Electric Utility Control Research Articles

A self-learning algorithm for coordinated control of rooftop units in small- and medium-sized commercial buildings

With the advent of the smart grid, demand response (DR) has been implemented in many electric utility control areas to reduce peak demand in buildings during grid stress conditions. However, small- and medium-sized commercial buildings typically do not deploy a building energy management (BEM) system due to high costs of commercially available solutions. Thus, their participation in DR events implies manual control and shutting down major building loads (e.g., air conditioning systems) without considering occupant comfort. With rapid development of Internet of Things (IoT) technologies, some cost-effective IoT-based BEM systems have become available. Based on such systems, this paper presents an algorithm to automatically coordinate the operation of rooftop units (RTUs) in small- and medium-sized commercial buildings, thereby meeting the specified power limit (kW) during a DR event while taking into account occupant comfort. The proposed algorithm has been designed to intelligently learn building thermal properties using coarse-grained indoor temperature data from thermostats, thus avoiding the deployment of sophisticated sensors network. A mixed-integer linear programming model has been utilized to determine an optimal RTU control strategy during a DR event. The peak load shedding performance of the proposed strategy has been tested in an office building in Blacksburg, VA, USA. The experimental result demonstrates that the building could achieve the required peak load reduction and the computation time required by the proposed algorithm is less than 5min. This implies that with the proposed algorithm a building is capable of responding to a DR signal with a short notice, providing valuable demand-side resources for electricity capacity and ancillary markets.

Application of artificial neural networks for short term wind speed forecasting in Mardin, Turkey

Artificial neural network models were used for short term wind speed forecasting in the Mardin area, located in the Southeast Anatolia region of Turkey. Using data that was obtained from the State Meteorological Service and that encompassed a ten year period, short term wind speed forecasting for the Mardin area was performed. A number of different ANN models were developed in this study. The model with 60 neurons is the most successful model for short term wind speed forecasting. The mean squared error and approximation values for training of this model were 0.378088 and 0.970490, respectively. The ANN models developed in the study have produced satisfactory results. The most successful among those models constitutes a model that can be used by the Mardin Electric Utility Control Centre.

11.1.2 Simulation of an Electric Utility Network and Control System in SysML

AbstractModeling of the electric utility network is normally done using bespoke or custom tools and programs rather than generic modeling languages. This requires the engineer to develop the complete simulation system from scratch. In addition, it is difficult to model from different viewpoints and levels of abstraction. The models are normally created from a single perspective to solve a specific problem or analyze the system from a single point of view. The Systems Modeling Language (SysML) was developed by INCOSE and the OMG to provide general purpose modeling language for systems. Most published examples of SysML are of electro‐mechanical software intensive systems in the aerospace and transportation industries. This paper documents a work in progress by the author to develop a model of an example electric utility network, including the user interface to show how SysML can be used to model complex systems of systems. In addition, it shows how a simulation tool integrated with SysML provides a means of integrating multiple paradigms as well as a Human Computer Interface to the simulation.

System of choice

Wide-area measurements have been an integral part of power system operations for over six decades. They have been used in economic dispatch and automatic generation control systems in electric utility control centers using real-time measurements of power flows on remote tie lines and generator output powers. In the late 1960s a new class of wide-area measurement systems came into use--supervisory control and data acquisition (SCADA) systems--in order to provide real-time state estimates of the power system in the electric utility energy management systems (EMSs). Over the years, the "real time" in these SCADA-based measurements came to imply measurements performed over a data window of several seconds without regard to the precise instant when the measurements were made.

Short term wind speed forecasting in La Venta, Oaxaca, México, using artificial neural networks

In this paper the short term wind speed forecasting in the region of La Venta, Oaxaca, Mexico, applying the technique of artificial neural network (ANN) to the hourly time series representative of the site is presented. The data were collected by the Comisión Federal de Electricidad (CFE) during 7 years through a network of measurement stations located in the place of interest. Diverse configurations of ANN were generated and compared through error measures, guaranteeing the performance and accuracy of the chosen models. First a model with three layers and seven neurons was chosen, according to the recommendations of diverse authors, nevertheless, the results were not sufficiently satisfactory so other three models were developed, consisting of three layers and six neurons, two layers and four neurons and two layers and three neurons. The simplest model of two layers, with two input neurons and one output neuron, was the best for the short term wind speed forecasting, with mean squared error and mean absolute error values of 0.0016 and 0.0399, respectively. The developed model for short term wind speed forecasting showed a very good accuracy to be used by the Electric Utility Control Centre in Oaxaca for the energy supply.

Wind speed forecasting in the South Coast of Oaxaca, México

Comparison of two techniques for wind speed forecasting in the South Coast of the state of Oaxaca, Mexico is presented in this paper. The Autoregressive Integrated Moving Average (ARIMA) and the Artificial Neural Networks (ANN) methods are applied to a time series conformed by 7 years of wind speed measurements. Six years were used in the formulation of the models and the last year was used to validate and compare the effectiveness of the generated prediction by the techniques mentioned above. Seasonal ARIMA models present a better sensitivity to the adjustment and prediction of the wind speed for this case in particular. Nevertheless, it was shown both developed models can be used to predict in a reasonable way, the monthly electricity production of the wind power stations in La Venta, Oaxaca, Mexico to support the operators of the Electric Utility Control Centre.

A DSS Design Model for complex problems: Lessons from mission critical infrastructure

This paper presents a new DSS Design Model for complex, mission critical decision-making situations and its technical, conceptual, and partial empirical evaluation. The new model was derived from conceptual design research and through a deep qualitative field research study at an electric power utility control center—a typical arena for “wicked” problems. The model suggests an iterative process of theory, simulation, and decision-making interactions. The DSS Design Model is validated using a tool instantiation, microgrid mini-case, and current research of a KMDSS for telecommunications. Main findings suggest that broader and more integrated approaches are necessary to design DSS for complex domains.

Electric utility responses to grid security issues

This paper discusses the different initiatives that utility decision makers have set in place to address the vulnerability of the US power grid to physical and cyber attacks. One of the efforts to enhance grid security is EPRI's Infrastructure Security Initiative (ISI), which was designed to develop both prevention countermeasures and enhanced recovery capabilities. To protect against cyber attacks, several organizations were also established including the Computer Emergency Response Team (CERT) and the Process Control Systems Forum (PCSF). In addition, EPRI also launched the Energy Information Security (EIS) program to focus on computer-based security breaches. An industry-wide cybersecurity program alliance, called the PowerSec Initiative, was also formed to address the cyberthreat issue as it could impact electric utility operational and control equipment.

Open system, video projection power system visualization system

Video projection systems are starting to be used in electric utility control rooms as a replacement to the traditional hardwired tile mimic boards. Initial applications have been in distribution control rooms displaying CAD, geographical and weather information. Video projection mapboards are also in use for power plant control rooms displaying process control data. The cost of video projection systems has gone down significantly while the image quality of these systems has increased. This has made them a more cost effective solution for use in all types of electric utility control rooms. The development of innovative, open system software products in conjunction with video projection provides an alternative to the costly traditional hardwired approaches. This project demonstrates the successful development and integration of a 52'/spl times/10' rear-projection video wall capable of displaying a real time power system diagram as a continuous image across the entire projection space. Innovative design and integration of off-the-shelf software products enabled this project to be completed under budget, three months ahead of schedule and with no additional staffing. The new system has proven itself to be a indispensable operations tool during system disturbances and restoration scenarios.

Applying low-voltage circuit breakers in direct current systems

Low-voltage, direct current equipment in electric utility control systems, uninterruptible power systems (UPS), telecommunication systems, and elsewhere has received increasing attention in recent years. Power conditioning needs are one reason. Closer attention by regulatory agencies is another. This paper is intended to help fill a gap in available material on ratings and application characteristics of low-voltage circuit breakers in DC power systems. >

Tracking evolutionary trends in generation control

Issues such as limited investment in new production and transmission facilities, forced transmission access, environmental concerns (Clean Air Act), and independent power producers are forcing changes in electric utility operations, putting more emphasis not only on efficiency and reliability, but also on improved controls to meet new operating constraints. The impact of these issues on electric utility generation scheduling and control is addressed. Some of the shortcomings of the technologies presently used in generation scheduling and control are described, and new technical requirements and evolutionary trends are outlined. An attempt is made to evaluate the impact of the new requirements on the current generation scheduling and control methodologies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Application of artificial neural networks to power system transient energy margin evaluation

Modern energy control centres utilized for electric utility control and monitoring are required to provide real-time security assessment. Maintenance of power system security is a technological challenge as the power systems are now operated much closer to security limits. The paper proposes a new approach to on-line transient stability analysis. The method combines transient energy function methodology with artificial neural networks. Case studies are presented to illustrate the suitability of the proposed approach.

Utility control centers open to change

The 'open systems' concept is examined from the perspective of an electric utility control center. The concept is defined, and its advantages are discussed. It is shown how open systems can improve the process by which utilities acquire and evolve their control centers. Suggestions for procuring an open system are offered. >

An Historical Information Spreadsheet for Power System Operation

The application of electronic spreadsheet packages has been maturing with the increased usage of small or personal computers. However, little work has been done to explore the use of spreadsheet techniques in power system operation. In this paper the common spreadsheet concept used for answering the ``what if'' question is extended to conveniently answer the questions of ``what was'' or ``what will be'' in power control operation. Enhanced with features needed to support automated data collection and processing in a real-time electric utility control, the extended spreadsheet concept has been implemented in a delivered power control computer. This paper describes an approach to the implementation of the real-time spreadsheet and data storage software package. The intended uses are first described. The method of constructing a real-time spreadsheet using this package is illustrated with an example. The software tools included in the package are presented in substantial detail. The presentation of the software functions also illustrates the relationship of spreadsheet building to the control computer database.

An Historical Information Spreadsheet for Power System Operation

The application of electronic spreadsheet packages has been maturing with the increased usage of small or personal computers. However, little work has been done to explore the use of spreadsheet techniques in power system operation. In this paper the common spreadsheet concept used for answering the "what if" question is extended to conveniently answer the questions of "what was" or "what will be" in power control operation. Enhanced with features needed to support automated data collection and processing in a real-time electric utility control, the extended spreadsheet concept has been implemented in a delivered power control computer. This paper describes an approach to the implementation of the real-time spreadsheet and data storage software package. The intended uses are first described. The method of constructing a real-time spreadsheet using this package is illustrated with an example. The software tools included in the package are presented in substantial detail. The presentation of the software functions also illustrates the relationship of spreadsheet building to the control computer database.

Calculation of Optimum Preventive Maintenance Intervals for Electrical Equipment

Formulas to calculate the optimum interval of preventive maintenance and the optimum interval of diagnostic testing of electrical equipment are presented. Each user can calculate his own custom intervals using the formulas which are based on least total annual costs. The user must have his own data base of equipment failures similar to the example presented. Using 10000 failures of electric utility control and monitoring equipment as a sample, it was found that 25 percent of the failures could have been prevented by preventive maintenance, 65 percent could have been caught by diagnostic testing, and less than 10 percent have failed in the operative mode and could not have been maintained against or caught beforehand. One factor in the formula, which determines the shape of the equipment failure curve, remains to be proven after the next five years of data are collected.

Synopsis of C37.1 Manual, Automatic and Supervisory Control and Data Acquisition

This working group report is prepared to 1) encourage electric utility control system engineers in the applications of C37.1 and 2) serve as a vehicle for panel discussions at winter and summer Power Engineering Society Meetings during 1979. C37.1 is the identifying number that ANSI will assign to the document produced by working group 72.2.