An alternative design and implementation of a solid state on-load tap changer

Power quality and reliability are of great importance in the modern world, whether it be the power generated by the power utilities or the power consumed by the customer respectively. They need these supplies to be at its optimum value so that the cost is effective, and the safety of devices assured otherwise problems such as overvoltage, under-voltage, and voltage sags caused by disturbances in the power supply could be disastrous. On-load tap changers (OLTC) have therefore been used since the inception of electrical engineering. The main function of the OLTC is to change the turns of the transformer winding so that the voltage variations are limited without interrupting the secondary current.The major idea is that the electronic switches and other smart systems provide more controllability during the tap changing process, unlike mechanical switches.This paper presents an alternative design and implementation of a low-cost solid-state OLTC and employs a control strategy that is microcontroller-based, ensuring the desired flexibility and controllability required in programming the control algorithms.It eliminates the limitations of both mechanical and hybrid OLTCs (arcing, slow response time, losses) and is user-friendly (provides an effective communication medium). Voltage regulation is achieved by varying the turns of the transformer winding whiles it is energized, supplying load current and with the tap selection carried out on the primary side. Therefore, this approach provides a less expensive system but ensures the efficiency and reliability of voltage regulation.

A Fast and Accurate Wind Speed and Direction Nowcasting Model for Renewable Energy Management Systems

To plan operations and avoid any grid disturbances, power utilities require accurate power generation estimates for renewable generation. The generation estimates for wind power stations require an accurate prediction of wind speed and direction. This paper proposes a new prediction model for nowcasting the wind speed and direction, which can be used to predict the output of a wind power plant. The proposed model uses perturbed observations to train the ensemble networks. The trained model is then used to predict the wind speed and direction. The paper performs a comparative assessment of three artificial neural network models. It also studies the performance of introducing perturbed observations to the model using six different interpolation techniques. For each technique, the computational efficiency is measured and assessed. Furthermore, the paper presents an exhaustive investigation of the performance of neural network types and several techniques in training, data splitting, and interpolation. To check the efficacy of the proposed model, the power output from a real wind farm is predicted and compared with the actual recorded measurements. The results of the comprehensive analysis show that the proposed model outperforms contending models in terms of accuracy and execution time. Therefore, this model can be used by operators to reliably generate a dispatch plan.

Electrokit: Power Utility Toolkit-Electricity Loss Reduction

The Electrokit is an initiative created by the IDB to strengthen transformation and continuous improvement of electric utilities in the LAC region. The Electrokit is organized in 16 activities that are common to most electricity utilities. This publication presents the indicators and best practices related to Electricity Loss Reduction. The aim of the toolkit is to provide power utilities, policy and decision-makers access to best practices, current trends, and expertise to: (i) identify challenges, develop a strategy and action plan for addressing them; and (ii) support utilities to be more sustainable, efficient, improve customer experience and accelerate innovation to stay ahead of the rapidly sector transformation.

Electrokit: Power Utility Toolkit–Quality of Technical Service

The Electrokit is an initiative created by the IDB to strengthen transformation and continuous improvement of electric utilities in the LAC region. The Electrokit is organized in 16 activities that are common to most electricity utilities. This publication presents the indicators and best practices related to Quality of Technical Service. The aim of the toolkit is to provide power utilities, policy and decision-makers access to best practices, current trends, and expertise to: (i) identify challenges, develop a strategy and action plan for addressing them; and (ii) support utilities to be more sustainable, efficient, improve customer experience and accelerate innovation to stay ahead of the rapidly sector transformation.

Electrokit: Power Utility Toolkit-The Overview: Best Practices in Electric Power Distribution Companies in the Latin America and Caribbean Region

The Electrokit is an initiative created by the IDB to strengthen transformation and continuous improvement of electric utilities in the LAC region. It follows international standards that characterize and evaluate utilities based on indicators and best practices. The Electrokit is organized in 16 activities that are common to most electricity utilities. The aim of the toolkit is to provide power utilities, policy and decision-makers access to best practices, current trends, and expertise to: (i) identify challenges, develop a strategy and action plan for addressing them; and (ii) support utilities to be more sustainable, efficient, improve customer experience and accelerate innovation to stay ahead of the rapidly sector transformation. The Overview presents the main objectives of the toolkit, the structure of its areas and activities, and a guide on how companies could design an action plan.

On a special case of non-symmetric resource extraction games with unbounded payoffs

The game of resource extraction/capital accumulation is a stochastic infinite-horizon game, which models a joint utilization of a productive asset over time. The paper complements the available results on pure Markov perfect equilibrium existence in the non-symmetric game setting with an arbitrary number of agents. Moreover, we allow that the players have unbounded utilities and relax the assumption that the stochastic kernels of the transition probability must depend only on the amount of resource before consumption. This class of the game has not been examined beforehand. However, we could prove the Markov perfect equilibrium existence only in the specific case of interest. Namely, when the players have constant relative risk aversion (CRRA) power utilities and the transition law follows a geometric random walk in relation to the joint investment. The setup with the chosen characteristics is motivated by economic considerations, which makes it relevant to a certain range of real-word problems.

Short Term Load Forecasting System Using Artificial Neural Networks For Improved Demand Scheduling By Power Utilities.

Load forecasting is a technique used by power utilities to predict electricity demand to maintain the balance between supply and demand. The problem comes when the power utilities draw more than the inadvertent power from the power pool. This necessitates the need for more accurate forecasting models. In this study, a short-term load forecasting system using artificial neural networks in MatLab was performed. The Levenberg-Marquardt optimization technique which has one of the best learning rates was used as a back-propagation algorithm for the Multilayer Feed Forward ANN model using MatLab® R2018a ANN Toolbox. Historical electricity load data obtained from a feeder line at the Zimbabwe Electricity Transmission and Distribution Company (ZETDC) Marvel 420 kV substation in Bulawayo Zimbabwe was used for the training, testing, and validation of the model. Results indicate that ANNs can forecast load with an accuracy of 6.71%. The results indicate that the proposed technique is robust in forecasting future load demands for the daily operational planning of power system distribution

Global Methodology for Electrical Utilities Maintenance Assessment Based on Risk-Informed Decision Making

Modern electrical power utilities must deal with the replacement of large portions of their assets as they reach the end of their useful life. Their assets may also become obsolete due to technological changes or due to reaching their capacity limits. Major upgrades are also often necessary due to the need to grow capacity or because of the transition to more efficient and carbon-free power alternatives. Consequently, electrical power utilities are exposed to significant risks and uncertainties that have mostly external origins. In this context, an effective framework should be developed and implemented to maximize value from assets, ensure sustainable operations and deliver adequate customer service. Recent developments show that combining the concepts of asset management and resilience offers strong potential for such a framework—not only for electrical utilities, but for industry, too. Given that the quality and continuity of service are critical factors, the concept of Value of Lost Load (VoLL) is an important indicator for assessing the value of undelivered electrical energy due to planned or unplanned outages. This paper presents a novel approach for integrating the power grid reliability simulator into a holistic framework for asset management and electrical power utility resilience. The proposed approach provides a sound foundation for Risk-Informed Decision Making in asset management. Among other things, it considers asset performance as well as the impact of both current grid topology and customer profiles on grid reliability and VoLL. A case study on a major North American electrical power utility demonstrates the applicability of the proposed methodology in assessing maintenance strategy.

Influence of the Characteristics of Weather Information in a Thunderstorm-Related Power Outage Prediction System

Thunderstorms are one of the most damaging weather phenomena in the United States, but they are also one of the least predictable. This unpredictable nature can make it especially challenging for emergency responders, infrastructure managers, and power utilities to be able to prepare and react to these types of events when they occur. Predictive analytical methods could be used to help power utilities adapt to these types of storms, but there are uncertainties inherent in the predictability of convective storms that pose a challenge to the accurate prediction of storm-related outages. Describing the strength and localized effects of thunderstorms remains a major technical challenge for meteorologists and weather modelers, and any predictive system for storm impacts will be limited by the quality of the data used to create it. We investigate how the quality of thunderstorm simulations affects power outage models by conducting a comparative analysis, using two different numerical weather prediction systems with different levels of data assimilation. We find that limitations in the weather simulations propagate into the outage model in specific and quantifiable ways, which has implications on how convective storms should be represented to these types of data-driven impact models in the future.

STABILITY AND CONTROL ASPECTS OF MICRO-GRID ARCHITECTURES OF WIND POWER SYSTEM

Voltage unstability nowadays is a serious problem, Present day electric power utilities are confronting numerous difficulties because of regularly expanding multifaceted nature in their task and structure. One issue that got wide consideration is voltage instability. One of the significant reasons for voltage instability in the power framework is with its receptive power limit. It can cause different damages to our electrical appliances, and therefore the approach used in this research is for the benefit for these dangerous phenomenon. In this research Voltage control single phase STATCOM using different sources such as Photovoltaic Cell, DC generator, battery and WAPDA used, in such a way to have a backup voltage source to have an untriptable supply, in case of less than 9 V the relay converter used the DC generator as back end source. It is a controller based system, controller on the basis of voltages changes the source to PV to DC and DC generator to Battery depends upon the voltages. Inverter is used which take input of 12 V that are controlled by relay in case of PV it is stabilized by buck converter. 1kVA Transformer then sets the voltage to 230V single phase, STATCOM is used after transformer to set the voltage at 230 V Power and Voltage monitoring system is used to check power and voltages at every point.