness, health hazard mitigation, and ensuring a reliable electrical supply. The findings indicate that the system under investigation exhibits an ideal energy cost of 0.1393$/kWh, carbon emissions amounting to 184283.1 kg CO2-eq/yr, a health impact of 2.56 × 10−1 DALYs, and an ecological damage footprint of 1.45 × 10−7 species⋅year. The system exhibits a job creation rate of 4.22 jobs per megawatt and attains a human development score of 0.404. Through the utilization of renewable energy sources and advanced storage technologies, it is possible to address the challenges posed by energy and environmental problems.

Development of Organic Positive Electrodes for Rechargeable Aqueous Zinc-Ion Batteries for Stationary Energy Storage Systems

The rising concern towards the amount of anthropogenic carbon emissions and their effects on the environment has motivated the transition away from fossil fuels. The implementation of renewable energy sources has promoted the decarbonization of the power sector, but the variability of wind and solar energy necessitates the parallel deployment of high-performance energy storage infrastructure to ensure a reliable on-demand supply of green electricity to the grid. To this end, aqueous rechargeable zinc-ion batteries (ZIBs) are a promising new option for stationary energy storage owing to their high safety and low cost, when compared to established storage technologies like lithium-ion batteries. However, ZIBs are still limited by several technological challenges that hinder their uptake for commercial energy storage installations. In particular, the positive electrode materials, mostly comprised of metal oxides, are restraining the energy density and stability of the batteries and are yet under investigation. Low cost, long cycle life, and natural abundance are required properties of materials used in batteries for stationary energy storage. The search for materials with these properties has motivated the investigation of alternatives to metal oxides. One group of materials attracting considerable research attention is organic compounds which offer advantages like their natural abundance and high theoretical capacities. In this work, we developed an organic positive electrode for ZIBs using carbonyl groups as redox-active centers to provide energy storage capacity at round-trip energy efficiencies that are higher than the conventionally utilized manganese oxide electrodes. Furthermore, we investigated the effects of the conductive carbon additive on the deliverable capacity of the battery and elucidated the charge storage mechanism of this positive electrode material through detailed characterization. The results indicated that both Zn2+ and H+ are involved in the energy storage process of this organic electrode material. In addition to studying the energy storage process, degradation mechanisms were identified through nuclear magnetic resonance (NMR) and mass spectroscopy (MS). Both dissolution of the reduced form of the active material from the electrode and the formation of unwanted decomposition products are important contributors to the capacity fade of the battery. The technological and scientific insights provided in this presentation will thereby contribute towards the development of high-performance and naturally abundant electrode materials for the next generation of ZIBs to enable clean energy grid storage.

Eval_uasi Pemasangan LBSM Loopring untuk Menurunkan SAIDI pada Penyulang PKR 16 dan Riyal di Wilayah Kerja ULP Pulung Kencana

The reliability and continuity of electric power supply are heavily reliant on the maneuverability of existing feeders. To enhance this capability, the installation of LBSM (Load Break Switch Motorized) devices is essential for feeders lacking the ability to maneuver to alternative feeders. This LBSM installation will be implement on the Riyal and PKR 16 feeders at ULP Pulung Kencana. The Riyal feeder receives power from the Mesuji Substation, while the PKR 16 feeder is supplied by the Pakuon Ratu Substation. Both feeders currently lack switches for maneuvering in the event of disturbances or maintenance, which significantly contributes to high SAIDI (System Average Interruption Duration Index) rates. To determine the optimal installation points for the LBSM, a thorough analysis was conducted, prioritizing the closest proximity between the two feeders and incorporating topologic calculations using the Digsilent PowerFactory 15.1 software. This approach ensures optimal performance of the distribution network. The installation of the LBSM loopring is anticipated to significantly improve network maneuverability, thereby reducing the SAIDI rates at ULP Pulung Kencana.

Optimal allocation of wind power hybrid energy storage capacity based on ant colony optimization algorithm

Renewable energy sources, such as wind power, face challenges owing to their erratic construction and intermittent nature, leading to the emergence of energy storage strategies to achieve grid stability and reliable electricity supplies. Determination of the correct size of energy storage devices for wind power plants is complicated. In this study, the ant colony optimization (ACO) algorithm is proposed for the best distribution/sizing of wind-generated hybrid storage capacity. Ants’ foraging habits motivate the development of wind turbines with high dependability, high efficiency and low energy storage costs. A study is conducted to confirm the practicality of the proposed method, using real data from a wind power plant to calculate the contrast between wind energy production and load consumption features, to influence the appropriate quantity for energy storage organization. The study demonstrates that the ACO approach provides precise and efficient solutions for determining the optimal energy distribution in wind power plants.

Augmented Two-Stage Hierarchical Controller for Distributed Power Generation System Powered by Renewable Energy: Development and Performance Analysis

The sustainable development of an area is highly reliant on a reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller’s performance is evaluated in a MATLAB environment, and simulation results show the proposed scheme’s superiority under different operating conditions. The frequency is stable at 50 Hz after a 50 KW load is added.

Enhancing Reliability of Electricity Supply of City Electric Networks Cities

A mathematical model is proposed to increase the reliability of power supply on the basis of reducing the technical cause of damage by the expressed relative probability of a flow of failure depending on power consumption. To test the adequacy of the proposed mathematical model, the data of daily winter and summer power consumption schedules are used to determine the dependence of the relative flow of failure from power consumption during peak hours.

Renewable compensation policies and conventional energy investment: A theoretical model

Many jurisdictions are simultaneously expanding natural gas and renewable capacities, largely supported by renewable compensation policies (RCPs). However, RCPs' impacts on firms' incentives for conventional capacity investment remain unclear. This paper develops a two-stage theoretical model to investigate this interaction within an imperfect competition and uncertain demand context. Firms initially invest in conventional energy capacity, followed by competing to supply electricity from conventional and previously owned renewables. Conventional output is compensated at market prices, but renewable output is subject to two common RCPs: feed-in tariffs (FiT) and feed-in premiums (FiP). The illustrative numerical example shows that increasing the proportion of renewable output compensated by a FiT from 20% to 80% increases the market-level conventional investment by 18%, leading to an increase in consumer surplus but decreasing firms' profits. These results exemplify the unintended effects of RCPs, encouraging the adoption of conventional generation capacity. The model presented in this paper provides a theoretical foundation for understanding the relationship between RCPs and conventional energy capacity investment—critical for carbon-intensive nations transitioning to renewables while maintaining reliable electricity supply through conventional generation.

Renewable energy integration for sustainable cold storage: Designing a solar PV operated thermoelectric cool chamber

Thermoelectric coolers utilizing peltier effect offer a promising solution for cooling applications. This study elaborates the design and optimization of a TEC-operated cool chamber and evaluation of developed thermoelectric cool chamber. A number of elements need to be carefully considered during the design process, including heat load assessment, TEC module selection and effective heat dissipation techniques. Appropriate TEC modules are chosen based on estimated cooling load, temperature difference achieved, power consumption, maximum cooling capacity of each TEC and heatsink. The solar photovoltaic operated thermoelectric cool chamber comprises essential components such as SPV Panel, solar charger controller, battery, PWM controller, TEC module with heat sink, and insulated box (TCC unit). The design considerations involve estimating total power consumption and determining the number and ratings of solar panels, batteries, and power conditioning devices to ensure reliable electricity supply. The system operates on SPV-generated power, utilizing MPPT charge controllers to maximize power output. Pulsed width modulation (PWM) systems efficiently regulate power distribution to thermoelectric modules, optimizing performance. The thermoelectric cool chamber was developed of 40 L water capacity. It was observed that, the chamber and water temperature in developed thermoelectric cool chamber was reduced from initial temperature by 11.85°C and 11.56°C, respectively after 24 hours. The chamber and water temperature after 24 hours were 13.31°C and 13.49°C, respectively. The performance evaluation showed that the chamber’s cooling efficiency was influenced by factors such as cooling load and water volume. This comprehensive approach enables the development of an effective and sustainable thermoelectric cooling system suitable for various applications.

Designing a multi-purpose network of sustainable and closed-loop renewable energy supply chain, considering reliability and circular economy

Since renewable energy systems have a limited lifespan and cannot be used after a while, it seems imperative to pay attention to recycling and sustainability in the supply chain network design of these systems. Also, modern power systems have high complexity and a large number of problems that affect the reliability of electricity supply to consumers. Therefore, organizations should consider broader goals, including the maximum use of resources and the minimization of waste, which is known as lean economy. In this research, a multi-objective non-linear forward optimization model has been considered for the design of the supply chain network of photovoltaic and wind systems based on the aspects of stability and taking into account the reliability. Also, adding the reverse flow, in addition to the forward flow, is also considered, which, in addition to economic advantages, also pays attention to environmental and social issues. The objective function includes minimizing all costs and negative environmental effects as well as increasing reliability. In order to convert the multi-objective planning model into a single-objective one, the epsilon method of the enhanced constraint is used. Uncertainty has been considered for all variables (except binary variables) and parameters of demand, intensity of sun radiation and amount of wind speed. Then, the efficiency of the model has been investigated through its implementation on a case study and the results have been obtained. Eventually, the model's efficiency is illustrated by discussing a real-world case, through which prominent managerial results are acquired.

ФОРМУВАННЯ ЛОКАЛЬНИХ ЕЛЕКТРОЕНЕРГЕТИЧНИХ СИСТЕМ В СКЛАДІ ОБ’ЄДНАНОЇ ЕЛЕКТРОЕНЕРГЕТИЧНОЇ СИСТЕМИ

At present, renewable sources of energy (RSE) are geographically diffused in energy supply systems, which complicates the formation of local electric energy systems (LEES), which operating in normal modes in parallel with the energy system as balancing groups, in extreme cases can operate in isolation in autonomous mode. However, the diffuse distribution of RSE does not allow for the effective formation of LEES in such a way that they ensure the required level of reliability of electricity supply to electricity consumers. The article proposes to integrate RSE into distribution power grids in the form of separate microgrid (MG), which is a key part of the transition to a power grid operating on the principles of SMART Grid. Local MGs, in addition to generation sources and consumers, also have the means to accumulate a certain amount of energy. To ensure the technical and economic efficiency, MGs are combined into an intelligent control system, which allows for more rational use of MG resources, efficient interaction with the distribution grid, and the use of active electricity consumers in the process of balancing the LEES mode. The paper proposes a hierarchical structure of the intellectual system of LEES. Thus structured, LEES with intelligent power grids can not lose RSE during the limitation of centralized power supply, but fully use their advantages together with energy storage systems for reliable power supply to consumers. Thanks to the intelligent system proposed in this paper, the LEES implements the principles of SMART Grid and functions as an informative energy system. The LEES formed in this way can operate as a balancing group within the ESS, performing the tasks of the distribution system operator depending on the voltage and power of its MG components. Since LEES are a part of the ESS, they operate under the conditions and according to the rules, without disrupting the functioning of the ESS, which currently provides a stable power supply. This applies to all modes of operation of LEES.

Features of multi-agent evaluation of of microgrid systems efficiency in parallel operation with the power system according to the reliability criterion

Ensuring reliable electricity supply to consumers in the face of destruction of critical energy infrastructure and shortage of generating capacities in Ukraine requires the development of distribution systems and their management systems. The purpose of the study was to substantiate the development of models for ensuring the optimal structure of electrical distribution networks under the conditions of connecting micro-networks according to the reliability criterion in conditions of limited investments. The paper uses a method for assessing the structural reliability of complex electrical systems with microgrid structures and forms a rational power distribution of such structures according to the criterion of optimising the reliability indicators of the studied electric power system. A mathematical optimisation model based on a computational system was proposed, designed to solve non-convex problems with minimising integral reliability indicators, considering financial constraints and the investment efficiency curve. Based on the research, the possibilities of optimisation using the BARON solver available on the NEOS server were examined. The results of the model’s performance are demonstrated using examples, considering the parameters of distribution system objects and their limitations on network components. An algorithm and programme for solving the problem of targeting power flows of microgrid structures in multi-node regional power systems are proposed. Algorithms and scenarios for the response of dispatching services are developed, provided that investments are limited, which will ensure the survivability of the power system as a whole. It is established that the development of rational electricity flows of microgrid structures will minimise the under-supply of electric energy by specific load nodes and determine their shares in covering the demand of the energy island in conditions of power shortage. The findings can be used in the operational management of power systems

Hybrid Solar PV and WECS Power Quality Improvement by STATCOM

The increasing integration of off-grid energy sources in the utility load has ended up resulting in elevated standards regarding power quality, voltage stabilisation purposes, and efficient energy use. The electrical network Wind and solar energy have been considered to be among the most reliable renewable energy sources. However, the self-sufficient operation of either photovoltaic or wind energy systems does not offer a highly consistent source of electricity production owing to the unpredictability of the wind and solar irradiance availability. As a result of this, a variety of solar and wind power generation systems have the ability to produce a very reliable and promising electrical supply. In the present study, a hybrid wind and photovoltaic panels system model has been provided. This specific type of technology possesses plenty of possibilities for its users from afar. This particular kind of technology is highly beneficial in inaccessible or offshore locations where integrating with the grid is not very cost-effective. Nevertheless, integrating power electronics to dissipated generation (DG) systems brings substantial issues with power quality, which include reactive power adjustment and harmonic development, which throws off the system for power distribution. The present study proposes a simulation framework for a hybrid wind-photovoltaic generation system. The system's efficiency in gridconnected mode is assessed. Calculations of total harmonic distortion (THD) at various speeds of wind were used for assessing the wind-SPV hybrid system's power quality. This hybrid system's power quality has been enhanced owing to its employing of STATCOM.

Smart Fault Detection on Transmission Lines via IoT Technology

In today's society, the reliability of electricity supply is paramount for sustaining essential services and infrastructure. However, power transmission networks, crucial for distributing electricity over vast distances, are vulnerable to faults that can cause equipment damage and service disruptions. Rapid fault detection is crucial to minimize these risks. This paper proposes an innovative IoT-based solution for detecting faults in transmission lines. The system integrates a center-tapped transformer and switches to simulate fault conditions, allowing real-world testing of fault detection mechanisms. Voltage signals from the transmission line are meticulously analyzed using opto-couplers and a micro-controller, which compare these signals with predefined references. Upon fault detection, immediate notifications are displayed on an LCD and transmitted via a WiFi-enabled IoT system for swift action. Furthermore, all data is logged on a central server for comprehensive analysis and ongoing monitoring. This research endeavors to significantly enhance the reliability and efficiency of transmission line operations by implementing advanced fault detection technologies, thereby reinforcing the resilience of electricity supply networks essential for modern society. Key Words: IoT,WiFi Module,Micro-controller,Transmission line.

Integration of risk, flexibility, and resilience in the optimization of water–energy nexus

AbstractCo‐location of power plants and desalination systems allows for a reduction in operational expense through energy integration. Furthermore, augmenting fossil‐based power plants with solar energy provides a means of reducing the carbon footprint of electricity generation. It is also critical to protect the combined energy–water system against internal and external risk factors to maintain a reliable supply of both electricity and water. Therefore, a systematic approach for assessing and mitigating risks is needed. Because of the complex water–energy interactions, a superstructure representation is created and a quantitative risk assessment is conducted to show potential risk factors that target specific sub‐systems. A surrogate model of the flexibility index analysis is built in order to optimize the superstructure for both cost and flexibility objectives. Finally, the generated design is simulated against disruption scenarios to obtain its resilience against various risk factors. This approach is applied to a case study on the Kuwait water–energy plant to show how the developed approach can help decision‐makers create operational strategies to protect against risk in a cost‐effective manner.

Quantum support vector machine for forecasting house energy consumption: a comparative study with deep learning models

The Smart Grid operates autonomously, facilitating the smooth integration of diverse power generation sources into the grid, thereby ensuring a continuous, reliable, and high-quality supply of electricity to end users. One key focus within the realm of smart grid applications is the Home Energy Management System (HEMS), which holds significant importance given the fluctuating availability of generation and the dynamic nature of loading conditions. This paper presents an overview of HEMS and the methodologies utilized for load forecasting. It introduces a novel approach employing Quantum Support Vector Machine (QSVM) for predicting periodic power consumption, leveraging the AMPD2 dataset. In the establishment of a microgrid, various factors such as energy consumption patterns of household appliances, solar irradiance, and overall load are taken into account in dataset creation. In the realm of load forecasting in Home Energy Management Systems (HEMS), the Quantum Support Vector Machine (QSVM) stands out from other methods due to its unique approach and capabilities. Unlike traditional forecasting methods, QSVM leverages quantum computing principles to handle complex and nonlinear electricity consumption patterns. QSVM demonstrates superior accuracy by effectively capturing intricate relationships within the data, leading to more precise predictions. Its ability to adapt to diverse datasets and produce significantly low error values, such as RMSE and MAE, showcases its efficiency in forecasting electricity load consumption in smart grids. Moreover, the QSVM model’s exceptional flexibility and performance, as evidenced by achieving an accuracy of 97.3% on challenging datasets like AMpds2, highlight its distinctive edge over conventional forecasting techniques, making it a promising solution for enhancing forecasting accuracy in HEMS.The article provides a brief summary of HEMS and load forecasting techniques, demonstrating and comparing them with deep learning models to showcase the efficacy of the proposed algorithms.

Enhancing Hybrid Power System Performance with GWO-Tuned Fuzzy-PID Controllers: A Comparative Study

This study explores the implementation of a novel control strategy within hybrid power systems, leveraging a Grey Wolf Optimization (GWO)-tuned Fuzzy Proportional-Integral-Derivative (Fuzzy-P.I.D.) controller to enhance the integration of renewable energy sources. By addressing the critical challenge of grid frequency deviations, this approach significantly bolsters the stability and efficiency of power flow, ensuring a more reliable electricity supply. Employing MATLAB simulations, the research underscores the superior performance of the GWO-tuned Fuzzy-P.I.D. controller, which necessitates fewer control interventions and yields lower oscillation frequencies than its conventional P.I.D. and Fuzzy-P.I.D. counterparts. The robustness of this optimized controller is further validated through extensive tests, demonstrating its resilience across a spectrum of parameter adjustments and operational scenarios, including the hypothetical removal of system components. The findings reveal that this advanced control method markedly surpasses traditional solutions in maintaining stable electricity flow and enhancing the system's overall resilience and adaptability to the variable nature of renewable energy. Thus, the GWO-tuned Fuzzy-P.I.D. controller emerges as a significant innovation in hybrid power system management, heralding a new era of optimization and efficiency in renewable energy integration.

A Reviewed Turn at of Methods for Determining the Type of Fault in Power Transformers Based on Dissolved Gas Analysis

Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master’s and PhD students interested in such applications.

Local Government Empowerment and Collaborative Approaches in the Electricity Sector: A Constitutional Analysis

This article explores the constitutional provisions and legislative aspects governing the role of local governments in generating and distributing electricity in South Africa. It encompasses the constitutional framework, which grants municipalities specific powers and responsibilities, highlighting the significance of these "original powers" derived directly from the Constitution. The article emphasises the need for intergovernmental cooperation at national, provincial, and local government levels to effectively address the complexities of electricity provision, taking into account related services such as water, sanitation, and environmental rights. The article further assesses recent amendments to the Electricity Regulation Act 4 of 2006, which grant municipalities greater involvement in electricity generation and procurement from independent power producers. While these amendments are seen as positive, the article highlights the need for financial resources and technical capacity building to empower municipalities to undertake these new responsibilities effectively. Ultimately, it emphasises the critical role of local governments in ensuring a sustainable and reliable supply of electricity for their communities while calling for comprehensive support from higher government levels to realise this goal.

Enhancing the economic viability and reliability of renewables based electricity supply through Power-to-Gas-to-Power with green hydrogen

This study explores the role of green hydrogen in the Power-to-Gas-to-Power process as a solution to grid instability caused by the rise of volatile renewable energy sources. A comprehensive numerical model is developed to evaluate the economic viability and reliability of electricity supply, using key performance indicators such as system levelized cost of electricity and loss of power supply probability. Through simulations based on hourly renewable energy production profiles for a scenario with an average power demand of 100 MW, the effectiveness of batteries and green hydrogen is compared. Findings indicate that while batteries are suited to photovoltaic systems, green hydrogen excels in wind energy applications, particularly in wind-solar hybrid setups. Here, green hydrogen substantially enhances the power supply reliability (loss of probability reduced from 0.23 to 0.06) and achieves a competitive system levelized cost of electricity at 0.157 USD/kWh. Sensitivity analysis regarding system size and cost variations further highlights green hydrogen's potential, providing strategic insights for improving grid stability and economic efficiency.

Predictive maintenance in electrical power systems: Thermography and statistical methods for phase synchronization analysis in disconnected substations

Phase synchronization can aid in understanding the dynamics of underlying systems. In an electric substation, disconnect, failures mostly occur due to overheating. In this work using the Hilbert transform to assess the phase synchrony of a disconnect temperature and its relationship with meteorological variables and disconnect current can be helpful in understanding temperature influences and composition. Statistical methodologies, including entropy analysis, correlation, Kalman filter, Fast Fourier Transform, Augmented Dickey–Fuller test, and Kwiatkowski–Phillips–Schmidt–Shin test, were employed. One of the differentials of this study is the use of the median filter, which was able to access the phase synchrony of the variables with disconnect temperature. An important result is that current is not the most correlated variable with disconnect temperature, instead, air temperature exhibits the highest correlation, and the highest phase synchronization is only obtained when disconnect current and air temperatures are combined. This study contributes to the advancement of power substation operations, advocating for continuous monitoring and analysis to ensure a reliable electricity supply obtaining better predictive maintenance.