Electric Power Utilities Research Articles

Erratum to “Systematic Development of Short-Term Load Forecasting Models for the Electric Power Utilities: The Case of Pakistan”

Erratum to “Systematic Development of Short-Term Load Forecasting Models for the Electric Power Utilities: The Case of Pakistan”

Influence of the Economic Efficiency of Built-Up Land (EEBL) on Urban Heat Islands (UHIs) in the Yangtze River Delta Urban Agglomeration (YRDUA)

Currently, an urban agglomeration is a trend in global urbanization. With the continuous development of urban agglomerations, Chinese urban agglomerations have entered an era of high-quality development. Improving the economic efficiency of built-up land (EEBL) and maintaining a good ecological environment are important for promoting the high-quality development of urban agglomerations. Urban heat islands (UHIs) are one of the major ecological environmental problems affecting urban agglomerations. Therefore, it is meaningful to investigate the influence of the EEBL on UHIs in urban agglomerations. Based on the land-use data, MODIS land surface temperature (LST) data and gross domestic product (GDP) in the secondary and tertiary industries from 2000 to 2018, and electric power consumption data in 2018, this paper analyzed the influence of the EEBL on the surface urban heat island intensity (SUHII) in the Yangtze River Delta Urban Agglomeration (YRDUA). The results showed that most of cites in the YRDUA experienced rapid EEBL growth and a significant increase in heat island intensity from 2000 to 2018. There has been a significant positive correlation between the EEBL and the SUHII over the years, among which the EEBL had the strongest correlation (R = 0.76, p < 0.01) with the SUHII in 2000. Moreover, among the 27 cities in the YRDUA, 21 cities showed a significant uptrend of the SUHII with rising EEBL and the uptrend was significantly and negatively correlated with the electric power utilization efficiency (EPUE) of the secondary and tertiary industries (R = −0.6, p < 0.01). These results indicated that the EEBL of the secondary and tertiary industries had a significant influence on UHIs, which also reflected the significant influence of anthropogenic heat on UHIs to a certain extent. The findings of this paper can provide a scientific basis for mitigating the UHIs caused by the rapid economic development and promoting the high-quality development of urban agglomerations.

Hydrogen energy and large scale hydrogen production with nuclear power plants based on high-temperature reactors

At the present moment resource and ecological issues and challenges related to energy supply have become more acute. Key contradiction lies between constantly growing energy consumption and need for CO2 emission reduction. In the search of the solution hydrogen plays significant role as multi-purpose energy source and accumulator for transport, electric power, industry, distributed generation and public utility. It is expected that hydrogen energy development will benefit for the world’s energy system, environment and economy. Hydrogen may be used as pure fuel for transport and independent energy sources based on fuel elements. Global demand for hydrogen is expected to increase due to the growth of its consumption as a chemical agent in oil processing, petrochemical, chemical, metallurgic and other industries. In developed countries more than 80 % of hydrogen is derived from natural gas and petrochemicals. Large-scale hydrogen production is mainly accomplished by steam methane reforming. For natural gas saving and combustion products emission elimination steam methane reforming technology with heating from high-temperature gas cooled reactors (HTGR) is suggested. In 2018 hydrogen energy was declared as high priority area for scientific and technology development of Rosatom State Corporation. This area is integrated to the Comprehensive program project “Technology and scientific research development in nuclear energy of Russian Federation” and aims at design and demonstration of key technological solutions for nuclear hydrogen energy for large scale ecologic hydrogen production with heating from HTGR, hydrogen consumption infrastructure and integration of hydrogen energy into the economy. “Hydrogen energy” program implementation will diversify nuclear power non-electric applications.

Analysis of electric distribution utilities efficiency levels by stochastic frontier in Brazilian power sector

The regulatory power sector model in several countries determines tariff review forms based, among other things, on sharing efficiency gains with consumers. As these reviews have an important impact on consumers and distribution utilities, it is necessary that the adopted methodologies always be improved. To this end, this article assessed a Bayesian inference application in order to estimate a stochastic cost frontier considering temporal efficiency dynamics. Taking this point into consideration is essential, since studies carried out to assess power sector efficiency have neglected the fact that part of efficiency increases originate from scale gain due to market expansion, which occurs over time. The sample assessed herein is composed of panel data from 61 electric power utilities between 2003 and 2016. The results demonstrate that the tariff review is positively affected by distributor efficiency.

Development of a Wavelet – ANFIS Based Fault Location and Identification System for Underground Power Cables

Transmission lines are the backbone of electrical power systems and other power utilities as they are used for transmission and distribution of power. Power is distributed to the end-user through either overhead cables or underground cables. In the case of underground cables, their propensity to fail in service increases as they age with time. The increase in failure rates and system crashes on older underground power cables now negatively affect system reliability and involve numerous losses. It is therefore easy to realize that the consequences of this trend need to be managed [3]. Identification of the type of defects and their locations along the length of the cables is vital to minimize the operating costs by reducing lengthy and expensive patrols to locate the faults, and to speed up repairs and restoration of power in the lines. In this study, a method that combines wavelets and neuro-fuzzy techniques for fault location and identification are proposed. For this methodology a power transmission line model was developed and different fault locations were simulated in MATLAB/SIMULINK, and, as an input to the training and development of the Adaptive Network Fuzzy Inference System (ANFIS), certain selected features of the wavelet transformed signals were used. Fault index obtained from wavelet transformation are used as input variable for fuzzy input block function. Different membership functions were observed within input block function. As per formulation of rules, for membership function, the output value of the defuzzifier component was decoded to give a crisp value of ANFIS output. ANFIS results were compared with actual values. A comparison of the ANFIS output values and the actual values show that the percentage error was less than 1%. Thus, it can be concluded that the wavelet-ANFIS technique is accurate enough to be used in identifying and locating underground power line faults. Which will help in solving this time taking and tedious problem more efficiently and thereby reducing human effort in finding the type of fault and its location.

An In-Situ Assessment of Wood-in-Service Using Microwave Technologies, with a Focus on Assessing Hardwood Power Poles

Simple SummaryBoth termites and decay fungi use wood as a food source. Termites and decay cause major damage and inflict significant costs on human societies around the world. Currently, power pole testing techniques either involve a subjective evaluation, based on the sound that the pole makes when it is hit by a heavy hammer, or observing wood shaving from holes that are drilled into the core of the pole itself. Drilling is destructive and compromises any protection from wood preservative treatments, allowing termites or decay fungi to enter the pole. This project developed a simple, objective measurement technique, which is based on the transmission of very low power microwave energy through the wood. Two versions of the system were developed, and both could easily distinguish between sound hardwood poles and those which were compromised by decay and termite attack, without compromising the pole’s integrity in any way. These will be of enormous benefit to the power utility industry.Wooden power poles and their ongoing inspection represent a significant investment for most electrical power utilities. This study explored the potential for using microwave fields to non-invasively assess the state of hardwood power poles in a field experiment. Two strategies were assessed: 2.4 GHz microwave field transmission through the pole; and mutual coupling between antennae using a 10.525 GHz radar module applied to the surface of the pole. Both systems distinguished between sound hardwood poles and those which were compromised by decay and subterranean termite attack and infestation.

Maximum power point tracking supported proton exchange membrane fuel cell based intelligent dynamic voltage restorer

In modern era, electrical power utilities are more concerned about power quality. In this endeavour, dynamic voltage restorer (DVR) provides adequate support to the system. Accordingly, the present work illustrates intelligent hybrid control mechanism for DVR. Artificial neural network (ANN) is incorporated to obtain real-time optimal gains under distinct voltage situations. Closed loop type 2 fuzzy logic (CLT2-FL) is also realized in order to assist the ANN supported unit concomitantly. In order to enhance the potential of the present DVR, a CLT2-FL controlled maximum power point tracking (MPPT) based proton exchange membrane fuel cell arrangement is also explored in the present study. CLT2-FL module is adopted in DC-DC converter topology to provide simultaneous supply to the loads at different and regulated voltage levels. Consequently, the results are evaluated and compared to the state-of-the-arts which unveil the efficacy of the implemented controller against the oddity seen in the voltage waveform, thereby, exhibiting better voltage regulation and less harmonics. The effectiveness of the implemented MPPT unit from the viewpoints of convergence speed and oscillations is also established.

Cost and load forecasting by an integrated algorithm in intelligent electricity supply network

The smart electricity network and generation of power through distributed units require novel improved forecasting methods. In a restructured energy industry, electricity consumption and cost forecasts serve as two fundamental factors. Nevertheless, a dynamic price determination method is proposed in smart electricity network, where users may be capable of responding to continuously changing cost signals by shifting electric power utilization from expensive hours to cheap ones, which would accordingly influence electric power costs. Therefore, cost and load signals are powerfully linked, and traditional isolated prediction models could be inefficient. A novel two-sided wavelet transform (TWT), a revised mutual information (RMI)-based feature selection, a novel least squares versions of support vector machine (SVM)-based multi-input multi-output (MIMO) model, and improved particle swarm optimization (PSO) algorithm are constituents of the suggested prediction algorithm. Take into account that modeling the association between cost and load based on two prediction phases is carried out by MIMO model. Also, optimizing least squares versions of SVM parameters is performed by improved PSO. High precision of electric power cost and load forecasting arises from utilization of certain real-world markets to assess the proposed model.

Predictive Control for Microgrid Applications: A Review Study

Microgrids need control and management at different levels to allow the inclusion of renewable energy sources. In this paper, a comprehensive literature review is presented to analyse the latest trends in research and development referring to the applications of predictive control in microgrids. As a result of this review, it was found that the application of predictive control techniques on microgrids is performed for the three control levels and with adaptations of the models in order to include uncertainties to improve their performance and dynamics response. In addition, to ensure system stability, but also, at higher control levels, coordinated operation among the microgrid’s components and synchronised and optimised operation with utility grids and electric power markets. Predictive control appears as a very promising control scheme with several advantages for microgrid applications of different control levels.

Forecasting annual electricity consumption in China by employing a conformable fractional grey model in opposite direction

Electric power makes a significant contribution to economic development. Predicting annual electricity consumption is becoming increasingly crucial for electric power utility planning and economic development. To address this problem, a novel conformable fractional grey model in opposite direction is presented to predict annual electricity consumption in China. Firstly, the computational formulas for the novel model are deduced by grey modelling method and the effectiveness of the novel model is proved by matrix perturbation theory. Secondly, the optimal parameters are determined by quantum inspired evolutionary algorithm. Thirdly, two empirical examples are taken to validate the prediction accuracy of the novel model. Finally, the proposed model is applied to predict electricity consumption of Beijing, Fujian and Shandong. The results show that the novel model is superior to other six competitive models. Besides, electricity consumption of these regions in next five years are predicted, which can well serve a benchmark research and provide a relatively reliable reference for economic and electric sectors.

Automated Identification of Electrical Disturbance Waveforms Within an Operational Smart Power Grid

Electric power utilities employ “smart” re-closing devices capable of capturing electrical disturbance (ED) waveforms in real-time. These waveforms are digitally sampled, transmitted back to the utility, and stored in text files that comply with the IEEE COMmon format for TRAnsient Data Exchange (COMTRADE) standard. An average of 2,100 ED events are recorded, by 850 devices, on a monthly basis within Electric Power Board's distribution network. Due to operational restraints such as: time, money, and person power, only 2% of these recorded events are currently analyzed by power utility personnel. The remaining 98% of recorded events remain a significant loss in information, which could be vital in fully understanding the operating condition within the distribution network. This work presents a hierarchical automated classification process that assigns ED events into one of three “categories”: valid data, switching events, and faults/power quality (PQ) disturbances. This process correctly assigned 92.9% of the tested 140 COMTRADE files into one of these categories. In addition to this categorization, this work presents an automated approach for the classification of magnetic inrush events. A classification rate of 90.63% is demonstrated using 32 transformer inrush COMTRADE files.

Factors for Measuring Photovoltaic Adoption from the Perspective of Operators

The diffusion of photovoltaic distributed generation is relevant for addressing the political, economic, and environmental issues in the electricity sector. However, the proliferation of distributed generation brings new administrative and operational challenges for the sustainability of electric power utilities. Electricity distributors operate in economies of scale, and the high photovoltaic penetration means that these companies have economic and financial impacts, in addition to influencing the migration of other consumers. Thus, this paper aims to systematically identify and evaluate critical factors and indicators that may influence electricity distributors in predicting their consumers’ adoption of photovoltaic technology, which were subjected to the analysis of 20 industry experts. Results show that the cost of electricity, generation capacity, and cost of the photovoltaic systems are the most relevant indicators, and it is possible to measure a considerable part of them using the internal data of the electricity distributors. The study contributes to the understanding of the critical factors for the forecast of the adoption of consumers to distributed photovoltaic generation, to assist the distribution network operators in the decision making, and the distribution sustainability. Also, it establishes the theoretical, political, and practical implications for the Brazilian scenario and developing countries.

Phasor measuring unit calibration considering topology expansion of electric power utilities

Phasor Measuring Units (PMU) is considered as a feasible alternative for power system data communication and for the preparation of smart grid. To operate multiple PMUs in stable mode, synchronization is a much essential procedure. After examining the concise literature survey on topical PMU applications, this paper step ahead by considering prevailing objectives such as: extension of network topology and PMU calibration considering bias errors. The appropriate deployment of PMUs and intimidating situation influence the reliance on physical configuration. Hence, it is obligatory to extend the topology of the networks. Also, calibrating the PMUs in a definite trail is crucial as the phasor measurements will be corrupted by bias error. This paper proposes a novel framework for bias error detection and calibration of PMU while expanding the topology network. With a whale optimization algorithm based method to improve the accuracy of PMU measurements for enhancing power system state estimation, monitoring and control operations. Case studies on the standard test systems have been conducted to test the efficacy of the intended tool.

International Legal and Ethical Issues of a Future Carrington Event: Existing Frameworks, Shortcomings, and Recommendations

Solar-geomagnetic superstorms like the 1859 Carrington Event pose significant risks to electrical power utilities and satellite infrastructure. Damage to this critical infrastructure could have sig...

Opportunities and challenges of PV technology in power system

The power distribution’s aim is to satisfy power required at all load centre in the power distribution network with several considerations such as efficient functioning, the economy of operation, voltage stability, and carbon emission in the generation. Because of the rapid growth in electrical power utilization, there is a call for the addition of generation units. However, due to the global exhaustion of fossil fuels, concerns about the environmental impacts, and advancement in PV technologies, fixing a sufficient number of PV based, is a more promising solution than adding a centralize large generation station, to satisfy the increased electrical power demand. The novelty of the paper is that it presents an effectual solution to assure the increased demand by optimal placement and size of PV based DG. The impacts of the PV unit on the voltage contour, power loss of network and carbon emission are examined in IEEE 33 bus radial network and IEEE 30 bus interconnected network. Results show that the optimally placed DG improves stability, efficiency, and reduce the emission of air pollutants.

Evaluation of Power System Reliability and Quality Levels for (N-2) Outage Contingency

One of the main objectives of electric power utilities keeping up a continuous and adequate power supply to the customers at a sensible cost. This paper contributes to the solution of the reliability and quality assessment problems in power systems, using the (N-2) outage contingency scenario to evaluate power system’s reliability and quality levels. Therefore, the methodology presented in this paper is based on the integration of reliability measures, quality indices, and contingency analysis. While reliability formulas have traditionally been applied to small and illustrative power systems, large-scale reliability and quality assessment go far beyond direct implementation of formulas. Systems with hundreds of buses and tens of complex stations can only be analyzed using advanced and numerically effective large-scale algorithms for reliability and quality assessment as demonstrated in this paper.

A Remote and On-Site Educational Tool to Improve the Learning Process of Electrical Power Distribution and Utilization Systems

In this paper, the development of an educational tool to improve the learning process about electrical power distribution and utilization systems in power system courses is presented. Usually, power system courses cover several concepts from the generation of electrical energy, transportation, interconnection, transformation, protection, distribution to final consumption. Most concepts are taught using theoretical circuit analysis, mathematical models and simulations in the classroom and laboratories. To improve the learning of some concepts, some technical tours to power stations and substations are made whenever possible. However, experimental exercises in power system courses are very difficult to implement due to safety reasons since most power equipment operates with high voltages. To mitigate this problem and motivate students in this area, a new power system educational tool to simulate electrical power distribution and utilization systems is proposed. The proposed system was developed using a Programmable Logic Controller (PLC) and other industrial equipment. The proposed pedagogical activities of the educational project and the results achieved with this new update are discussed in this study.

Enhanced data communication models for real‐time power system monitoring in a distributed platform

ABSTRACTThe novelty behind this research is to develop enhanced models for real‐time power system monitoring in a platform‐independent and distributed platform. Distributed models for power system applications have been implemented using Remote Method Invocation (RMI), Common object Request Broker Architecture and. NET remoting technologies. The interoperability among the heterogeneous power system clients in a distributed platform has been achieved through XMLization of power system data which provides meaningful solution to the legacy issues associated with power systems. A RMI‐based model for real‐time power system monitoring in a distributed platform had been implemented and discussed in detail. A component model for real‐time power system monitoring has also been proposed and implemented to increase the reusability and scalability of the system. A location transparent model has been developed using Common object Request Broker Architecture with RMI‐Internet Inter‐Orb Protocol for load flow monitoring and the idea is extended to solve real‐time economic load dispatch and dynamic security monitoring. The detailed monitoring on performance of the proposed models has been done with load flow monitoring, dynamic security monitoring and economic load dispatch problems. A. NET remoting architectural model has been developed for real‐time economic load dispatch in a distributed platform. This research paper explores various issues in deploying power system applications in a distributed platform. It will serve the purpose of stimulating interest among power engineers and also will be extremely useful for electric power utilities.

Distribution system state estimation with elegant PMU placements using a novel metaheuristic

In recent days, the expansion of the distribution network followed by network complexity and contingencies are noted as major issues in electric power utilities. At this juncture, there is not even a distinct constituent for handling such disturbances that occurs due to natural hazards which in turn causes a difficult situation for decision making tracked by redundant state estimation. Therefore, effective monitoring in distributed networks with phasor measuring unit (PMU) involving accurate placements and identification of numerous line outages is presented. Here, a technique using ant lion optimisation (ALO) through elite methodology (EALO) for recognising accurate PMU locations considering cascaded line outages is projected. To evaluate the effectiveness of the projected method standard IEEE systems, practical Indian utility system and polish large scale bus networks are instigated. The numerical result cares about the exact state of distribution topology in a way for improving the performance of the smart grid.

Capacity Planning of Energy Hub in Multi-Carrier Energy Networks: A Data-Driven Robust Stochastic Programming Approach

Cascaded utilization of natural gas, electric power, and heat could leverage synergetic effects among these energy resources, precipitating the advent of integrated energy systems. In such infrastructures, energy hub is an interface among different energy systems, playing the role of energy production, conversion, and storage. The capacity of energy hub largely determines how tightly these energy systems are coupled and how flexibly the whole system would behave. This paper proposes a data-driven two-stage robust stochastic programming model for energy hub capacity planning with distributional robustness guarantee. Renewable generation and load uncertainties are modelled by a family of ambiguous probability distributions near an empirical distribution in the sense of Kullback–Leibler (KL) divergence measure. The objective is to minimize the sum of the construction cost and the expected life-cycle operating cost under the worst-case distribution restricted in the ambiguity set. Network energy flow in normal operating conditions is considered; demand supply reliability in extreme conditions is taken into account via robust chance constraints. Through duality theory and sampling average approximation, the proposed model is transformed into an equivalent convex program with a nonlinear objective and linear constraints, and is solved by an outer-approximation algorithm that entails solving only linear program. Case studies demonstrate the effectiveness of the proposed model and method.