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In this short paper, we use machine learning methods to maximise the efficiency in the Hellenic Electricity Distribution Network Operator (HEDNO) S.A.'s project management by predicting which upcoming projects are going to be paid by the customer, thus enabling the company to fetch all needed materials in time, and to avoid unwanted delays in the operations of the company.

This paper focuses on the variance risk premium of project returns and its impacts on the real options to expand and to abandon a project. Variance risk premium measures the hedging costs associated with the time-varying variance of the returns. We find that the variance risk premium increases the real option value to expand and to abandon a project. Hence, the variance premium delays both abandoning and expanding the project. Our setting also enables us to study the multi-stage decisions with real options under the variance risk premium. For example, we consider when there is an abandonment or a re-expansion add-on attached to an expansion project, which is a reminiscence of how our framework facilitates modeling compound real option structures in the presence of the variance risk premium. We present two applications of our models that involve Ford Motor company and battery storage investments for electricity distribution networks. These cases demonstrate how the proposed framework in this paper can be applied to real world decisions, and, moreover, they establish a baseline for how much decisions can be improved when variance risk premium is included in the modeling.

Water and electricity distribution networks are two highly interdependent and critical infrastructures in the world today. This paper investigates the coupling of water and electricity distribution networks through the electrical energy demand of water pumps. Further, with additional variable renewable energy (VRE) sources in the distribution system, utilities face significant challenges stemming from the VRE stochasticity. In this paper, a coordinated operational model of urban water and electricity distribution networks is proposed. Stochastic VRE generation is handled by using a data-driven probability efficient point (PEP) method based on historical wind and solar datasets without the need for any probability distribution function. Case studies are performed on a modified Institute of Electrical and Electronics Engineers (IEEE) 13-node electricity distribution network coupled with a 10-node water distribution network, typical of a small-town setting. Results show the impact of coordinating water and energy networks on the cost of operation and the distribution locational marginal prices (DLMPs). The inclusion of water tanks as alternative storage devices in the electricity distribution network are shown to slightly reduce voltage violations, line congestion, and VRE curtailments in a case with high VRE penetration.

PurposeThe purpose of this paper is to describe a novel method to compromise between planned (regulated) maintenance and outage initiation and unplanned (unregulated) maintenance and to find an economic model using which one can perform maintenance adequately and in the most optimal state.Design/methodology/approachIn this paper, a system consisting of similar components is considered, and the role of each component in the system is explained. Then, the cost pertaining to failure in each asset is determined. Costs such as energy not supplied, penalties, human resources to resolve the defect and replacing assets are taken into account. Finally, a new comprehensive objective is proposed, and optimization is performed for a sample system.FindingsIn this paper, some graphs have been plotted from which plenty of information may be extracted. This is mentioned in the Conclusion.Originality/valueIn this paper, some graphs have been plotted from which plenty of information may be extracted. This is mentioned in the Conclusion.

This perspective paper is in line with an in-depth research on electricity distribution network (EDN) and role of resilience capability in development of EDN. The research was conducted during multi-objective project for developing resilient EDN in Guilan Province, Iran. To explore the theoretical aspect, resilience main factors of EDN were extracted from literature considering viewpoints of experts, after that, the set of factors were evaluated in electricity distribution units for obtaining practical findings by implementing an integrated framework. The results obtained by two comparative methodologies indicate the total resilience level in each unit according to the status of all resilience main factors. Also, an important part of findings relates to managerial implications, which include how to operate and enhance these factors, resulting in optimizing of overall resilience capability in the EDN. Therefore, this paper can be considered as a reliable basis for future studies to align theories with practices.

Advancement in technology has continuously driven the evolution of metering devices and infrastructure in the world and has resulted in more accurate and user-friendly devices equipped with customer interaction interfaces. The evolution of metering technology in Nigeria arose with the unbundling of the National Electric Power Authority (NEPA) but have not progressed smoothly and successfully despite the implementation of various reforms and policies in the Nigerian electricity industry. The persisting problems in the electricity distribution system such as energy theft, vandalism, energy wastage, high line losses can be overcome by the deployment of appropriate metering infrastructure. In the second quarter of 2020, the Nigerian Electricity Regulatory Commission revealed that the total registered customers and total metered customers are 10,516,090 and 4,234,759 respectively leaving a metering gap of 59.73%; after 124 years of commercial electricity availability in Nigeria. This paper discusses Nigeria's metering history and the challenges encountered in the transition of policies, technologies and government reforms. The paper also proposes the way forward to a successful transitioning into a smart distribution grid.

Nowadays energy demand is increasing speedily because of a rise in increase and way of the individuals. This leads to more issues in electricity distribution. In order to avoid such issues, a home energy management system (HEMS) has been introduced. HEMS represent the locations where energy is wasted in the homes and utilization of energy in a better way. A HEMS considers both energy generation and utilization and also provides two-way communications between the distribution centre and consumer. This paper displays a writing survey of the home vitality the board framework (HEMS). This review paper basically deliberates upon research papers related to the HEMS for different conditions and cases depending upon different climate conditions, different appliances, different controllers with algorithms, different home occupants and their living styles.

The distribution system reconfiguration (DSR) is a complex large-scale optimization problem, which is usually formulated with one or more objective functions and should satisfy multiple sets of linear and non-linear constraints. As the exploration of feasible solutions in large and nonconvex search space of DSR is typically hard, it is important to develop efficient algorithms and methods for finding optimal solutions for DSR problem in reasonably short computational times. In traditional DSR, the configuration of distribution network can be changed by opening and closing sectional and tie switches, where active power losses are minimized, while radial network configuration and supply to all connected loads are both preserved. Accordingly, this paper provides a comprehensive review of a number of existing metaheuristic reconfiguration methods and introduces a novel efficient genetic algorithm (efficient GA) for DSR with loss minimization. In order to demonstrate benefits and effectiveness of the proposed efficient GA for DSR, the paper also provides a detailed comparison of results with an improved genetic algorithm (improved GA) for several test systems and real distribution networks. The obtained simulation results clearly show higher accuracy and improved convergence performance of the proposed efficient GA method, compared to the improved GA and other considered reconfiguration methods.

To meet the growing demands of electricity, it is imperative to increase the efficiency of the distribution system and reduce all wastage of energy. In this paper, the data from the distribution companies and regulatory bodies are analysed to identify the inefficiencies existing in the electricity distribution to the agriculture consumers of the state of Gujarat inIndia. The primary causes for the inefficiencies in the system are the absence of effective monitoring and correct and reliable data on the usage of electricity by agricultural consumers, and the technical loss of electricity on account of low Power Factor and poor voltage regulation. The paper proposes a comprehensive solution to address the identifiedproblems by way of installing a Metering Reactive Compensation Unit (MRCU) independent of consumers’ energy meters. MRCU will contain capacitors for reactive compensation, relay and switching unit, metering unit for current, voltage, Kilowatt, KVARH and KWH, and LORA based communication module for 24x7 data capture. The data captured at the cloud level will be analysed by a head-end software system for real-time reports and corrective actions. The estimated monetary benefits from installing MRCUs for entire Gujarat’s agricultural consumers is estimated to be Rs 1500 Crore in a year, apart from an estimated energy savingof close to 2000 Mus per year. How to cite this article: Chandran DR, Marathe JC. Metering and Reactive Compensation Unit (MRCU) for Improved Energy Efficiency and Management - Supply of Electricity to Agricultural Consumers. J Adv Res Power Electro Power Sys 2020; 7(3): 11-21. DOI: https://doi.org/10.24321/2456.1401.202006

Rapid increases in distributed energy resources on distribution systems are prompting research efforts to improve and evaluate electric power distribution algorithms; however, there is a shortage of realistic, large-scale, U.S.-style test systems for the evaluation of such advanced algorithms. Some available tools to build large-scale test systems are of European style, and their application to studies focused on the United States might not be desirable given very different characteristics between the European and U.S. distribution designs. Motivated by this need, this paper develops detailed algorithms to build large-scale U.S. distribution systems and incorporates them in a new Reference Network Model, RNM-US. The approach starts with information from street maps and a catalog with electric equipment that includes power lines, transformers, voltage regulators, capacitors, and switching devices. The paper presents the algorithms through an illustrative case study of the different steps that comprise the process of building a synthetic distribution grid. Finally, the paper presents a medium- and a large-scale data set covering 10 million electrical nodes and 120,000 km of power lines, demonstrating the applicability of the proposed method to build very large-scale synthetic distribution systems.

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. It also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

PurposeThis paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.Design/methodology/approachSelf-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.FindingsThe proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.Research limitations/implicationsThe choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.Practical implicationsTo prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.Originality/valueTo the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Electric power and transportation networks become increasingly coupled through electric vehicles (EV) charging station (EVCS) as the penetration of EVs continues to grow. In this paper, we propose a holistic framework to enhance the operation of coordinated electric power distribution network (PDN) and urban transportation network (UTN) via EV charging services. Under this framework, a bi-level model is formulated to optimally determine EVCS charging service fees (CSF) for guiding EV charging behaviors and minimizing the total social cost. At the upper level, PDN with wind power generation is formulated as a second-order cone problem (SOCP) where CSF is determined. Given the settings calculated at the upper level, the lower level problem is described as a traffic assignment problem (TAP) which is subject to the user equilibrium (UE) principle and captures the individual rationality of single EV owners in UTN. The uncertainties in wind power output and origin-destination (O-D) traffic demands are considered in the proposed model and a deep reinforcement learning (DRL)-based solution framework is developed to decouple and approximately solve the stochastic bi-level problem. Both gradient-based and gradient-free training algorithms are implemented in this paper and the respective results are compared. The case studies on a 5-node system, 24-node Sioux-Falls system and real-world Xi’an city in China are conducted to verify the effectiveness of the proposed model, which demonstrates the enhanced operation of coordinated PDN and UTN networks by reducing the traffic congestion and improving the integration of renewable energy.

This paper examines the determinants of households energy demand and energy use in order to provide useful information on energy consumption pattern of Mubi metropolis in Adamawa State – Nigeria. The paper explore various energy sources such as traditional biomass, wood fuel, kerosene, LPG, solar, wind, and electricity and the willingness of the households to shift from one energy source to the other. Secondary sources of data were used extensively for this work and the data were collected from Yola Electricity Distribution Company Mubi branch (YEDC, Mubi) and NNPC depot Yola. The study utilizes econometrics methods of regression analysis and findings from the results shows that energy is the key factor to the welfare of the households and individual energy consumption majorly depends on households’ income and energy prices. This paper reveals that previous studies use limited economic models for analysing household energy consumption pattern which limits its scope of analysis. The paper suggest that there is a need to make a general awareness in Mubi on the importance of using clean energy sources like; LPG and Electric Cookers which improve health and non-hazardous because of the fact that negative relationship exist between household’s energy consumption and energy price.

Smart buildings form an integral part of the smart grid that lowers electricity cost. This objective can be achieved by using suitable enhanced algorithms and techniques. The motivation of this paper is the request for an economical decision-making system from a commercial company in Singapore. This paper presents an economical building management system (EBMS) concept inspired by the building management system and machine learning. EBMS improves the decision-making process through rule-based algorithm within the system. Machine learning algorithm is included as part of EBMS to enhance the computational calculation for the electricity distribution. It includes the function of self-making decision for purchasing electricity based on forecasting system for electricity price or real-time electricity price data when facility managers are not present. EBMS uses multiagent system to communicate, interact, and negotiate with multiple agents for energy supply and demand in the building. Simulation studies have shown the potential of EBMS concept to provide a cost reduction solution up to 61.42% savings for smart buildings. Better electricity purchasing contract option can be decided based on the forecasting system for building power consumption.

Background/Objectives: In the past couple of decades, several counties all around the globe, decided to conduct some reforms in the way that they manage the electrical power in their countries. Even in Middle East countries like Iran have taken the path to intensively privatize their power distribution and pass it over to the non-governmental sector paving way for security, social and economic threats. For this purpose, lack of proper and optimal management results in distribution companies and the government having to explain its threats so that sovereignty could eliminate the threats or reduce their effects. This study discusses the problems of restructuring the electric power sectors and its defects in Iran distribution companies. Methods/Statistical analysis: This paper discusses the problems of re-structuring the electrical power sectors and its defects in the distribution companies. Furthermore, this paper investigates the threats facing the privatization of electricity distribution companies. The threat of monopolization is also analysed in a separate section. Data source gathering is done during 2014-2016. Findings: Establishment of formal and legal framework in this regard is provided in such a way that the interests of all stakeholders, including shareholders, employees, subscribers, and government are provided. Application/Improvements: Establishment of formal and legal framework in this regard is provided in such a way that the interests of all stakeholders, including shareholders, employees, subscribers, and government are provided. Also, establishment of proper implementation of the privatization of electricity distribution companies in Iran. Keywords: Iran distribution companies, Electricity distribution company, Monopoly, Privatization, Distribution systems.

Purpose The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation. Design/methodology/approach Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier. Findings The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors. Originality/value This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

This paper is proposing a data-driven approach for fault location of distribution systems with distributed generations (DGs) by utilizing smart meters at low voltage (LV) networks and remote fault indicators (RFIs) at medium voltage (MV) networks. The determined fault location assists system operators with expedited service restoration, thus improving system reliability and resiliency. To quickly locate a fault, an enhanced escalation method is proposed to use outage reports from smart meters for prediction of the outage region. The determined outage region together with overcurrent notifications from RFIs with directional elements is jointly used to pinpoint the faulty line section. To this end, a new analytical model based on mixed integer linear programming (MILP) is proposed and each hypothetical fault location is modeled as decision variables. The result is an algorithm that is capable to support decision-making of single or multiple faulted line section(s) with incorrect and incomplete data from smart meters and RFIs for accurate fault location. In addition, an engineering way is presented to configure “power outage recognition time” of smart meters and logics for outage escalation are proposed in this paper. Simulation results based on a utility feeder validate the proposed methodology for fault location.

Purpose This paper aims to assess the impact of infrastructure development on Ghana’s economic growth. Design/methodology/approach Using data obtained from the World Bank’s World Development Indicators, the United States’ (US) International Energy Statistics and the Central Intelligence Agency’s (CIA) Factbooks from 1980 to 2016, an autoregressive distributed lag (ARDL) framework is used to determine the long- and short-run impact of the selected infrastructure stock and quality indices on Ghana’s economic growth. Findings Findings indicate a statistically significant relationship between infrastructure development and economic growth. Additionally, electricity-generating capacity is identified as the infrastructure stock index that has the greatest positive impact on Ghana’s economic growth. The study reveals that electricity-distribution loss has a significant negative effect over both long- and short-run periods. Research limitations/implications Commercial petroleum export from Ghana since 2010 has been a key contributor to economic growth. Although its aggregate effect is included in the annual GDP figures adopted for the study, the authors would have wished to assess its impact on GDP as an independent standard growth determinant. However, because of a lack of available data over this study period, petroleum exports could not be adopted as an independent standard growth determinant. Additionally, an aggregated index of infrastructure stock and quality could not be derived because of the small size of data available. Hence, this study did not assess its impact on Ghana’s economic growth. Practical implications The research provides pragmatic guidance to policymakers to focus their efforts on expanding electricity-generating capacity while simultaneously taking steps to curb electricity transmission and distribution losses. These two related actions offer the greatest positive impact on infrastructure development and, as a consequence, Ghana’s economic growth. Originality/value This paper represents the first attempt to empirically study the relationship between infrastructure development and Ghana’s economic growth. A key contribution to the existing body of knowledge includes strong evidence of a positive effect of infrastructure development upon Ghana’s economic growth. Results also reveal that the greatest positive impact on economic growth is derived from electricity-generation capacity. However, the study also uncovers a negative, but statistically significant, relationship between road and economic growth.

Electric power systems are experiencing a growing number of electronic loads in the residential sector as modern appliance technology progresses, and it has become increasingly more important to consider the total power factor (PF) of residential communities. This paper provides a survey based on literature and publicly available information of typical appliance PF values and effects at the residential level as well as a discussion on appliance energy use and corresponding operation schedules. A procedure for the calculation of equivalent PF is proposed and exemplified with minutely experimental data at 15-minute and hourly time intervals, which correspond to smart metering and traditional practices, respectively. The application of the proposed equivalent PF procedure in coordination with building energy modeling, may, in principle, be employed to determine PF for entire communities at an aggregated level. The paper includes a proposal to simulate reactive power through an approach that utilizes EnergyPlus, a building energy modeling software. Such simulation capability could facilitate improved planning for compensation implementation both in electric power distribution networks and in individual residences, which offers significant opportunity for energy savings.

In the future, active network management (ANM) and adaptive distributed energy resources (DER) control schemes will be increasingly required to fulfill growing power system resiliency and renewable generation integration needs. As part of future ANM schemes more frequent electricity distribution network topology changes could be utilized to improve the electricity supply reliability. However, these topology changes may require DER control methods and functions adaptation accordingly in order to maintain feasible power quality, voltage level and supply reliability in the distribution network. This paper presents a real-life case study from the needed adaptation of DER control schemes and functions after MV distribution network topology change from normal to back-up connection. The focus in the studied case is on MV network connected wind turbine (WT) control scheme adaptation after the topology change based on real measured data from the WT. In addition, the paper presents also simulations from potential future scenarios with centralized and distributed battery energy storage systems (BESSs) which could be also simultaneously utilized for the provision of local and system-wide services.

This paper describes a terminal for remote control of renewable energy sources powered station for electric vehicles charging. This terminal enables remote control of electric vehicle chargers, smart storage batteries, smart electricity meters, cash registers, as well as, remote control of renewable energy sources and other devices within the station. In this way, stations for electric vehicles charging powered by renewable energy sources, are made more accessible to electric vehicles users, to electricity distribution system operators, to supplier operators, to tax administration operators, and finally to users and owners of station for electric vehicles charging. In this paper, the realization of hardware and software of such terminal has been also described. Its development and commercialization would potentially encourage an increase in the use of electric vehicles powered by energy from renewable sources, which would decrease the level of air pollution as well as the negative effects it brings.

In India, because of socio-economic constraints, there is cross subsidy regime in electricity sector under that industrial consumers cross subsidize agricultural and residential consumers. This paper attempts to analyze the impact of cross subsidy on the industrial demand from the state distribution units. To measure the impact, elasticity of electricity demand in context of cross subsidy is estimated and to estimate cross subsidy elasticity, panel data techniques are used. The main finding of the paper is that the impact of cross subsidy on the Discom’s industrial load in is limited. The elasticity value of cross subsidy is -0.54, which is significantly lower than 1 (the perfectly elastic value), which means that change in cross subsidy does not have any meaningful influence on the electricity demand of the industrial consumers.Keywords: Cross Subsidy, Open Access, Electricity DemandJEL Classifications: H2, Q41, Q48DOI: https://doi.org/10.32479/ijeep.8111

This paper presents a Unified Power Flow Controller (UPFC) application of the Custom Power Active Transformer (CPAT); a power electronics integrated transformer which provides services to the grid through its auxiliary windings. The CPAT structure integrates three single-phase transformers into one shunt-series combining transformer. This integration empowers a sub-station with the capability of dynamically regulating the terminal voltage and current of a transformer through isolated power electronics converters. This paper investigatesthe CPAT’s capability to provide UPFC services which includes power flow control, reactive power compensation, voltage regulation and harmonics elimination. Simulations of the CPAT-UPFC with a stiff grid and a 5-bus power system demonstrates its functionality as an inter-bus couplingtransformer that provides the required grid services. Moreover, the impact of the CPAT-UPFC during load perturbations on the power system is investigated to further validate its transient and steady-state response. Furthermore, an experimental prototype reveals the operation of the three-phase CPAT-UPFC confirming its stable operation according to the theoretical expectations.

This paper presents an excerpt of a more comprehensive survey of smart grid systems on electric power distribution networks and its impact on reliability. The survey was carried out as part of the feasibility study in Nigeria to determine its enhance-ability on the smartness of a conventional (traditional) distribution network. A smart grid is not a single technology but multiplex technologies in which the combination of different areas of engineering, communication and energy management systems are done. Consequently, a comprehensive review of various approaches and their impact on reliability of the network is presented. Furthermore, this paper introduces the smart grid technology and its features, reliability impacts and emerging issues and challenges that arise from the smart grid system applications. The benefit of this comprehensive survey is to provide a reference point for educational advancement on the recently published articles in the areas of smart grid systems on electric power distribution network as well as to stimulate further research interest.

Voltage regulation issue in the distribution network is considered as a challenge that is associated with high penetration of the distributed generations (DGs). The widespread of the DGs led to influence the operation of the reactive power compensation (RPC) devices and the on-load tap-changers (OLTCs) and significantly affected the voltage profile. Therefore, obtaining the suitable control settings for the OLTC and the RPC should be reconsidered considering the impact of the DGs. This paper proposes a strategy for coordinating the operation of the OLTC and the RPC with DGs in the distribution networks. The proposed coordination strategy obtains the optimal values of the active power generated from the DGs, the reactive power injected from the switched capacitors (SCs), and the tap settings of the OLTC by using the multi-objective particle swarm optimization (MOPSO). The objective function is to minimize the total active power losses for all lines and the total voltage deviation for all nodes in the distribution network. The proposed coordination strategy is tested on the modified IEEE 33-node test feeder and a practical distribution feeder extracted from the North Delta Electricity Distribution Company in Egypt. A MATLAB code is built in this paper for simulation of the case studies and for determining the optimal parameters. A comprehensive comparison between the proposed MOPSO and the mixed-integer linear programming (MILP) method for different operating conditions of the distribution network is made. The results demonstrate that, the proposed strategy decreases the power losses, improves the voltage regulation and provides efficient coordination of DG with the voltage regulating devices; SCs and OLTC.

Purpose The purpose of this paper is to compare environmental performance of two shackle insulator manufacturing enterprises in India by evaluating and quantifying the life cycle environmental impacts in these enterprises using ISO 14040 guidelines. Design/methodology/approach All relevant life cycle phases – raw material, manufacturing, transportation and disposal – are considered. Primary inventory data for the two enterprises are collected through observations of processes at the sites. Ecoinvent 3.0 database is used as secondary data source. Process flow models are developed using Umberto software. ReCiPe impact assessment methodology is adopted to calculate environmental impacts in terms of endpoint categories of ecosystem quality, human health and resource availability; and midpoint categories of climate change, fossil depletion, human toxicity, metal depletion, ozone depletion, terrestrial acidification and water depletion. Findings This study has found that manufacturing phase followed by raw material extraction and transportation phases are responsible for most of the environmental impacts. This study also found that raw materials used in glaze preparation (manganese and ferrite), electricity, heavy fuel oil (C-9) and cotton have high environmental impacts in the manufacturing phase. Research limitations/implications The limitation of this study is that most of the inventory data are collected from only two manufacturing plants. Practical implications The researchers/enterprises can use the knowledge body for modelling and result comparison under different conditions. The enterprises can do the micro analysis of environmental effects of processes to improve environmental as well as economic performance. The government agencies can use the data for policy development and deployment. Originality/value The main contribution of the research is the creation of a knowledge body in the area of ceramic product environmental impacts. The paper provides inventory for the life cycle assessment (LCA) of shackle insulators using primary source (measured values) as no secondary data source is available for the shackle insulators. The inventory and results of this study can be used as reference for the future LCA studies in ceramic industry.

This paper examines the challenge of epileptic electric power supply in Nigeria since independence till date. The paper observes that a majority of Nigerians now pay excessively for darkness as they experience power outage for an average of 20 hours daily, while their estimated billing has continued to increase astronomically, unabated. This has impacted negatively on the socio-economic development of the country and is currently inciting conflicts between the electricity distribution companies and aggrieved consumers across the country. In view of the above, the paper identified some factors responsible for this ugly development and highlights some of its effects on Nigeria's economy. Data for the study was obtained through oral interviews with electricity consumers (especially in Ekiti, Osun and Oyo states) and officials of Ibadan and Benin Electricity Distribution Companies; personal observations; group discussion method; and a rigorous library search of related literature. The study employed the descriptive and analytical qualitative methods of historical research to analyse its data. It recommends that electricity supply should be given necessary attention by the government to enable the country harness her rich human and material resources.

Distribution systems losses are the major losses in electrical power systems. The main objective of this paper is to study the losses in Sudanese electricity distribution company (SEDC) networks. The paper works out a hypothesis that feeding customers’ directory form medium voltage will decrease the overall losses in the SEDC network. The paper began by running a simulating model to study the impact of eliminating the lowvoltage network of AL-Basher city’s losses, NEPLAN program was used to simulate the research problem. Two different models (A, B) were designed for Al-Bashir city network in Red Sea State, specifications and data were taken from Geographical Information System program (GIS); the tow is identical in loads, conductor’s length and total transformers capacities. The simulation result shows that the losses were decreased from 22.58% in case A to 5.46% in case B. These results reveal a very high reduction in losses reached 17.12% when customers were divided into small groups and each group feed by 15 KVA/ 11KV transformers as in model B.

The term "price volatility" is used to describe price fluctuations in asset prices. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. Volatility indicates a measure of price uncertainty in markets. When volatility rises, firms may delay investment and other decisions or increase their risk management activities such as hedging. The costs associated with such activities tend to increase the costs of supplying and consuming energy. The main goal of this paper is to build a volatility model and demonstrate a mechanism to forecast electricity price volatility using electricity distribution of EMCALI ("Empresses Municipals de Cali") in Colombian electricity market. The objectives of this study are threefold: 1) First we begin our approach by introducing the energy market in Colombia and EMCALI’s role in generation and distribution of electricity. 2) Next we discuss some of the more widely used time series techniques and also show how we can utilize generalized autoregressive conditional heteroscedastic (GARCH) volatility model as a volatility forecasting model for the energy price in Colombia. 3) Finally, we apply this model to estimate the behavior of the electricity price volatility and discuss the results obtained. The paper ends with conclusions.

In recent years, the penetration of decentralized wind power generation in distribution networks has increased rapidly, and the uncertainties in wind power generation has posed great challenges on the operation of distribution networks. To this end, this paper establishes a distributed coordinated optimization model of integrated electricity-gas distribution networks considering power-to-gas (P2G) units and gas turbines to deal with the uncertainties of wind power output. First, this paper uses chance constraints to deal with the uncertainties of wind power output and converts it into a linear model that is easy to be solved. Secondly, considering the electricity distribution network and gas distribution network as different stakeholders, optimization models are established with the objectives of minimizing their respective operating costs, and the established models are solved in a distributed manner through the analytical target cascading (ATC). Finally, an integrated electricity-gas distribution system composed of the IEEE 33-node distribution network and 24-node natural gas network is used for simulation, which validate the proposed model and method.

In this paper, the effect of raising the distribution system voltage level to 0.6 kV and 1 kV on the technical and nontechnical energy losses has been investigated. This investigation has been based on a case study in the Jordanian Electricity Distribution Company (EDCO) network. It presents technical and cost comparison between different distribution networks including different system typologies for the 0.4 kV, 0.6 kV and 1 kV distribution systems. The distribution network of Karak city in Jordan has been modeled using CYME software and updated with the grid data needed to perform the analysis, such as transmission line parameters and lengths; and transformers ratings. The study has been performed, firstly, by analyzing the current situation of the grid with 0.4 kV distribution voltage. Then the grid voltage has been raised to 0.6 kV and 1 kV to reduce the technical and non-technical energy losses. A comparative analysis between the current situation and the proposed two solutions concluded this paper.

Despite the National Grid expecting the number of electric vehicles (EVs) on UK roads to increase to 35 million by 2050 (2019 data), the effect of electric vehicle chargers (EVCs) together with steady-state cable faults on the total harmonic distortion of the LV electricity distribution network (EDN) has not been considered. Therefore, the purpose of this paper is to investigate the effect that increased numbers of EVCs have on the steady-state voltage total harmonic distortion (THDv) of a UK LV EDN under steady-state cable fault arrangements. Using MATLAB simulations, the study analysed the steady-state THDv of a UK suburban residential LV EDN with increased numbers of EVCs under phase-to-phase and open-circuit network conditions. It was found that on the LV EDN studied, phase-to-phase conditions can increase the THDv of the network significantly. Under the test conditions, the LV EDN was found to no longer comply with the Engineering Recommendation G5/4-1. This paper recommends that the number of EVCs connected to LV EDNs should be restricted, or harmonic reducing technology implemented to observe compliance with the G5/4-1. Further analysis should be carried out to verify the simulation and to determine whether the harmonics observed have a noticeable effect on equipment connected to a residential network.

The wasteful, non-efficient way and manner in which the small, available power energy in Nigeria is distributed and consumed especially by residential consumers, is such that it cannot grow the country sustainably. The result is that Nigeria will continue to remain a developing economy with the associated features. This paper examines the current electricity distribution and consumption scenario in Nigeria and also discusses the myriads of problems associated with the distribution and consumption of power energy in the country. Available data and findings presented in this paper show that distribution of electricity is bedeviled with high losses and is corruption ridden while consumption is wasteful and non-efficient. The paper makes some suggestions on the way forward for Nigeria to grow sustainably. The paper concludes that unless the current electricity distribution and consumption patterns are reversed and re-patterned, industrial and commercial advancement will continue to elude the nation. The paper recommends the way forward on how to re-position the power energy sub sector of the economy so as to achieve sustainable national development. Keywords: Power energy; Power energy consumption; industrial and commercial development; Sustainable national development; Renewable electricity

Electric power distribution system are usually unbalance. Therefore, a power flow method that can handle the three-phase configuration of the power system is needed so that the system planning and operation can properly be carried out. In the case of three-phase distribution system power flow analysis, for each system bus (except for substation bus), the voltage magnitude and angle of the three phases must be calculated. These calculations are carried out under certain loading conditions. After these voltages have been calculated, the electric power flows and losses in the distribution lines, and the substation power can also be determined. This paper proposes a new technique for three-phase distribution system power flow analysis using sequence components. The new formulation for the power flow problem in terms of sequence components is also proposed and developed in this paper. The application of sequence components has the advantage that the size of the problem can effectively be reduced, and solution to the power flow problem will be easier to find. Case study using a representative distribution test system confirms the validity of the proposed method where comparative studies between the proposed (i.e. sequence components based) method and the phase components based method are carried out.

With the proliferation of distributed energy resources and advanced metering, modern electric power distribution systems require more simulation and engineering analysis to ensure that the planning and operation of the evolving feeders are efficient and reliable. Although distribution analytical and operational tools are widely available, their usage by utility engineers has been particularly difficult because of the huge effort required in massaging the data available from their enterprise systems into the unique database requirements for each analytical tool. This paper presents a data modelling and application usage framework for utilities that utilizes the Common Information Model (CIM) to standardize and integrate data directly available from the utility enterprise database. The paper describes this framework’s approach in standardizing a utility’s distribution data and storing it in a large database of high fidelity CIM models which can then be used as input to any analytical tool that can accept data in a CIM structure. This is demonstrated by using this CIM-based integration framework for Avista Corporation to translate data in the CIM structure into a distribution model of GridLAB-D, which is an open source distribution system simulator. The results from GridLAB-D are presented to show that many proprietary distribution analytical and operational tools can be made inter-operable if the utilities adopt such a CIM based data platform as a standard for distribution data.

In 2010, South Africa introduced the Renewable Energy Independent Power Producer Procurement Programme to invigorate low-carbon energy generation using renewable energy resources. Amongst the development of wind and hydro plants; solar photovoltaic plants then took off rapidly. The volume of solar PV plants connected to the grid in 2015 and 2016 was unparalleled. However, the solar PV electric power distribution network is challenged with the presence of unacceptable harmonics and distortion content at the point of common coupling due to the switching action of inverters and operation of non-linear loads. It therefore essential to precisely estimate the resultant increased load losses in order to estimate the hot spot temperature and total losses during service.In order to demonstrate the significance of these challenges, this paper provides a comprehensive harmonic analysis of an oil-filled transformer for the supplied geometrical data and harmonic spectrum of an oil-filled transformer. The load losses are evaluated under fundamental and harmonic conditions. The load losses are classified into I2R and stray losses. The I2R losses can be easily obtained by analytical calculations and also through practical measurement. On one hand, analytical calculation of the stray losses cannot give an optimized estimation and practically their immeasurable. In this paper, a 2D FEM model that is dynamic to any transformer geometrical data is developed to produce a pragmatic loss estimation by using knowledge of the magnetic flux density. Generally, analytical formulations neglect the radial magnetic flux density component. During operation, this component becomes predominant towards the winding ends and cannot be disregarded.

With the development and popularization of electric vehicle (EV), impacts of large-scale of EV charging to the power system have emerged, especially to the distribution systems. Most of the electricity distribution infrastructure was designed before EV is developed, so most of the existing distribution transformers did not consider the load of the EV charging stations. The large-scale un-coordinated charging EVs can cause the overload or damage of the distribution transformers. Therefore this paper developed a real time control system which monitor the load of the distribution transformers in real time. If it is overloaded, the control system then sends a control command to the charging piles to reduce the output power of the charging piles in order to reduce the overload of the distribution transformers. The coordinated control strategy for electric vehicle charging piles is discussed in the paper. The control strategy under various operation conditions are analyzed. Based on the control strategy, the power output of the charging pile is optimized according to the real-time operation data such as the distribution transformer load, the load of each charging pile and the operation status of the charging piles. Finally, the simulation of cases is performed. The results show that the coordinated control strategy is effective in preventing overload of distribution transformers. It is believed that the control system developed can solve the difficulties of building charging station in old districts and in dense urban areas, where the existing distribution transformers have the risk of overloading during peak demand times.

Traditional restructuring of power markets has focused on legally separating monopolistic transmission and distribution infrastructure with sufficient regulatory oversight to ensure non-discriminatory access to networks, and transparent and cost-reflective tariffs. There is consensus that ownership separation for transmission assets is beneficial for competition and transparency. However, at the distribution level the benefits of going beyond legal unbundling are questionable. This paper reviews the theoretical arguments for ownership unbundling and summarises the findings from 23 academic papers and consulting reports. In addition, this paper empirically demonstrates that forced distribution ownership unbundling in New Zealand (from 1998) and the Netherlands (from 2009) did not increase retail competition and did not increase network quality. It resulted in significant one-off and structural costs. The combination of increasingly active distribution networks with bi-directional power flows from distributed renewables, in combination with the digitalisation of energy supply and creation of distribution data platforms, suggests that interaction between networks and customers, traditionally separated from a regulatory and competition perspective may become more interlinked in future. Policymakers should therefore assess a broader set of policy measures, taking into account this changing network landscape, when focusing on increasing retail competition and network quality.

This paper presents the evolution and development trends of the distributed control systems (DCS) implemented in the Electrical Power Systems, highlighting the impact of the modern versus traditional DCS systems. The principles of the modern DCS systems presented in this paper can be found implemented in Romania in the Transmission and Distribution energy sector, implemented by the Romanian Transmission and System Operator CNTEE Transelectrica SA and, as well as the electricity distribution operators like Electrica, EoN and CEZ.

The South African government policy to electrify all customers has placed immense demands on the electricity infrastructure. Several new connected customers in line with these government targets and plans are in networks that are already constrained, with the consequence of violating statutory performance requirements and electrical parameters, such as thermal loading, voltage limits and technical losses. Utilities' solutions to remedy these problems sometimes requires huge investments to upgrade infrastructure and this may take years for implementation. In many instances, short-term solutions are available and feasible. This study investigates Solar Roof-Top PV (RTPV) as a renewable energy resource for reticulation (11/22KV) networks. Currently RTPV is not well documented and guided when considering available Grid codes, Guidelines and Standards. This paper demonstrates that RTPV penetration is more worthwhile to consider than capital strengthening/refurbishment projects. The study demonstrates the supportive role of RTPV to meet electrification demands. With increased penetration of RTPV's on distribution networks, there is a benefit to the feeder tail-end voltages with reduced thermal loading and technical losses in distribution networks. This provides Utilities with the opportunity to electrify more customers and defer capital expenditure, while reducing the carbon footprint. The balance of the paper presents an accurate view of RTPV analysis, attributed to the accuracy of data, by using a practical network topology coupled with its related statistical loading. It further takes into account the associated customer connected at the LV transformers. With the imminent influx of RTPV, the results of this study will assist in equipping the South African Electricity Supply Industry (ESI) for the readiness of RTPV and the influence of RTPV on reticulation networks by quantifying the impacts and expectations for the Electric Power Utility and the customer.

An attractive way to reduce losses in electric power distribution networks is addressing the network reconfiguration problem, which should give a topology for the primary distribution network that minimizes the total losses due to the electrical resistances in the lines and complementary equipment’s ( technical losses ). Distributed energy resources and additional innovations associated to smart grids allow enhancing the benefits of finding better network topologies. On the other hand, the integration of renewable energy sources with variable random outputs requires expanding the perspective in modeling the network reconfiguration problem and in the shaping of appropriate solution techniques. These issues are the object of this paper. The main new features of the problem are explored with a maquette designed to highlight the consequences of random generation sources in the networks. Following, the paper proposes a formulation for the problem that explicitly considers random energy sources. A state of the art genetic algorithm build under the biased random-key evolution framework (BRKGA) is developed to address this hard combinatorial optimization problem. Case studies with benchmark networks put into perspective the proposed methodology. Results show that random energy values should be explicitly modeled in contemporary approaches to the network reconfiguration problem. The paper provides the grounds for addressing this new problem and points to additional research paths in the area.

The decision to proceed with a distribution engineering expansion project is often preceded by some form of cost to benefit analysis. The Kaldor–Hicks compensation principle is a criterion that assists in this analysis by the evaluation of net present value over the expected project life. This paper discusses this principle applied to power distribution systems. A probabilistic formulation is proposed to capture uncertainty in cost and benefit data. In effect, the approach models ranges of value of project parameters. While the method does not determine whether to proceed with a given project, it does give a measure of the value of the engineering economic efficiency. The method is especially valuable for cases of “next generation” systems, and this is illustrated in this paper.

The objective of this work is to detect what problems of inefficiency electricity distribution companies have, in order to disseminate this information and to allow distributors and public agencies to be more precise in calculating their costs. In turn, this will have an indirect impact on the price of the kilowatt in order to try to reduce its volatility. It should be noted that the volatility of the kilowatt price is mainly due to distribution costs and more specifically to access tolls. In the present paper, knowing that the distribution activity is a regulated activity, the efficiency in the electricity distribution companies will be studied. To this end, a study has been carried out on the efficiency of the main electricity distribution companies in Spain (Endesa, Iberdola, Union Fenosa, EDP and Viesgo) during the period of 2006–2015. The technique used was the Multi-period efficiency measurement in Data Envelopment Analysis, an input-oriented model at constant scales, working with panel data. The conclusions in this paper indicate that Spanish electricity distribution companies could improve their levels of efficiency if they improve the use of some inputs. This analysis demonstrates that overcapacity and deficit tariff have a negative influence on the efficiency level. Finally, this paper is useful as it shows that regulation again plays an essential role in regulated activities, requiring a commitment on the part of the State in order to improve efficiency in regulated activities.

Asset management and automation are acknowledged by distribution utilities as a useful strategy to improve service reliability, but the challenge facing decision makers is how to maximize the long-term return on a project whilst minimizing the investment and operation costs. The objective of this paper is reliability improvement by installing the optimum number of sectionalizing switches at appropriate locations in an electricity distribution network. This is achieved by adding new switches and the relocation of existing switches. Determining the number and location of switches become an optimization problem efficiently solved using an ant colony optimization (ACO) algorithm. The performance of this approach is assessed in the paper and illustrated using various case studies on a typical UK distribution network. Test results show that the proposed ACO methodology provides an optimum solution based on a trade-off region between the reliability indices and cost of multiple switches.

The main purpose of this research paper is to investigate the long-term effects of the proposed demand-side program, and its impact on annual peak load forecasting important for strategic network planning. The program comprises a particular set of demand-side measures aimed at reducing the annual peak load. The paper also presents the program simulations for the case study of the Electricity Distribution Company of Belgrade (EDB). According to the methodology used, the first step is to determine the available controllable load of the distribution utility/area under consideration. The controllable load is presumed constant over the analyzed time horizon, and the smart grid (SG) infrastructure available. The saturation of positive effects during intense program application is also taken into account. Technical and economic input data are taken from the real projects. The conducted calculations indicate that demand-side programs can bring about the same results as the energy storage in the grids with a strong impact of distributed generation from variable renewable sources (V-RES). In conclusion, the proposed demand-side program is a good alternative to building new power facilities, which can postpone investment costs for a considerable period of time.

Energy losses represent one of the main challenges for electric power distribution utilities all over the world. Several papers presented different methods for estimating technical losses (TLs) in distribution networks. Due to load variation during normal operation, load factor (LF) and loss factor (LSF) coefficients are considered. In this paper, the effect of repairing fault periods (RFPs) on calculating the TLs for medium voltage feeders of ring distribution network is presented. For emphasizing this effect, comparisons between TLs calculation considering only normal operation period (NOP) and considering both NOP and RFP are introduced. A proposed factor is suggested to be inserted into equations of TLs calculation to express the effect of RFPs. A proposed formula is introduced to calculate the new factor depending on repairing fault hours over the year. An actual ring distribution network in Egypt is chosen for evaluating the proposed study according to real data and measurements.

Uncertain and potentially harsh operating environments are often known to alter the operational performance of a system. In order to maintain system performance while coping with varying operating environments and potential disruptions, the resilience of engineered systems is desirable. Engineering systems are often interconnected in a dimensional way inherently from basic components to subsystems to the system of systems, which poses a grand challenge for system designers to analyze the resilience of such a complex system. Moreover, further complications in the assessment of resilience in the engineering domain are attributed to time-varying system performances, random perturbation occurrences, and probable failures caused by adverse events. This paper presents a dynamic Bayesian network (DBN) approach for the modeling and predictive resilience analysis for dynamic engineered systems. With the inter-time-slice links and the conditional probability tables in a DBN, the system performance could be molded as changing in a discrete time slice, while capturing the temporal probabilistic dependencies between the variables. An industrial-based case study of an electricity distribution system is further studied to demonstrate the effectiveness of the DBN approach for resilience analysis. The approach presented in this paper hopes to aid in realizing resiliency in system designs and to pave the way toward enhancements in developing resilient engineered systems.

In this paper an analytical approach is conducted to evaluate the droop control method in an islanding microgrid. Droop control is the key solution for sharing the demand power between generators in autonomous microgrids where there is no support from the electricity distribution grid. In the paper, three important load types are investigated to verify the droop control performance. First, coupling of active power and reactive power is considered in the microgrid and a new method is proposed to facilitate separate control of powers. In the proposed method the effects of droop gains on decoupling of active power and reactive power control, voltage regulation, power oscillation and system stability are studied. In the second load type study, by applying the different types of faults, induction motor characteristics are observed. By simulation results it is shown that the fault intensity and duration will determine how the microgrid attains to fast frequency convergence and how fast protection system operation can improve system stability. In the third case, imbalanced nonlinear load is studied in the microgrid and the influences of embedded controllers on harmonic distortion, system balance and voltage regulation are observed.

Purpose This paper is aimed to evaluate recently privatized 18 electricity distribution and retail companies, using the data and conditions at the time they were privatized. The main hypothesis of the study is that most of the privatized companies in this research are underpriced similar to previous experiences in developed and emerging economies. Design/methodology/approach Values of the companies are calculated considering the formal procedures of Turkish energy authorities. These companies are valued under the base, moderate and extreme scenarios created from different sets of assumptions considering conditions and existing data at the time they were privatized. Discounted cash flows (DCF) methodology is used in the estimations. The market prices obtained in their privatization tenders are compared with those theoretically calculated values (intrinsic prices). Findings The findings reject the hypothesis and indicate an overpricing in general in the privatizations of Turkey. Even the extreme scenario which gives the highest intrinsic values supports the findings. Research limitations/implications Research is limited with 18 regional electricity distribution company in Turkey. Originality/value The paper is one of the initial empirical studies on the valuation of energy companies using DCF methodology in an emerging market.