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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. [ABSTRACT FROM AUTHOR]

The electricity sector plays a key role in achieving zero emissions targets. The required transition will lead to substantial changes in the supply, demand, and distribution of electricity, as well as in stakeholder roles. Future market designs may change substantially to accommodate these changes, address challenges, and take advantage of new opportunities. This paper reviews the characteristics of future carbon-neutral electricity systems and electricity market design options. To provide a guiding framework for the literature review, we transfer the complexity of electricity systems into a three-layer structure: Firstly, we analyze papers that rely on techno-economic modeling of the physical electricity system. As a case study, we analyze various studies focusing on a decarbonized European electricity system in 2050. Secondly, we review papers that investigate the economic behavior and effects of self-interest-seeking stakeholders such as producers, network operators, and consumers. Finally, we review papers focusing on policy and market design questions that guide policymakers in achieving a target physical asset combination while considering the behavior of stakeholders. We highlight common trends and disagreements in the literature, review the main drivers of future markets, and finally provide a mapping between those drivers, challenges, and opportunities. The review concludes that the most promising next step toward a fully comprehensive assessment approach is to combine existing approaches across topical and disciplinary boundaries. [ABSTRACT FROM AUTHOR]

The ongoing electrification of the transport sector is expected to cause an increase in electricity demand and, therefore, trigger significant network investments to accommodate it. This paper focuses on investment decision-making for electricity distribution grids and specifically on the strategic and incremental investment network planning approaches. In particular, the former involves network planning with the consideration of a long-term multi-stage study horizon, as opposed to a shorter–term view of the future that applies to the latter case. An investment analysis that is carried out underlines the economic savings generated from adopting a strategic investment perspective over an incremental one. These economic savings are achieved from the fact that the associated fixed investment costs are incurred only once in the horizon under strategic planning. On the other hand, incremental planning involves a series of network reinforcement decisions, thereby incurring the fixed cost multiple times. In addition, sensitivity analyses that are carried out capture the effect of key parameters, such as investment cost, discount rate and investment delay, on the generated economic savings. [ABSTRACT FROM AUTHOR]

During the energy transition, new types of electrical equipment, especially power electronic devices, are proposed to increase the flexibility of electricity distribution grids. One type is the solid-state transformer (SST), which offers excellent possibilities to improve the voltage quality in electricity distribution grids and integrate hybrid AC/DC grids. This paper compares SST to conventional copper-based power transformers (CPT) with and without an on-load tap changer (OLTC) and with additional downstream converters. For this purpose, a corresponding electricity distribution grid is set up in the power system analysis tool DIgSILENT PowerFactory 2022. A DC generator like a photovoltaic system, a DC load like an electric vehicle fast charging station, and an AC load are connected. Based on load flow simulations, the four power transformers are compared concerning voltage stability during a generator-based and a load-based scenario. The results of load flow simulations show that SSTs are most valuable when additional generators and loads are to be connected to the infrastructure, which would overload the existing grid equipment. The efficiency of using SSTs also depends on the parameters of the electrical grid, especially the lengths of the low-voltage (LV) lines. In addition, a flowchart-based decision process is proposed to support the decision-making process for the appropriate power transformer from an electrical perspective. Beyond these electrical properties, an evaluation matrix lists other relevant criteria like characteristics of the installation site, noise level, expected lifetime, and economic criteria that must be considered. [ABSTRACT FROM AUTHOR]

Many emerging applications, such as factory automation, electric power distribution, and intelligent transportation systems, require multicast Ultra-Reliable Low-Latency Communications (mURLLC). Since 3GPP Release 17, 5G systems natively support multicast functionality, including multicast Hybrid Automatic Repeat Request and various feedback schemes. Although these features can be promising for mURLLC, the specifications and existing studies fall short in offering guidance on their efficient usage. This paper presents the first comprehensive system-level evaluation of mURLLC, leveraging insights from 3GPP specifications. It points out (i) how mURLLC differs from traditional multicast broadband wireless communications, and (ii) which approaches to provide mURLLC require changing the paradigm compared with the existing solutions. Finally, the paper provides recommendations on how to satisfy strict mURLLC requirements efficiently, i.e., with low channel resource consumption, which increases the capacity of 5G systems for mURLLC. Simulation results show that proper configuration of multicast mechanisms and the corresponding algorithms for mURLLC traffic can reduce resource consumption up to three times compared to the baseline solutions proposed for broadband multicast traffic, which significantly increases the system capacity. [ABSTRACT FROM AUTHOR]

Modern power systems present opportunities and challenges when integrating distributed generation and electric vehicle charging stations into unbalanced distribution networks. The performance and efficiency of both Distributed Generation (DG) and Electric Vehicle (EV) infrastructure are significantly affected by global temperature variation characteristics, which are taken into consideration in this study as it investigates the effects of these integrations. This scenario is further complicated by the unbalanced structure of distribution networks, which introduces inequalities that can enhance complexity and adverse effects. This paper analyzes the manner in which temperature changes influence the network operational voltage profile, power quality, energy losses, greenhouse harmful emissions, cost factor, and active and reactive power losses using analytical and heuristic techniques in the IEEE 69 bus network in both three-phase balance and modified unbalanced load conditions. In order to maximize adaptability and efficiency while minimizing the adverse impacts on the unbalanced distribution system, the findings demonstrate significant variables to take into account while locating the optimal location and size of DG and EV charging stations. To figure out the objective, three-phase distribution load flow is utilized by the particle swarm optimization technique. Greenhouse gas emissions dropped by 61.4%, 64.5%, and 60.98% in each of the three temperature case circumstances, while in the modified unbalanced condition, they dropped by 57.55%, 60.39%, and 62.79%. In balanced conditions, energy loss costs are reduced by 95.96%, 96.01%, and 96.05%, but in unbalanced conditions, they are reduced by 91.79%, 92.06%, and 92.46%. The outcomes provide valuable facts that electricity companies, decision-makers, along with other energy sector stakeholders may utilize to formulate strategies that adapt to the fluctuating patterns of electricity distribution during fluctuations in global temperature under balanced and unbalanced conditions of network. [ABSTRACT FROM AUTHOR]

The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used. [ABSTRACT FROM AUTHOR]

The expansion of distributed renewable resources, together with increased demand from the electrification of transport and heating sectors, impacts distribution networks significantly. Additionally, the emergence of non-programmable and intermittent generators is set to diminish the dominance of traditional rotating and programmable generation, thereby affecting the overall stability of the system. Nevertheless, the flexibility offered by distributed resources has the potential to alleviate the necessity for network reinforcement and contribute to system stability at competitive costs. Local flexibility procurement should be rooted in local markets, serving as mechanisms to address distribution congestion and coordinate the provision of flexibility for transmission network services. The multitude of existing systems and the interdependence of flexibility services have given rise to diverse solutions, still undergoing experimentation in various countries. This paper aims to scrutinize key projects that have established local flexibility markets, delineating their fundamental characteristics, the most common solutions, identifying prevalent barriers and suggesting potential future improvements. The investigation focuses on the most uncertain aspects of local markets: possible TSO-DSO coordination schemes, the time horizon for the acquisition of services and the baseline definition methodologies. [ABSTRACT FROM AUTHOR]

It is widely recognised that improving the visibility and controllability of distributed energy resources (DERs) within electricity distribution networks will have significant benefits, particularly for the management of low-voltage (LV) and medium-voltage (MV) networks. Much work within the electricity distribution industry is currently focused on improving the visibility of DERs on LV networks. From a control-theoretic perspective, this enables closing the loop between the DER and the control room and enables a shift towards utilising data-driven model-based control strategies for DERs. The result is a system-wide performance that is closer to the theoretical optimal. In the Australian context, several jurisdictions are trialling techniques such as dynamic operating envelopes to enhance DER hosting capacity, using IEEE 2030.5-based architectures, with the implementation of distributed energy resource management (DERMS) systems at the enterprise level still quite limited. While there is significant activity focused on DER behaviour and control techniques by way of inverter grid codes and standards, the core issue of interoperability with distribution management systems (DMSs), market operators or participants, electric vehicles (EVs) or other DERs is still a work in progress. Importantly, this is also an impediment to realising distributed architectures for DER control in the grid. The unique characteristics of Australian distribution networks highlights several challenging problems for DER control and management. The objective of this paper is to provide a broad overview of DER control and management strategies in the Australian context, with an application focus on DER control in distribution network management. [ABSTRACT FROM AUTHOR]

Assessments of the hosting capacity of electricity distribution networks are of paramount importance, as they facilitate the seamless integration of rooftop photovoltaic systems into the grid, accelerating the transition towards a more carbon neutral and sustainable system. This paper employs a deep reinforcement learning-based approach to evaluate the real-time hosting capacity of low voltage distribution networks in a model-free manner. The proposed approach only requires real-time customer voltage data and solar irradiation data to provide a fast and accurate estimate of real-time hosting capacity at each customer connection point. This study addresses the imperative for accurate electrical models, which are frequently unavailable, in evaluating the hosting capacity of electricity distribution networks. To meet this challenge, the proposed approach utilizes a deep neural network-based, data-driven model of a low-voltage electricity distribution network. This proposed methodology incorporates model-free elements, enhancing its adaptability and robustness. In addition, a comparative analysis between model-based and model-free hosting capacity assessment methods is presented, highlighting their respective strengths and weaknesses. The utilization of the proposed hosting capacity estimation model enables distribution network service providers to make well-informed decisions regarding grid planning, leading to cost minimization. [ABSTRACT FROM AUTHOR]

With the continuous development of renewable energy technologies, both domestically and internationally, the focus of energy research has gradually shifted towards renewable energy directions such as distributed photovoltaics and wind power. The penetration rate of renewable energy generation is constantly increasing, at the same time, the elements in the grid are becoming increasingly complex, and large-scale energy storage, as well as a variety of electricity loads such as electric vehicle charging piles and data centers are gradually appearing. Therefore, traditional distribution methods of the power grid are difficult to ensure the stable operation of the power system and cannot achieve efficient integration of renewable energy. Consequently, some scholars have proposed the concept of an energy internet. Compared to traditional power grids, the energy internet employs more comprehensive power electronics and communication technologies, enabling the interconnection of various new and traditional energy sources, and effectively integrating renewable energy. As the core device in the energy internet, the energy router plays a role in energy transformation and distribution, facilitating multi-information interconnection and multi-energy exchange within the energy internet. At the level of distribution network, the energy router can realize the efficient access of various forms of energy and the flexible control and management, which is of great significance for the optimal operation of distribution network. Against this backdrop, this paper reviews the development and current research status of energy routers, systematically analyzes the typical topologies and related control technologies of multi-port energy routers and summarizes and forecasts key issues and future development trends, aiming to provide thoughts and reference for subsequent related research. [ABSTRACT FROM AUTHOR]

As the adoption of distributed energy resources (DERs) grows, the future of electricity distribution systems is confronted with significant challenges. These challenges arise from the transformation of consumers into prosumers and the resulting increased system complexity, leading to more pressure on the distribution grids. To address this complexity, a Digital Twin framework is designed to simulate DERs within distribution grids effectively. This framework is structured around four key modules: DERs, the electricity distribution grid, the energy management system, and the consumers. It incorporates a communication interface to facilitate interactions among these modules and includes considerations for grid topologies and demand-side configurations. The framework allows for the exploration of various DER adoption rates and capacities. The validation of this framework involves case studies on two Danish distribution grids with scenarios incorporating rooftop photovoltaic (PV) systems, batteries, and electric vehicles, considering different combinations of these technologies. The findings demonstrate the framework's ability to depict the states of the grid, PV systems, electric vehicles, and battery systems with a 10 min resolution over periods ranging from a day to over a decade. [ABSTRACT FROM AUTHOR]

This work aims to comprehensively analyze the cooperation of an electricity storage facility with an operating photovoltaic installation in a manufacturing company regarding the efficiency and effectiveness of the device and the economic profitability of the investment. This work aims to check the benefits that can be brought by expanding the PV system with an electricity storage facility. Based on the real energy balance and the characteristics of electricity distribution in the company, profitability calculations were carried out reflecting the expected savings generated by using individual solutions. These methods allowed the authors to calculate the market value of the investment with the assumed boundary criteria and to determine the economic effectiveness of the investment. Additionally, the practical process of selecting an electricity storage facility was presented and key moments in the company's energy report were analyzed, in which the use of a battery could bring results. Calculations showed that supplementing the described PV installation with an energy storage facility will increase the current level of self-consumption of PV energy by over 14%. The benefits translate into the final effect of energy storage operation, which brings additional annual savings for the company of approximately EUR 23,000 in the case of a weaker device and roughly EUR 40,000 in the case of a more powerful energy storage device. The proposed research could improve the planning of new industrial plants for photovoltaic installations, as well as the redesign of existing ones. [ABSTRACT FROM AUTHOR]

This study evaluated vegetation management (VM) strategies under electricity distribution lines (EDLs) through ecosystem service (ES) criteria. Deforestation, worsened by insufficient VM practices, poses a threat to ecosystem stability. Using a hybrid FAHP (Fuzzy Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, ten VM strategies were assessed based on 15 ES criteria. The FAHP results identified biodiversity, timber resources, and erosion control as the most crucial criteria due to their significant weights. The TOPSIS analysis determined that VM6 (creation and restoration of scrub edges) was the most effective strategy, achieving a value of 0.744 for reducing deforestation and enhancing energy security. VM6 helps preserve forest cover and protect infrastructure by creating a "V"-shaped structures within the EDLs corridor. This study underscores the importance of ES-oriented VM strategies for sustainable vegetation management and deforestation mitigation. It also highlights the need for incorporating scientific, ES-based decision support mechanisms into VM strategy development. Future research should expand stakeholder perspectives and conduct a comprehensive assessment of ESs to ensure that VM strategies align with ecological and socio-economic sustainability. This study provides a framework for improving VM practices and offers directions for future sustainable energy management research. This study focuses exclusively on ecological criteria for evaluating VM strategies, neglecting other dimensions. Future research should use methods like ANP and fuzzy cognitive maps to explore inter-dimension relationships and their strengths. Additionally, employing SWARA, PIPRECIA, ELECTRE, and PROMETHEE for ranking VM strategies is recommended. [ABSTRACT FROM AUTHOR]

This article examines the impact of meteorological conditions represented by ambient temperature, ambient humidity, wind speed, and daily precipitation sum on the reliability of low-voltage cable lines. Cable line reliability is crucial to the stability and safety of power systems. Failure of cable lines can lead to power outages. This can cause serious economic and social consequences, as well as threaten human safety, especially in the public sector and critical infrastructure. In addition, any interruption of cable lines generates costs related to repairs, operational losses, and possible contractual penalties. This is why it is so important to investigate the causes of power equipment failures. Many power system failures are caused by weather factors. The main purpose of this article is to quantify the actual impact of weather conditions on the performance and reliability of power equipment in distribution networks. Reliability indicators (failure rate, failure duration, restoration rate, and failure coefficient) for low-voltage cable lines were calculated as a function of weather conditions. Empirical values of the indicators were determined based on many years of observations of power lines operating in the Polish power system. An analysis of the conformity of their empirical distribution with the assumed theoretical model was also conducted. By quantifying the impact of specific weather factors on the operation of power equipment, it becomes possible to identify the ranges in which failures are most likely. [ABSTRACT FROM AUTHOR]

As new-energy electricity increasingly enters the post-subsidy era, traditional fixed feed-in tariffs and guaranteed purchase policies are not conducive to the optimal allocation of large-scale, high-proportion new-energy power due to the high pressure of subsidy funds and the fairness issues of power-generation grid connection. Encouraging new energy to participate in electricity market transactions is considered an effective solution. However, existing studies have presupposed the adverse effects of new energy in proposing market mechanism optimization designs for new-energy participation without quantitative results to support this, which is not conducive to a true assessment of the comprehensive impact of individual instances of new-energy participation in the market. To this end, this study, based on the actual experience and data cases of China's electricity spot market pilot provinces, considers both unit commitment and economic dispatch in the electricity distribution process, and constructs a two-stage optimization model for electricity spot market clearing. According to the differences in grid connection time and the construction costs of new-energy power, differentiated proportions of new-energy participation in the market and bidding strategies are set. By analyzing the quantitative results of new energy participating in spot market transactions under multiple scenarios, using both typical daily data for normal loads and peak loads, the study provides theoretical support and a data basis for the optimized design of market mechanisms. The research results show that there is a non-linear relationship between the scale of new energy entering the market and its bidding strategies and market-clearing electricity prices. In the transition phase of the low-carbon transformation of the power sector, the impacts of thermal power technology with a certain generation capacity and changes in the relationship between power supply and demand on electricity prices are significant. From the perspective of the individual interests of new-energy providers, the analysis of their bidding strategies in the market is important. [ABSTRACT FROM AUTHOR]

With the increasing number of distributed power sources such as photovoltaic power and wind power and electric vehicles connected to the grid, the structure and operation state of the traditional distribution network have undergone great changes. Therefore, through the establishment of a distributed power grid-connected evaluation system, it has become an important research topic to evaluate the access of distributed power and the carrying capacity of electric vehicles in the distribution network of new power systems. Firstly, the situation of distributed power supply and electric vehicles and the impact of grid connection are introduced. Secondly, the traditional distribution network carrying capacity evaluation method is studied and introduced. Then, the distribution network carrying capacity evaluation considering uncertainty is reviewed and investigated. Finally, in view of the lack of existing research, further research is needed, aiming to provide a reference for the realization of distributed power supply and grid-connected EV carrying capacity evaluation and a scientific basis for the future operation planning of distributed power supply and EV integration into the distribution network. [ABSTRACT FROM AUTHOR]

The studies on strategies for improving restoration times in electrical distribution systems are extensive. They have theoretically explored the application of mathematical models, the implementation of remotely controlled systems, and the use of digital simulators. This research aims to connect conceptual studies and the implementation of improvements and impact assessment in electrical distribution systems in developing countries, where distribution technologies vary widely, by employing a comprehensive methodology. The proposed research examines the restoration times for faults in substations within general distribution networks in the central–western region of Mexico. The study comprises these stages: (a) diagnosing the electrical supply, demand, and infrastructure; (b) analyzing the electrical restoration time and the restoration index of the substations; and (c) providing recommendations and implementing pilot tests for improvements in the identified critical substations. The results revealed 12 analysis zones, including 120 distribution substations, 150 power transformers, and 751 medium voltage circuits. Among the substations, 73% have ring connections, 15% have TAP connections, and 12% have radial connections. Additionally, 27% of the substations rely on only a single distribution line. The study identified areas with significant challenges in restoring electricity supply, particularly focusing on power transformers: 32 transformers with permanent power line failures requiring load transfer via medium voltage; 67 transformers requiring optimized restoration maneuvers due to specific characteristics; and 4 areas with opportunities to enhance the reliability of the power supply through remote-controlled link systems. The analysis resulted in the installation of 145 remote link systems, which improved restoration rates by over 40%. This approach is expected to be replicated throughout Mexico to identify improvements needed in the national distribution system. [ABSTRACT FROM AUTHOR]

The global energy sector is currently undergoing a significant transformation to address sustainability, energy efficiency, and grid resilience. Smart grids, leveraging advanced technologies like the power internet of things (PIoT), play a crucial role in this transformation. This research focuses on enhancing the efficiency, reliability, and sustainability of electricity distribution through IoT technologies. It envisions a system where interconnected devices, sensors, and data analytics optimize energy consumption, monitor grid conditions, and manage demand response scenarios. Central to this effort is the integration of PIoT into the smart grid infrastructure, particularly in implementing dynamic pricing strategies for demand response. Leveraging power line communication (PLC) techniques, this innovative approach facilitates real-time communication between grid components and consumers. The results demonstrate improved grid stability through dynamic load management, effectively responding to demand fluctuations, and minimizing disruptions. The deployment of dynamic pricing methods using PLC-driven schemes empowers customers by offering access to real-time energy use data. This access incentivizes energy-efficient behavior. leading to a 30% increase in the adoption of energy-saving techniques among consumers. A utility company pilot study claimed a 12% drop in peak demand after adopting time-of-use charges, with an accuracy rate of 98.87% in total. [ABSTRACT FROM AUTHOR]

The cost reflectivity of electricity distribution network tariffs has been debated in several countries, and various ways to enhance it have been investigated in recent years. However, the recent academic literature regarding the approach based on cost causation has a clear gap because no case studies show how distribution network tariffs can be determined in practice for large customer groups. This article offers a calculation methodology to determine distribution network tariffs based on cost causation along with a case study where unit prices are determined for the tariff structures still widely used today using the data for two separate network areas being operated by two Finnish distribution system operators (DSOs) in an unbundled electricity market environment. The results of the case study show that the total differences between the target and the realized turnovers in both investigated networks are smaller than 1%, which means almost a full cost recovery. In addition to traditional tariff structures, the proposed calculation methodology can also be modified to design and determine other pricing schemes. The need for systematic calculation processes is growing to improve the cost reflectivity of present tariffs and adapt to the needs of the evolving operating environment, novel tariff structures, and new emerging customer groups. [ABSTRACT FROM AUTHOR]

With the ongoing development of new power systems, the integration of new energy sources is facing increasingly daunting challenges. The collaborative operation of shared energy storage systems with distribution networks and microgrids can effectively leverage the complementary nature of various energy sources and loads, enhancing energy absorption capacity. To address this, a shared energy storage capacity allocation method based on a Stackelberg game is proposed, considering the integration of wind and solar energy into distribution networks and microgrids. In this approach, a third-party shared energy storage investor acts as the leader, while distribution networks and microgrids serve as followers. The shared energy storage operator aims to maximize annual revenue, plan shared energy storage capacity, and set unit capacity leasing fees. Upon receiving pricing, distribution networks and microgrids aim to minimize annual operating costs, determine leased energy storage capacity, and develop operational plans based on typical daily scenarios. Distribution networks and microgrids report leasing capacity, and shared energy storage adjusts leasing prices, accordingly, forming a Stackelberg game. In the case study results, the annual cost of MGs decreased by 29.63%, the annual operating cost of the ADN decreased by 11.25%, the cost of abandoned light decreased by 60.77%, and the cost of abandoned wind decreased by 27.79% to achieve the collaborative optimization of operations. It is proven that this strategy can improve the economic benefits of all parties and has a positive impact on the integration of new energy. [ABSTRACT FROM AUTHOR]

The current electricity default rates in continental countries, such as Brazil, pose risks to the economic stability and investment capabilities of distribution utilities. This situation results in higher electricity tariffs for regular customers. From a regulatory perspective, the key issue regarding this challenge is devising incentive mechanisms that reward distribution utilities for their operational and investment choices, aiming to mitigate or decrease electricity non-payment rates and avoid tariff increases for regular customers. Despite adhering to the principles of incentive regulation, the Brazilian Electricity Regulatory Agency (ANEEL) uses a methodological approach to define regulatory targets for electricity defaults tied to econometric models developed to determine targets to combat electricity non-technical losses (NTLs). This methodology has been widely criticized by electricity distribution utilities and academics because it includes many ad hoc steps and fails to consider the components that capture the specificities and heterogeneity of distribution utilities. This study proposes a fuzzy inference-based model for defining regulatory default targets built independently of the current methodological approach adopted by ANEEL and aligned with the principles of incentive regulation. An empirical study focusing on the residential class of electricity consumption demonstrated that it is possible to adopt a specific methodology for determining regulatory default targets and that the fuzzy inference approach can meet the necessary premises to ensure that the principles of incentive regulation and the establishment of regulatory targets are consistent with the reality of each electricity distribution utility. [ABSTRACT FROM AUTHOR]

Technical losses in electrical grids are inherent inefficiencies induced by the transmission and distribution of electricity, resulting in energy losses that can reach up to 40% of the generated energy. These losses pose significant challenges to grid operators regarding energy sustainability, reliability, and economic viability. Distributed Energy Resources (DERs) offer promising solutions to lower technical losses by decentralizing energy generation and consumption, reducing the need for long-distance transmission and optimizing grid operation. Hence, estimating the impact of DERs on grid technical losses becomes paramount for grid operators and planners. In response, this article proposes the application of regression modeling and nonlinear curve fitting algorithms to provide a more nuanced understanding and better characterize the intricate interplay between DER deployment and technical losses. Through a comprehensive case study based on more than 1080 computer simulations, we demonstrate the effectiveness of our proposed dynamic polynomial varying coefficient regression model in estimating the impact of DERs on technical losses within electrical grids. The proposed model offers a simple and effective methodology that allows grid operators to gain insights into the nonlinear dynamics of DER integration and make quicker and more informed decisions regarding grid management strategies, infrastructure investments, and policy interventions. Also, this research contributes to advancing the field of grid optimization by offering a simple equation that enhances our ability and haste to assess and mitigate technical losses in the context of an evolving energy landscape characterized by increasing DER adoption. [ABSTRACT FROM AUTHOR]

This work presents a production management platform developed to minimize the costs of the capacity charge, part of the electricity bill associated with the cost of maintaining grid capacity during periods of high, fluctuating loads. After a summary of the regulatory solutions on the capacity market in Poland, a capacity charge management system is presented, specifically designed for production facilities within the Energy-Intensive Industry sector. The proposed platform combines hardware data collection, a simulation tool analyzing the electrical energy demand profile to predict the future impact on the capacity charge, and a cloud-based user interface providing real-time recommendations to the plant operators regarding the corrective actions needed to minimize the cost of operation. It was pilot tested in collaboration with a large production facility in Poland, for which the capacity charge was among the main components of the electricity distribution costs. Pilot tests were conducted in the period from January 2022 to September 2023. The tested platform allowed us to shorten the time span of elevated capacity charges from 33% in the year 2022 to only 7% in the year 2023. It also reduced the benchmark capacity charge indicator by more than 11%, from 4.02% to −7.56%, over the duration of the experiments. This improvement was achieved without major changes to the organization and planning of the work. [ABSTRACT FROM AUTHOR]

In support of the global green transition, numerous policies have been introduced to efficiently address the increasing demand for reliable electricity. However, the impacts of these policies have received limited attention, despite the potential for unsuccessful policy targets to introduce inefficiencies into the energy system, subsequently diminishing societal wealth. This study bridges this research gap by conducting a comprehensive examination of a supply reliability incentive within electricity pricing regulation, aiming to contribute new insights for policy assessments. Analyzing data from all electricity distribution operators within a single jurisdiction, the study investigates the volume and distribution of economic steering to elucidate the overall societal impact. The findings suggest a rewarding system for positive developments in indices, regardless of the absolute interruption index levels, highlighting the importance of precise variable definitions in implementing incentive mechanisms. The assessment tools developed for this study will be valuable for further regulation and policy assessments. [ABSTRACT FROM AUTHOR]

There is a consensus within the scientific community regarding the effects on the environment, health, and climate of the use of renewable energy sources, which is characterized by a rate of harmful polluting emissions that is significantly lower than that typical of fossil fuels. On the other hand, this transition towards the use of more sustainable energy sources will also be characterized by an increasingly widespread electrification rate. In this work, we want to discuss whether electricity distribution and transmission networks and their main components are characterized by emissions that are potentially harmful to the environment and human health during their operational life. We will see that the scientific literature on this issue is rather limited, at least until now. However, conditions are reported in which the network directly causes or at least promotes the emissions of polluting substances into the environment. For the most part, the emissions recorded, rather than their environmental or human health impacts, are studied as part of the implementation of techniques for the early determination of faults in the network. It is probable that with the increasing electrification of energy consumption, the problem reported here will become increasingly relevant. [ABSTRACT FROM AUTHOR]