An Immersive Virtual Reality Training Game for Power Substations Evaluated in Terms of Usability and Engagement

Safety-focused training is essential for the operation and maintenance concentrated on the reliability of critical infrastructures, such as power grids. This paper introduces and evaluates a system for power substation operational training by exploring and interacting with realistic models in virtual worlds using serious games. The virtual reality (VR) simulator used building information modelling (BIM) from a 115 kV substation to develop a scenario with high technical detail suitable for professional training. This system created interactive models that could be explored using a first-person-perspective serious game in a cave automatic virtual environment (CAVE). Different operational missions could be carried out in the serious game, allowing several skills to be coached. The suitability for vocational training carried out by utility companies was evaluated in terms of usability and engagement. The evaluation used a System Usability Scale (SUS) and a Game Engagement Questionnaire (GEQ) filled by 16 power substation operators demonstrating marginally acceptable usability, with improvement opportunities and high acceptance (by utility technicians) of this system for operation training focused on safety in such hazardous tasks.

Short term load forecasting using LSTM ensembled network on utility scale load demand.

This work entails producing load forecasting through lstm and lstm ensembled networks and put up a comparative picture between the two. Our work establishes that lstm ensemble learning can produce a better prediction compared to single lstm networks. We tried to quantify the improvement and assess the economic impact that it can have on the utility companies.

Solar Dollars: A Complementary Currency that Incentivizes Renewable Energy

Incentives are the key to addressing climate change and the various other aspects of the current multi-dimensional mega-crisis. This paper proposes the issuance of private community currency vouchers by electric utility companies based on their willingness and ability to provide their customers with energy derived from renewable sources. By monetizing the value of renewable energy in the form of a community currency Solar Dollars help to solve several critical problems at once: They incentivize a more rapid shift to renewable energy, help communities to become more resilient and self-determined, and enable the decentralization of economic and political power.

A Comprehensive Analysis of DSTATCOM-Based Power Improvement

Power quality became one of the most critical challenges in today’s modern power system. Utmost primary factors of power quality issues are non-linear fluctuating loads, system interruption, load variances, infrequent loads, and arc furnaces. As a matter of fact, there is occurrence of various electrical distortions, along with voltage spikes, voltage sags, and so forth. Several innovative techniques were employed for the development of circuits which resulted in minimised voltage stability as well as reliability. Utility companies which are electrical are receiving a large quantity of complaints because of these challenges. An approach is required now to explore the power quality challenges in industrial sector, corporate sector, municipal, or domestic sites. Therefore, a few techniques known as Flexible AC transmission system (FACTs) are used to enhance power quality. It is divided into two categories: namely series-FACTs and shunt-FACTS. As name itself define its architecture that in series-FACTS comprised of transmission line which is connected in series with module and connected in parallel in shun-FACTs. We can alleviate the problems related to power quality with the help of these FACTS devices. D-STATCOM is one of the better devices available. D-STATCOM is a shunt-connected solid-state device employed at the distribution network to maintain load-side disturbances. It has exceeded the traditional capacitor being used improve power quality with it's lower upfront investment, outstanding dynamics, absence of static, and lower operational expenses. The sorts, architectural style, operating, control systems, and AI are all described in this article.

Electricity Utility Companies Entering Private Sector Markets

On the one hand, energy utility companies (EUCs) fulfill public tasks assigned to them by the state. On the other hand, they are also often active as entrepreneurs in the free market. For example, they supply electricity products to major customers, install photovoltaic and e-mobility systems and provide services in the areas of building technology, metering and telecommunications. In such private sector activities, energy utility companies potentially enjoy unjustified advantages due to the fact that they are publicly controlled and perform public tasks: they receive particularly good financing conditions, are taxed on a privileged basis and benefit from economies of scope and information advantages when public and private sector tasks are carried out in parallel. Such privileges may distort competition or prevent companies from entering a market. This chapter examines the legal requirements for dealing with this issue and proposes specific measures with which legislators and authorities can avoid harmful effects of private sector activities by EUCs.

Integral diagnosis on the use of sustainable water treatment technologies

The water sector problems are framed by the low rate of adoption of technological innovation, in addition to the great environmental challenges. In Colombia, due to its topography, the provision of the aqueduct and sewerage service is difficult, causing the association of small rural communities to try to supply their need for drinking water for daily activities in a handcrafted way, this added to the increase of the limitations of the different natural resources, it becomes a challenge to guarantee the fundamental right to water and sanitation. This article, based on the UN's Sustainable Development Goals: "Health and well-being", "Clean water and sanitation", "Sustainable cities and communities, and "Responsible consumption and production" presents the results of a research carried out to validate sustainable technologies for safe water treatment systems in communities. Data were collected for a qualitative analysis through interviews applied to representative actors of the sector: water quality laboratories, aqueducts, and utility companies. The study provides information on the different needs identified for each segment, and provides information on the decisions companies make regarding investment in sustainable technologies, highlighting the existing gap in the water sector in innovation management, it presents a diagnosis on the uses of technologies on the water treatment market.

Day-Ahead Forecasting of Losses in the Distribution Network

Utility companies in the Nordics have to nominate how much electricity is expected to be lost in their power grid the next day. We present a commercially deployed machine learning system that automates this day-ahead nomination of the expected grid loss. It meets several practical constraints and issues related to, among other things, delayed, missing and incorrect data and a small data set. The system incorporates a total of 24 different models that performs forecasts for three sub-grids. Each day one model is selected for making the hourly day-ahead forecasts for each sub-grid. The deployed system reduced the mean average percentage error (MAPE) with 40% from 12.17 to 7.26 per hour from mid-July to mid-October, 2019. It is robust, flexible and reduces manual work. Recently, the system was deployed to forecast and nominate grid losses for two new grids belonging to a new customer. As the presented system is modular and adaptive, the integration was quick and needed minimal work. We have shared the grid loss data-set on Kaggle.

A Comparative Analysis Between LSTM and LSTM Ensembled Strategy for Short-term Load Forecasting

This work entails producing load forecasting through lstm and lstm ensembled networks and put up a comparative picture between the two. Our work establishes that lstm ensemble learning can produce a better prediction compared to single lstm networks. We tried to quantify the improvement and assess the economic impact that it can have on the utility companies.

A Comparative Analysis Between LSTM and LSTM Ensembled Strategy for Short-term Load Forecasting

This work entails producing load forecasting through lstm and lstm ensembled networks and put up a comparative picture between the two. Our work establishes that lstm ensemble learning can produce a better prediction compared to single lstm networks. We tried to quantify the improvement and assess the economic impact that it can have on the utility companies.

SMARTPHONE-BASED REALITY CAPTURE FOR SUBSURFACE UTILITIES: EXPERIENCES FROM WATER UTILITY COMPANIES IN DENMARK

Inaccurate and inconsistent documentation of subsurface utilities is a reoccurring problem in the construction industry affecting not only the end-users, but all actors involved in designing, constructing, and maintaining pipes, cables and other utilities hidden underground. In this study, a new method for 3D capturing of subsurface utilities, based on a newly developed Smartphone-based Reality Capture (RC) solution is explored. The research was divided into two parts. Firstly a testing of the method accuracy and secondly, an investigation of the usability of the method. The research results firstly showed that the RC solution is a feasible surveying method, that facilitate capturing of as-built utility assets, which can be used as a supporting tool to conventional surveying methods or alone, as the testing showed an accuracy of ±5 cm for the generated point clouds. Secondly the usability testing revealed that the RC solution benefited the utility owners by allowing time-savings on construction projects, as well as generating visual-realistic 3D models of exposed subsurface utilities to be used for quality assurance and planning of future utility work.