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This paper presents a multi-criteria decision-making method to rank loads for load shedding in microgrids. The proposed Fuzzy VIKOR technique is based on the Fuzzy Decision-Making Test and Evaluation Laboratory (DEMATEL) model and the Analytical Network Process (ANP). The load ranking for load shedding in a microgrid is an issue that requires balancing economic and technical criteria, both of which are often in conflict with each other when considering comparative objects. The proposed Fuzzy VIKOR technique aims to solve problems related to conflicting criteria. Fuzzy numbers theory is utilized to handle uncertainty and relativity. Furthermore, the DEMATEL method also establishes Network Relationship Maps (NRM) and normalizes the unweighted supermatrix of ANP for weight values that match the criteria. The proposed method provides a comprehensive approach to evaluate the importance of criteria by determining the correlation and influence between factors, calculating their weights, and then ranking and selecting optimal loads based on the weights of load factors that serve the purpose of load shedding. A microgrid system with 16 buses was deployed to validate the proposed method. [ABSTRACT FROM AUTHOR]

Zambia has recently faced prolonged load shedding due to reduced hydroelectricity generation caused by unfavourable rainfall patterns. To tackle this issue and satisfy increasing energy demands, the government aims to explore alternative energy sources like wind energy. However, the uncertainty surrounding the economic feasibility of implementing wind power projects in Zambia poses a significant challenge. This study evaluates the economic feasibility of eight proposed wind farm sites using net present value (NPV), simple payback period (SPP), internal rate of return (IRR), and levelized cost of electricity (LCOE). By examining energy yield analysis (EYA), wind speed, and financial indicators, the study identifies the most economically viable wind farm site(s). The results reveal that the Lusaka wind farm is the most economical, with an energy yield analysis of 386 GWh, wind speed of 8 m/s, NPV of USD 316 million, SPP of 2.9 years, IRR of 82%, and LCOE of 0.182 USD/kWh. An economic sensitivity analysis, varying the average electricity tariff, also points to Lusaka as the most financially viable site. Consequently, policymakers are advised to develop cost-reflective feed-in tariff (FiT) schemes and power purchase agreements to establish electricity tariffs that encourage investment from independent power producers in Zambia.

Nowadays micro-grids (MG) as one of the most important methods used for electric power generation from renewable energy to reduce dependence on fossil fuels and reducing environmental pollution have been considered. Due to the increasing number of distributed generation (DG) sources and MGs in the power grids, it is of particular importance to design and implement a suitable controller in order to use all the available capacities in these systems. The uncertainty in prediction of power generation can be considered as disturbances into the electrical system, making it difficult to control, and eventually resulting in an unstable system. With the use of power electronic converters the power and voltage of MG can be controlled. In this paper, a 13-bus MG is proposed. This MG includes 3 wind farms and 2 PV farms. A robust sliding mode controller (SMC) is used to control voltage source converters of PV farms. A load shedding program is proposed to avoid complete blackout of MG in case of islanding that recover MG voltage to normal range after a voltage collapse. Simulations were performed using MATLAB/SIMULINK software on a 13-bus IEEE micro grid, and the effectiveness of the proposed control and operational method was investigated and confirmed. [ABSTRACT FROM AUTHOR]

Axiomatically, in this era of irregular power outages, a fundamental change in the method of delivering lectures, whether online learning, distance learning, or continuing education has emerged as a universal remedy. Researchers have put to the fore that load shedding has adverse effects on the mental health of students and lecturers. This is a literature review investigative analysis which endeavoured to elucidate the detrimental effects on mental health and well-being caused by power outages to students and their educators. The article utilised variegated literature from various research engines such as Ebscohost, Google Scholar, Research Gate, etc. The study concurred with the legal decision that power outages contravene the South African Constitution, with this transgression causing socio-psychological repercussions. The study concluded that the upcoming government elections give a chance for change to the energy parastatal behemoth, ESKOM. The paper recommends, as a ploy to ease agonies imposed by load-shedding, the implementation of various coping strategies, including maladaptive coping strategies, resolution coping strategies, and the application of the circumplex model coping. The study discusses the impact of load shedding on South Africans’ mental health including involvement of psychosocial factors. It offers a detailed examination of the mental health implications of load shedding.

Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency load shedding, damage to turbine blades, and affect frequency-sensitive loads. In this study, we propose a methodology to improve the two critical frequency stability indices, i.e., the frequency nadir and the rate of change of frequency (RoCoF), by formulating an optimization problem. The size and placement location of battery energy storage systems (BESSs) are considered to be the constraints for the proposed optimization problem. Thereafter, the optimization problem is solved using the three metaheuristic optimization algorithms: the particle swarm optimization, firefly, and bat algorithm. The best performing algorithm is then selected to find the optimal sizing and placement location of the BESSs. The analyses are all performed on the IEEE 9-bus and IEEE 39-bus test systems. Several scenarios which consider multiple generator outages, increased/decreased loading conditions, and the addition of RESs are also considered for both test systems in this study. The obtained results show that under all scenarios, the proposed method can enhance system frequency compared to the existing method and without BESSs. The proposed method can be easily upscaled for a larger electrical network for obtaining the optimized BESS size and location for the improvement of the system frequency stability.

Power outages have become pervasive in many Global South countries causing serious disruption to economies, psycho-social well-being, and industries including libraries. Occasionally, these power outages and their implications are felt in Global North countries too, mainly as a result of natural disasters whose occurrence has become too common due to global warming. This study sought to assess the impact of power outages on library services. The method employed was desk research which relied on a literature review and the lived experiences of the researcher who is based in South Africa, one of the countries that experienced almost daily periodic power outages as a result of the imposition of load shedding. The results show that power outages disrupt daily services of libraries resulting in difficulties in accessing electronic resources and services causing library hours to be adjusted and even closures. Power outages often lead to great frustration and anger from clients and librarians alike. Based on the available literature, some remedies are suggested to cushion the blow to clients and libraries. However, these remedies can only be temporary solutions. Ultimately, it is recommended that libraries should tackle the issue of load shedding collectively by either negotiating favourable deals with alternative energy providers and/or in negotiations with governments to, as far as possible, exempt and prioritise libraries in cases of power outages. This will aid in stemming the negative effects on education, access to information, and other efforts to actualise sustainable development.

Abstract Unleashing the potential of distributed renewable energy sources (RESs), intelligent and autonomous microgrids are becoming pivotal in attaining net‐zero carbon emission goals. Hybrid AC/DC microgrids rise as cutting‐edge microgrid topologies, capitalising on the best of both AC and DC systems. However, the integration of intermittent renewables and uncertainties in loading poses stability challenges. Advanced bidirectional converter controls provide efficient power exchange, but in extreme contingencies, a resilient supervisory control framework (load management/load curtailment approach) is inevitable to withstand/avoid unplanned renewable disruptions/blackouts. Moreover, the operational paradigm shift towards achieving net‐zero emissions, isolated operation of RESs, and conventional load shedding methods are anticipated to encounter substantial challenges, necessitating the development of alternative strategies. In order to improve the stability of hybrid microgrid systems in islanding scenarios, this research presents an energy balancing and load curtailment strategy. The proposed method aims at optimising resource utilisation, prioritising essential loads, and executing an optimal load curtailment strategy (if required), thereby augmenting the stability of systems. Unlike a meta‐heuristic or exhaustive search, which depends on 2n − 1 possible combinations and become unworkable as load numbers increase, the suggested methodology is based on a mathematically modelled load restriction method. By including load criticality, this strategy effectively prevents blackouts even with an increasing number of loads, providing a significantly more useful and practical solution. Additionally, the proposed charging algorithm ensures that the energy storage system imports energy from the grid during off‐peak hours and maximises power generation from the DC subgrid. The efficacy of the proposed strategy is validated using a modified IEEE‐33 bus system as a test case for a hybrid AC/DC microgrid. Simulation results demonstrate the effectiveness of the MILP‐based load curtailment approach in maintaining system stability and preventing blackouts during unforeseen events.

When applying the fault enumeration method to evaluate the reliability of the whole transmission and distribution network composed of transmission network and flexible interconnected distribution network, apart from analyzing the influence of internal faults of the transmission network and distribution network on their respective power supply reliability, the interaction between the transmission network and distribution network should also be considered under the fault scenario. Based on existing independent reliability evaluation algorithms for the transmission network and distribution network, the reliability evaluation method for the whole transmission and distribution network is proposed in this paper. The proposed method in this paper can account for the interrelation between the operation states of the transmission network and the distribution network under the fault condition. The node load reduction after the failure of the transmission network is refined into the optimized load cutting scheme of the distribution network. While improving the accuracy of the reliability evaluation results of the transmission network, the load loss of the distribution network caused by the failure of the transmission network is included in the reliability evaluation of the distribution network. In addition, the load loss caused by internal faults of the distribution network and its influence on the reliability of the transmission network are included in the reliability evaluation of the transmission network. For the whole transmission and distribution network, the reliability index of the transmission and distribution network is calculated by the analytical method based on fault enumeration. The validity of the reliability evaluation model is verified by the results of the numerical analysis.

With the rapid development of distribution networks and increasing demand for electricity, the pressure of power supply for medium- and low-voltage distribution networks (M&LVDNs) is increasingly significant, especially considering the large scale of customers at the low-voltage (LV) level. In this paper, an outage sequence optimization method for low-voltage distribution networks (LVDNs) that considers the importance of users is proposed. The method aims to develop an optimal outage sequence strategy for LV customers in case of medium-voltage (MV) failure events. First, a multi-dimensional importance indicator system for LV users is constructed, and the customers are ranked using a modified Analytic Hierarchy Process–Entropy Weight (AHP-EW) method to determine their priorities during outages. Then, an elastic net regression-based method is used to identify the topology of the LV network. Finally, an outage sequence optimization model based on the user importance is proposed to reduce the load-shedding level. Extensive case studies are conducted in the modified LV distribution network. The results show that the proposed method results in fewer outage losses throughout the restoration periods than traditional methods and effectively improves the reliability of the power supply to LV users. [ABSTRACT FROM AUTHOR]

In large buildings, effective load shedding and shifting and providing the maximum power through solar renewable sources remain challenges because of users' unpredictable load consumption. Conventionally, load shifting, load shedding, and load covering are majorly dependent on user inputs. The lack of user interest in participating in demand responses for effective load shifting and covering remains a problem. Effective load covering through renewables and user-friendly load shedding and shifting with maximized user participation are challenging and demand high-resolution user load consumption information, which are not possible without sophisticated communication and digital twins. In this research work, a novel fuzzy-logic-based cascaded decentralized load-controlling mechanism has been developed that manages the residential building load through load-shifting, load-covering, and load-shedding schemes without any communication protocols and digitization between residential units. The decentralized controller aims to effectively utilize the centralized resources of power generation with the effective automated participation of users. The quantification of the load shifting, covering, and shedding performed during peak hours was well covered under the load-covering scheme, and the results showed that flexibility capacities of 1617 kW were achieved for load covering, 294 kW for load shedding, and 166.34 kW through shifting. A total load of 60 kW, which was reduced during shedding and shifting, was well covered during load covering through renewables. [ABSTRACT FROM AUTHOR]

Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency load shedding, damage to turbine blades, and affect frequency-sensitive loads. In this study, we propose a methodology to improve the two critical frequency stability indices, i.e., the frequency nadir and the rate of change of frequency (RoCoF), by formulating an optimization problem. The size and placement location of battery energy storage systems (BESSs) are considered to be the constraints for the proposed optimization problem. Thereafter, the optimization problem is solved using the three metaheuristic optimization algorithms: the particle swarm optimization, firefly, and bat algorithm. The best performing algorithm is then selected to find the optimal sizing and placement location of the BESSs. The analyses are all performed on the IEEE 9-bus and IEEE 39-bus test systems. Several scenarios which consider multiple generator outages, increased/decreased loading conditions, and the addition of RESs are also considered for both test systems in this study. The obtained results show that under all scenarios, the proposed method can enhance system frequency compared to the existing method and without BESSs. The proposed method can be easily upscaled for a larger electrical network for obtaining the optimized BESS size and location for the improvement of the system frequency stability. [ABSTRACT FROM AUTHOR]

Recent years have seen a sharp increase in the electrical crisis, which has an impact on our daily lives. In South Africa, load shedding is a common occurrence due to its ageing electrical infrastructure and rising energy consumption. This has led most educational institutions to rely more on blended learning to ensure that teaching and learning continue. The utilisation of blended learning in South African learning institutions saw an enormous disparity in student‘s household incomes, which directly affects their access to digital material and internet connections. During load shedding, technology-based tools and the internet are interrupted, and as a result, learning tools like Moodle become inaccessible. Many institutions have responded to load shedding upon observing the impact it has on them and their students. Therefore, this study seeks to identify the obstacles encountered by university students during teaching and learning amid load shedding in South Africa. The study adopted a quantitative approach with a target population of 150 students at the University of Zululand. A questionnaire with closed-ended questions was shared electronically with respondents using Google forms. The responses were captured and analysed using Google forms. The data was then presented using graphs, charts, and tables. The study was conceptualized using the Shannon and Weaver communication model and Diffusion of Innovation Theory. The findings revealed that most students experience connectivity problems, limited access to digital resources, dark venues, and student absenteeism during load shedding. It is recommended that management should provide all staff and students with up-to-date power usage statistics and early warnings on what staff and students must do to minimise the impact of load shedding. Load shedding apps and schedules are available and easily accessible which the university could further assist by sharing this information with students. Academics also need to plan for offline tasks, and it is imperative that students are timeously aware of any load shedding interferences. This time during load shedding can also be used to engage in collaborative tasks such as team building activities and fostering social cohesion. Higher education also needs to invest in alternative power solutions to effectively mitigate the impact of load shedding on the teaching and learning process. [ABSTRACT FROM AUTHOR]

Fault-induced delayed voltage recovery (FIDVR) occurs after a fault in the network with high penetration of induction motor (IM) loads. Load shedding (LS) is one of the appropriate methods to reduce the destructive effects of FIDVR on the network, and for this reason, the authors have previously presented three LS methods to deal with FIDVR. The first method uses the index of IM loads' power change. The second one is an optimization problem and the third method introduces indicators based on sensitivity analysis. The proposed methods obtain less LS amounts, also, the number of LS locations and moments of proposed methods are fewer than previous ones. However, these methods have different execution times which are related to the speed of the utilized processor; and the suitable method to deal with FIDVR must have the ability to shed the load in the initial moments of this phenomenon. Since the proposed LS methods are centralized, therefore, a central unit is required to monitor the network through the voltage and current sent through PMUs and the status of circuit-breakers, for detecting critical conditions and determining the amount and location of LS. Various states such as estimation of load parameters, detection of fault occurrence and clearance, detection of topology change, and voltage estimation process are also needed before the start of LS calculations, which are discussed in this paper. Also, the telecommunication required by this central unit is provided with a GOOSE message based on IEC 61850 standard. [ABSTRACT FROM AUTHOR]

Congestion in transmission lines will not be tolerable except for a short time as it may cause power outages and losses. In this paper, through multistage congestion management (CM), a conceptual framework for transmission CM is presented. At first, by the contingency analysis, uncertainties are prioritized based on their impacts on the congestion. Those with severe impacts (in congestion) are taken into account in the day ahead, while those with minor impacts are considered in the real time. It is because of the fact that all uncertainties do not happen in reality and considering all of them in the day ahead imposes high additional costs. In other words, the minor effect uncertainties are neglected in day ahead and are postponed to real time. Hence, even if they happen, they will be overcome by remedial measures with no significant concern. Then at each time interval (for both day ahead and real time), using the sensitivity analysis a congestion control zone is formed for each congested line. Finally, through the intelligent implementation of the nonlinear demand response programs (DRPs) and an alternative load shedding model, the congestion is alleviated. Results prove the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

There is currently a rising interest in reusing and repurposing offshore facilities through decommissioning; however, major challenges arise, such as size, weight, sea depth, planned use, and location. This article aims to discuss the philosophy that needs to be adopted for field redevelopment, particularly when existing platforms must be preserved and integrated into new greenfield facilities. The article also discusses the concept of weight shedding during the decommissioning of offshore facilities to either extend the life of existing platforms or provide clear space for new equipment to be installed by removing unnecessary components and structures. The above aspects of decommissioning are investigated through the redevelopment of a case study of a mature offshore oil field located in shallow water. The study indicated that weight shedding presents a favourable method for decommissioning offshore installations and can effectively lower expenses, minimise environmental consequences, and optimise the use of resources. [ABSTRACT FROM AUTHOR]

This paper proposes a new comprehensive load restoration (LR) method for electrical distribution networks. Since two main technologies of switching equipment are there in the modern distribution networks, namely manual switches (MSs) and remote‐controlled switches (RCSs), this article has benefited from this concept effectively. A two‐stage algorithm that provides the system operators with the ability to recover part of the loads in the shortest possible time by RCSs is proposed. After this step, the remaining loads will be restored by a combination of MSs and RCSs. The other strength of this algorithm is to provide accurate and practical solutions so that the sequence of switching actions is clearly defined. Also, using an innovative index called expected weighted energy not supplied as the objective function of the main problem will ensure the operators recover the maximum amount of load in the shortest time possible. This novel method was applied on a sample standard IEEE distribution test network. The simulation results proved the effectiveness of this proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Load shedding in South Africa has a profound impact on various sectors, including education, and specifically, South African music education faces significant disruptions. One of the most notable effects is the interruption of music instruction, with load shedding frequently causing classes to be interrupted. This leads to gaps in learning and a disjointed educational experience for students. The aim of this article was to investigate the influence of load shedding on South African higher education, particularly in Schools of Music. The study utilized a qualitative research method and relied heavily on secondary data. It employed a data cleaning strategy and a triangulation approach to ensure data validity and minimized bias. Additionally, Critical Pedagogy Theory was used to address the exacerbated socio-economic disparities resulting from load shedding. The findings of the study highlighted that before the onset of load shedding, South African music education already faced an urban-rural divide, with urban institutions having better resources and opportunities than rural schools. Load shedding exacerbates these disparities, as students from disadvantaged backgrounds face increased barriers to accessing musical instruments and supplementary resources. In conclusion, the study emphasized the urgent need for concerted efforts to mitigate the impact of load shedding on music education. It underscored the transformative potential of inclusive, uninterrupted music instruction for students in South African rural-based Schools of Music.

System stability issues regarding frequency and voltage in modern power systems are growing in importance as they incorporate more and more complex components. To ensure a sustainable, pollution-free power generation, modern power systems are designed to incorporate more renewable generation sources than traditional ones. Therefore, in the event of a large-scale disruption event, conventional load-shedding strategies are unable to keep the voltage and frequency limit below the threshold value. The suggested approach takes into account this issue by rating load buses in relation to relevant frequency changes, their voltage stability, system load damping coefficients, and the introduction of green energy sources in place of fossil fuel-based ones. Battery Energy Storage Systems (BESS) are used in the proposed method to minimize load shedding amount required for conventional schemes. After determining the amount, the scheme dynamically chooses feeders as per relative weightage of the stability components (voltage, frequency) to ensure that the overall load shed amount is near to the calculated value. To verify this, the scheme is tested on IEEE 39 bus with python scripted simulation. There are four scenarios considering 250 MW, 500 MW and 1500 MW injection of PV based power generation sources with conventional generation loss of 800 MW and 1000 MW. The threshold frequency is considered 49.10 Hz. The total amount of BESS is 300 MW. For every scenario, it has been found that the methodology successfully maintains the system frequency above 49.10 Hz with a minimal amount of load shedding. Hence, the proposed methodology is able to maintain frequency stability for a modern power system with large-scale PV generation through adaptive feeder selection for load shedding.

Abstract This paper proposes a two‐stage stochastic scheduling model for urban distribution network resilience enhancement against ice storms, which coordinates mobile deicing equipment routing and distributed energy resources dispatching. An improved line ice thickness prediction model and a photovoltaic power generation prediction method in accordance with conditional generative adversarial networks are proposed to provide data boundaries for scheduling strategy. Facing the uncertainty of line failure, a two‐stage scenario‐based distribution network optimization model is established. At first stage, the mobile deicing equipment routing strategy is decided to mitigate the impact caused by ice storms. The Monte‐Carlo simulation method is introduced to describe the uncertainty of line failure due to ice acceleration. For the second stage, based on the results of photovoltaic forecasting and possible distribution line failure scenario generated by Monte‐Carlo simulation method, the optimal distributed energy resources dispatching strategy can be obtained through the mixed integer programming. The proposed model is simplified to a mixed integer linear programming model that can be solved by a commercial solver. The test results on the modified IEEE 33‐node system and modified 69‐node system demonstrate that the proposed method can effectively improve the resilience performance of urban distribution network under ice storms.

This paper examines governance strategies to address South Africa's persistent electricity infrastructure challenges, particularly recurring blackouts. It centres on the crucial role of the President in orchestrating effective energy service delivery. Drawing on historical approaches and employing intersectionality theory, it identifies key areas for improvement. Through secondary data research from various sources, including textbooks and journals, the paper advocates for prioritising renewable energy, enhancing accountability, and fostering stakeholder collaboration. The conclusions underscore the necessity of combined efforts among policymakers, officials, and stakeholders to stimulate investment, optimise infrastructure, and ensure universal electricity access. The paper's novelty lies in its comprehensive analysis within an intersectional framework, offering actionable recommendations for navigating South Africa's electricity landscape. Through embracing these strategies, South Africa can envision a future of reliable, accessible electricity, vital for societal well-being and holistic development. [ABSTRACT FROM AUTHOR]

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions). Plain Language Summary: Electric heat pump adoption could help abate the impacts of climate change on overall power system reliability by reducing summer cooling demand in a warmer world because heat pumps are a more efficient alternative to standard air conditioning. It would also carry greenhouse gas emissions benefits in a decarbonized power grid. Yet widespread adoption of heat pumps (especially low‐efficiency heat pumps) could cause more extreme winter peaking events. During these extreme cold events, higher peak demand could result in an increased probability of outages. Higher efficiency heat pumps would help avoid these winter reliability impacts, but these more efficient heat pumps are also currently more expensive. From a grid planning perspective, planners need to account for a range of future peak demand dynamics across different heat pump adoption scenarios and climate futures. Key Points: Widespread electric heat pump adoption and climate change will increase uncertainty in seasonal peaking patterns and grid reliabilityFuture peaking behavior depends on the frequency and severity of extreme heat and cold events and the type of heat pumps widely adoptedShifts toward winter peaking could carry large resource adequacy risks, depending on pump efficiency and climate scenario [ABSTRACT FROM AUTHOR]

Copyright of Journal of Nanchang University (Engineering & Technology) is the property of Nanchang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Power distribution utilities need to have an effective and suitable service restoration (SR) plan to reconnect customers quickly after power outages. This article presents a heuristic bi-stage SR algorithm that first re-energizes some of the loads fast by remote-controlled switches (RCSs) in the first stage and then continues to restore the rest of the network in the second stage with all possible switching actions using RCSs and manual switches (MSs). This study also includes finding the optimal Switching Sequences (SSs) and the estimated energy not supplied (EENS) as an objective function. Moreover, the proposed method is more attractive and practical because it considers the time of occurrence of the failure and the daily load curve, the location of the load transfer capability, and the traffic conditions of the network. In this method, repair crew (RC) and mobile power sources (MPSs) are also important for the restoration process. The heuristic SR algorithm was tested on a standard IEEE 70-bus system in different scenarios. The results showed a significant difference in the solutions to the problem and the ENS in different scenarios. Lastly, it was concluded that this heuristic method would produce optimal, precise, and feasible solutions for SR in distribution networks. [ABSTRACT FROM AUTHOR]

This paper proposes a two‐stage stochastic scheduling model for urban distribution network resilience enhancement against ice storms, which coordinates mobile deicing equipment routing and distributed energy resources dispatching. An improved line ice thickness prediction model and a photovoltaic power generation prediction method in accordance with conditional generative adversarial networks are proposed to provide data boundaries for scheduling strategy. Facing the uncertainty of line failure, a two‐stage scenario‐based distribution network optimization model is established. At first stage, the mobile deicing equipment routing strategy is decided to mitigate the impact caused by ice storms. The Monte‐Carlo simulation method is introduced to describe the uncertainty of line failure due to ice acceleration. For the second stage, based on the results of photovoltaic forecasting and possible distribution line failure scenario generated by Monte‐Carlo simulation method, the optimal distributed energy resources dispatching strategy can be obtained through the mixed integer programming. The proposed model is simplified to a mixed integer linear programming model that can be solved by a commercial solver. The test results on the modified IEEE 33‐node system and modified 69‐node system demonstrate that the proposed method can effectively improve the resilience performance of urban distribution network under ice storms. [ABSTRACT FROM AUTHOR]

This paper describes a novel algorithm for line overload alleviation with minimum load curtailment in the presence of wind turbine doubly fed induction generator (WTDFIG). Emergency conditions may arise due to predicted load in the next interval or outage of a transmission line. Selection of load buses for load shedding has been identified by sensitivities of severity index. Bounds on bus voltages have been considered in addition to line flow limits. Crow search algorithm (CSA) modified with Lampnien's criterion to account inequality constraints has been employed to obtain optimal solution of the formulated problem. A significant increase in electric vehicles (EVs) is observed each year. This, in turn, causes an increase in EV charging substations to meet the load demand. In view of this, role of renewable energy sources (RESs) has increased to maintain the continuity of supply to EVs charging substations. The developed algorithm has been implemented on 25-bus and 118-bus standard IEEE test systems. Results have been compared with those obtained using SFLA (shuffled frog leaping algorithm) and CAPSO algorithm based on statistical inferences. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a new comprehensive load restoration (LR) method for electrical distribution networks. Since two main technologies of switching equipment are there in the modern distribution networks, namely manual switches (MSs) and remote‐controlled switches (RCSs), this article has benefited from this concept effectively. A two‐stage algorithm that provides the system operators with the ability to recover part of the loads in the shortest possible time by RCSs is proposed. After this step, the remaining loads will be restored by a combination of MSs and RCSs. The other strength of this algorithm is to provide accurate and practical solutions so that the sequence of switching actions is clearly defined. Also, using an innovative index called expected weighted energy not supplied as the objective function of the main problem will ensure the operators recover the maximum amount of load in the shortest time possible. This novel method was applied on a sample standard IEEE distribution test network. The simulation results proved the effectiveness of this proposed method.

ABSTRAK Gangguan kontingensi sistem tenaga listrik dapat menyebabkan overload yang berpotensi memicu blackout masal jika tidak ditangani dengan tepat. Penelitian ini mengusulkan desain skema overload shedding untuk Subsistem Pedan 3,4 yang mempertimbangkan prioritas beban. Simulasi dilakukan pada tiga skenario gangguan kontingensi N-1 dan N-1-1 meliputi trip pada Interbus Transformer (IBT), PLTU Pacitan 1, serta kombinasi keduanya. Hasil simulasi menunjukkan bahwa pada kasus gangguan IBT dan kombinasi IBT-PLTU, skema overload shedding yang diusulkan berhasil mencegah blackout dengan melakukan pelepasan beban bertahap sesuai prioritas. Namun, pada kasus trip PLTU saja, tidak diperlukan pelepasan beban karena pembebanan IBT masih aman. Dengan demikian skema overload shedding ini terbukti efektif dalam menjaga keandalan sistem tenaga listrik saat menghadapi gangguan kontingensi, mencegah blackout masal dan meminimalkan dampak pada area non-kritis. Kata kunci: load shedding, overload, kontingensi, prioritas beban, DIgSILENT ABSTRACT Power system contingency disturbances can cause overloads that have the potential to trigger mass blackouts if not handled appropriately. This study proposes an overload shedding scheme design for Pedan 3,4 Subsystem that considers load prioritization. Simulations were conducted on three N-1 and N-1-1 contingency fault scenarios including trips to the Interbus Transformer (IBT), Pacitan 1 PLTU, and a combination of both. The simulation results show that in the case of IBT fault and IBT-PLTU combination, the proposed overload shedding scheme successfully prevents blackout by performing gradual load shedding according to priority. However, in the case of PLTU trip only, no load shedding is required because the IBT loading is still safe. Thus this overload shedding scheme is proven effective in maintaining power system reliability when facing contingency disturbances, preventing mass blackouts and minimizing the impact on non-critical areas. Keywords: load shedding, overload, contingency, load priority, DIgSILENT

The tight interactions between energy sectors increase the risk of affecting integrated energy systems (IESs); therefore, reliability assessment is important for identifying vulnerability and improving security in IESs. In the literature, the network topology, transmission loss, and distinguishing thermal dynamics in IESs are seldom addressed for reliability assessment, rendering the results unreliable. To bridge this gap, an integrated electricity and district cooling model is formulated for IESs that involves elaborate network topologies and transmission losses to reflect their impacts on reliability characteristics. In addition, the evaluation of reliability indices for district cooling systems is improved by considering the thermal inertia characteristics of buildings and the transportation delay of circulating water to characterize the reliability levels of district cooling systems more accurately. Numerical results using a 12-node case validate the improved accuracy of the proposed reliability assessment method and reveal the potential of district cooling systems for enhancing the reliability of power systems.

In 1994, the African National Congress (ANC)-led government implemented a Reconstruction and Development Programme (RDP) program that entailed providing South Africans with stable and regular electricity supplies. Government through the state president declared COVID-19 a pandemic in 2019. Institutions of higher education resorted to introduce online teaching and learning as a method of ensuring that section 27 (1) (a) (b) of the Constitution of the Republic of South Africa was executed. Load shedding brought numerous challenges in the education settings in the institutions of higher learning. The crisis led to institutional economy and disrupted academic performance at institutions of higher learning. The purpose of this study is to examine whether load shedding can be regarded as a pandemic post COVID-19. Access the impact of load shedding at institutions of higher learning. Therefore, this is a conceptual paper and it relied on existing data for analysis and interpretation. The study recommends that institution of higher learning should invest in alternative sources of energy, and develop an effective communication strategy.

Industrial electrification provides a motivation to explore new methods for electrical power management. This paper addresses the situation where the available power is not enough to meet the full demand of a large production site, which can happen because of an electrical contingency. An industrial power management system typically handles electrical power deficits by disconnecting equipment, also known as load shedding. However, disconnections may cause an industrial process to shut down giving a very significant negative economic impact. Using a gas export plant as an example, this paper shows that flexible operation of the plant can offer an alternative to disconnection by making optimal use of any remaining available power, thus avoiding load shedding and enabling an electricity-intensive process to ride through a contingency without an expensive shut-down. Instead of load shedding, the electrical drives will enforce an immediate partial reduction of the power supplied to electrical motors and other machinery on a timescale similar to that of a circuit breaker. An innovation of the research is a framework for pre-computing feasible operating points of the process that match the available power. Technology suitable for industrial implementation is identified in the article and practical considerations are addressed. The findings show promise for the development of new systems for managing electrical power in electricity-intensive sites.

The management of electricity distribution faces numerous challenges, including energy losses arising from technical and non-technical issues such as electricity theft. Energy losses due to theft have a significant global impact, including in South Africa (SA). SA rural areas are suffering from poor voltage, and technical and non-technical losses due to old power system systems. Hence, this research project is a proposal for the upgradation of an old and technically weak network of Nottingham Road, Kwa-Zulu Natal in South Africa. To reduce non-technical losses, this research examines the influence and potential solutions of using smart meters. The paper focuses on modeling real low voltage (LV) distribution systems and the energy meters that measure various parameters of the smart meters. This research also examines the effect of illegal links on the network. However, implementing the smart metering technology for lesser power consumers in developing countries such as South Africa can be challenging because of the greater initial costs. Therefore, this paper investigates the possibility of various technology choices and their return on investment in both urban and rural regions.

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events. [ABSTRACT FROM AUTHOR]

To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island's power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability. [ABSTRACT FROM AUTHOR]

The most critical strategy to keep the electrical grid from collapsing is load shedding. However, by itself, this approach is unable to achieve system stabilization, as well as frequency and voltage have an impact on the network's stability as well. Traditional load-shedding designs do not take into account the various load models and the declining economic cost associated with load disconnecting. When calculating load flow, multiple load models like constant power (C.P), constant current (C.I), constant impedance (C.Z), and combined load (ZIP) may be involved, but all loads are typically described as constant electrical power (C.P). In this article, the idea of a dual approach to load shedding and capacitor placement is adopted to maximize the amount of power loss reduction in the distribution network, taking into account different load models and determining the best one that leads to the least losses, the best voltage profile, and the lowest cost. To minimize load shedding for the network and choose the optimal capacitor size and location, the Teaching Learning Based Optimization (TLBO) algorithm. The outcomes showed that using the ZIP scenario is the superior model for all scenarios in terms of reducing active power losses by about 66.018% and lowering the percentage of load shedding to 19.5195%. [ABSTRACT FROM AUTHOR]

This article addresses a comprehensive analysis of power electrical systems, employing a combined approach of genetic algorithms and mathematical optimization through nonlinear programming with discontinuous derivatives (DNLP) in GAMS. The primary objective is to minimize economic losses and associated costs faced by the network operator following disruptive events. The analysis is divided into two fundamental aspects. Firstly, it addresses the topological reconfiguration of the network, involving the addition of lines and distributed energy resources such as distributed generation. To determine the optimal topological reconfiguration, a genetic algorithm was developed and implemented. This approach aims to restore electrical service to the maximum load within the system. Secondly, an optimal energy dispatch was performed for each generator, considering the variation in load throughout the day. The system's load curve is taken into account to determine the optimal energy distribution. Thus, the problem of economic losses is approached from two perspectives: the minimization of costs due to nonsupplied electrical energy and the determination of efficient energy dispatch for each generator after network reconfiguration. For the analysis and case studies, simulations were conducted on the IEEE 9- and 30-node test systems. The results demonstrate the effectiveness of the proposed solution, evaluated in terms of reduced load shedding and economic losses. [ABSTRACT FROM AUTHOR]

Increased stress in traditional power systems results in blackouts due to voltage instability attributed to a mismatch between available capacity and load demand, especially in distribution networks. Service restoration schemes are designed to return power supply to the affected parts of the networks. The availability of insufficient supply is a complex problem that requires operational experience or an automatic system. The stochastic nature of load demand significantly impacts service restoration as it results in increased restored demand in case a fault occurs during off-peak hours and helps reduce overload if the fault occurs during peak hours. The study adopts an experimental design methodology to develop the Reinforcement Learning-based service restoration algorithm considering the stochastic nature of load demand. Three reinforcement learning models were used to develop the optimal load shedding model, including Actor-Critic (A2C), a Deep Q Network (DQN) and Proximal Policy Optimization (PPO2), and compared to maximize restored customers, satisfaction of operational constraints, and balancing of power supply and demand. The Particle Swarm Optimization (PSO) algorithm, a metaheuristic algorithm, was also implemented to compare with the proposed approach. The proposed solution has been tested using data from a real electrical secondary distribution network. The proposed solution considered the stochastic nature of load demand, resulting in more restored customers. The computation time during restoration has been improved by 69.8% compared to the metaheuristic approach. [ABSTRACT FROM AUTHOR]