A Practical Approach to Intelligent Power Management Systems Framework

Guest Editorial: Situational awareness of integrated energy systems

The design of systems used for operation and control of electric power systems, commonly called a supervisory control and data acquisition (SCADA) system, energy management system (EMS) or distribution management system (DMS) is still oriented towards deterministic operations. However, the advent of intelligent electronic devices (IEDs) in the substation, and the potential volume of time data they can supply, creates a requirement to re-assess the basic design criteria. This paper begins with a brief overview of the main elements of substation automation. It then considers some of the typical features and functions that make up the significant characteristics of a SCADA/EMS/DMS. The paper considers both the 'positive' and 'negative' impacts of IED data volumes in such areas as database and display principles, processing of alarms and events, alarm identification and performance of control functions, and design of analytical programs. The easiest solution, which seems to be the preferred method today, is to make slight adjustments to the basic designs; and ignore the balance of the issues. On the other hand, incorporating the capabilities of IEDs, and taking advantage of the data volumes in the basic EMS/DMS design can greatly increase the ability of the control system and the operators to manage the electric power system in a safe, reliable and economic manner.

Special issue on “Optimal design and operation of energy systems”

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Power system voltage control and voltage stability are emerging as major problems in the day-to-day operation of stressed power systems. STATCOM is an important voltage source converter FACTS device, which can be used in voltage control mode or reactive power injection mode. For stable operation and control of power systems it is essential to provide real time solution to the operator in energy control centers. Artificial neural networks are an important artificial intelligence tool, which gives fast and acceptable solution in real time. This paper deals with development of ANN architecture which provides solution for bus voltage control and reactive power control in the day to day operation of power systems.

In this article, a hybrid electric propulsion system which consists of a fuel cell (FC) and a battery is proposed for an unmanned aerial vehicle (UAV) propulsion application. Based on the UAV propulsion power requirements during take-off, climb, endurance, and maximum velocity, the hybrid electric power plant specifications are defined to respond to any propulsion power demand. A power and energy management system is introduced to control the hybrid system power flow while optimizing the FC system performances. The power and energy management system consists of three sections called, power management system, power electronic interface, and energy management system. The power management system decides the operating power of the each power source based on the propulsion power demand and the battery state of charge. The power electronic interface is an implementation protocol of the power management decisions through a unidirectional power converter and a bidirectional power converter which are connected to the FC, the battery, and the DC bus. Based on the FC current decided by the power management system, the energy management system controls the air supply system of the FC to maximize the FC system net power output. A referenced model is used to obtain the optimum inlet air pressure of the FC and a neuro-fuzzy-based adaptive control architecture adapts the FC air compressor power to the optimum value. The results show that the optimum compressor power configuration is superior than the constant power configuration.

Electrical Engineering in JapanVolume 110, Issue 2 p. 60-73 Article Restoration guidance system for trunk line system Shigeru Warashina, Tokyo Electric Power Co. Shigeru Warashina joined Tokyo Electric Power Co. in 1969. He graduated in 1970 from Kagaku Gijutsu Gakuen Technical High School. He is engaged mainly in the power supply operation of power systems. He joined the System Research Section of the Technical Research Laboratory of Tokyo Electric Power Co. in 1985.Search for more papers by this authorYukio Kojima, Tokyo Electric Power Co. Yukio Kojima obtained a Master's degree in 1977 in Electric Engineering from the Science and Engineering Research Division of Waseda University. He joined Tokyo Electric Power Co. the same year, and began working in the System Research Section of the Technical Research Laboratory in 1986. He is engaged mainly in the power supply operation of power systems.Search for more papers by this authorShizuka Nakamura, Mitsubishi Electric Co. Shizuka Nakamura obtained a Master's degree in 1973 in Electrical Engineering from Seikei University. He joined Mitsubishi Electric Corp. in April of the same year, and is presently in its Power System Division at the Information Communication Second System Engineering Center. He is engaged in the technological development on the analysis, operation, and control of power systems. He is a member of the Information Processing Society of Japan.Search for more papers by this authorKeinosuke Matsumoto, Mitsubishi Electric Co. Keinosuke Matsumoto obtained a Master's degree in 1978 in Precision Mechanics from the Engineering Research Division of the Kyoto University. He also has a Dr. of Eng. degree. He joined Mitsubishi Electric Corp. in April of the same year, and is assigned to the Central Research Laboratory. Since then he has been engaged mainly in research on the application of knowledge engineering to the operation/control of power systems. In 1983, he received the Sawaragi Memorial Award of the Japan Association of Automatic Control Engineers, and in 1984, a paper prize of the Institute of Electrical Engineers of Japan. He is a member of the Information Processing Society of Japan; and I.E.E.E.Search for more papers by this author Shigeru Warashina, Tokyo Electric Power Co. Shigeru Warashina joined Tokyo Electric Power Co. in 1969. He graduated in 1970 from Kagaku Gijutsu Gakuen Technical High School. He is engaged mainly in the power supply operation of power systems. He joined the System Research Section of the Technical Research Laboratory of Tokyo Electric Power Co. in 1985.Search for more papers by this authorYukio Kojima, Tokyo Electric Power Co. Yukio Kojima obtained a Master's degree in 1977 in Electric Engineering from the Science and Engineering Research Division of Waseda University. He joined Tokyo Electric Power Co. the same year, and began working in the System Research Section of the Technical Research Laboratory in 1986. He is engaged mainly in the power supply operation of power systems.Search for more papers by this authorShizuka Nakamura, Mitsubishi Electric Co. Shizuka Nakamura obtained a Master's degree in 1973 in Electrical Engineering from Seikei University. He joined Mitsubishi Electric Corp. in April of the same year, and is presently in its Power System Division at the Information Communication Second System Engineering Center. He is engaged in the technological development on the analysis, operation, and control of power systems. He is a member of the Information Processing Society of Japan.Search for more papers by this authorKeinosuke Matsumoto, Mitsubishi Electric Co. Keinosuke Matsumoto obtained a Master's degree in 1978 in Precision Mechanics from the Engineering Research Division of the Kyoto University. He also has a Dr. of Eng. degree. He joined Mitsubishi Electric Corp. in April of the same year, and is assigned to the Central Research Laboratory. Since then he has been engaged mainly in research on the application of knowledge engineering to the operation/control of power systems. In 1983, he received the Sawaragi Memorial Award of the Japan Association of Automatic Control Engineers, and in 1984, a paper prize of the Institute of Electrical Engineers of Japan. He is a member of the Information Processing Society of Japan; and I.E.E.E.Search for more papers by this author First published: 1990 https://doi.org/10.1002/eej.4391100207Citations: 1 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Citing Literature Volume110, Issue21990Pages 60-73 RelatedInformation

This paper presents a unique facility capable of exhibiting the operation of modem-day power system energy management systems (EMS) for educational and possible research applications. We present the design and construction of the laboratory facility. Key elements include a real-life, flexible power system network, signal conditioning hardware, data acquisition equipment, and client/server industry-standard computer networking technology. The system allows students to get experience on the realistic operation and control of power systems and exposes them to modem data acquisition and supervisory control (SCADA) equipment and procedures used by the industry.

This paper presents a unique facility capable of exhibiting the operation of modern day power system energy management systems (EMS). The purpose is educational with possible research applications. We present the design and construction of the laboratory facility. Key elements of the facility include a real-life, flexible power system network, signal conditioning hardware, data acquisition (DAQ) equipment, and client/server industry standard computer networking technology. The designed EMS system will allow students to get experience on the realistic operation and control of power systems and expose students to modern supervisory control and data acquisition (SCADA) equipment and procedures used by the power industry.

During the last twenty years, intelligent systems applications have received increasing attention in manufacturing industries, electric power utilities and academia including universities and institutions. The applications are spread to the wide areas for the operation, control and management of electric power systems including prediction, diagnosis, optimization, and planning. In Japanese utilities, a certain number of intelligent systems have been actually utilized to have the improved performance of the power systems, however, the time of their renewals has been approaching for many of them. There exist new innovative applications. However, most of them are still under investigation or in the development stage. Intelligent systems have been increasingly used to develop more efficient schemes for the power system operation, planning, control, and management. This paper presents the current status of intelligent systems applications to power systems in Japan and future considerations of fuzzy system applications

Unmanned aerial vehicle (UAV) electric propulsion is a modern aviation concept that has long endurance capacity compared to the conventional IC engines. The polymer exchange membrane (PEM) fuel cell and Li-Ion battery hybrid power plant shows a great potential to replace the IC engines from UAVs due to high energy and power densities of the power sources. The power and energy management is an important consideration in PEM fuel cell/ Li-Ion battery hybrid power system to optimize the energy sharing between two power sources. The energy management system (EMS) has long term objectives to maximize the FC net power output by minimizing the oxygen concentration voltage losses. The EMS receives the feedbacks from the battery, the load power and the FC system control parameters. The decisions taken by the EMS are passed to the power management system (PMS) which makes the short term policies to control the power electronic interface (PEI). The PEI is consisted with the bidirectional controller for the battery and the DC boost converter for the PEMFC system. The PMS has rule base system to decide the operating power of the PEMFC system. In addition to that, the PMS decide the bidirectional converter current flow direction to charge or discharge the battery. The EMS system controls the FC system inlet air flow rate by changing the compressor motor voltage to the optimum values. The Adaptive Neuro Fuzzy Inference System (ANFIS) based online learning and adaptive control algorithms are used to train the existing compressor voltage into the optimum values which are obtained from the reference model. In this power and energy management system, the FC system is operated at optimum power region and the battery supplies the transient power to the propulsion system. (6 pages)

Reinforcement learning (RL) is area of Machine Learning (ML) and part of wide-range portfolio of the Artificial intelligence (AI) methods. Besides the explanations of the concepts and principles of RL, in the paper are presented practical RL models for control and optimizing operation of power system – controlling tap-changers for maintain voltage levels and model for techno-economical optimizing operation of energy storages of households in microgrid. Trained RL agent in the practical example synchronizes operation of tap-changers to maintain satisfactory voltage level for the consumers, even in the network with distributed generation. Energy storages are in wide use in households, especially in the combination with PV. In the second example, microgrid’s energy management system (EMS) RL agent after learning process act in the simulated environment with variable electrical energy prices, variable load profiles and efficiency of PV modules of households to maximize profit for the houseowners in the microgrid. Agent controls charging and discharging of energy storages and obtain maximal benefit in randomly determined conditions of microgrid operation and different tariff situations. Models are implemented in the Python programming environment Python with specialized power system simulation software (Pandapower) and RL libraries (RLib, OpenAI).

As the trend toward modernization of todays electric power systems deepens, some fundamental problems with electric power systems remain unchanged - system reliability, optimized unit commitment, optimal generation allocation, load forecast, optimal unit control. This paper presents an overview of a series of innovations that have been implemented for better electric power transmission and distribution systems over the past decade, when deregulation has become widely accepted and energy market system designs become more standardized. Several key aspects are reviewed: Power system operation, power system control, and power system markets. Developments, as revealed especially in recent patents, in several important functional areas are emphatically discussed: voltage stability, unit commitment, load forecast, market dispatch. A unified framework is presented in which all these discussions are conducted, and formulated in a unified perspective, where prediction, optimization and control are integrated and work together to attempt to achieve the best overall system control performance, system economics, and yet maintain system stability and required reliability. Keywords: Smart Grid, load forecast, voltage stability, optimal power flow, unit commitment, economic dispatch, generation allocation, load prediction, neural networks, optimization

In this paper, the Distribution Automatic System (DAS) is introduced and analyzed to improve the operation of power systems in Quang Nam province, Vietnam. The application of DAS contributes to quickly detect and isolate incidents, immediately restore the normal operation of the system and improve the power system reliability. The DAS is an effective support tool for the dispatchers in the remote operation, control and management of power systems. Previous publishes have done the research and application of DAS technology to the distribution grid but did not analyze of busbar segment problem and the programming for the DAS. This paper investigates the application of DAS using MicroSCADA SYS600 9.4 Pro software in the construction of smart grids in Quang Nam province and examines specific cases of faults on two Quang Nam feeders. Also, a program to implement the simulation of DAS is processed.

With the increasing penetration of renewable energy resources (RESs), the uncertainties of volatile renewable generations significantly affect the power system operation. Such uncertainties are usually modeled as stochastic variables obeying specific distributions by neglecting the temporal correlations. Conventional approaches to hedge the negative effects caused by such uncertainties are thus hard to pursue a trade-off between computation efficiency and optimality. As an alternative, the theory of stochastic process can naturally model temporal correlation in closed forms. Attracted by this feature, our research group has been conducting thorough researches in the past decade to introduce stochastic processes within renewable power systems. This paper summarizes our works from the perspective of both the frequency domain and the time domain, provides the tools for the analysis and control of power systems under a unified framework of stochastic processes, and discusses the underlying reasons that stochastic process-based approaches can perform better than conventional approaches on both computational efficiency and optimality. These work may shed a new light on the research of analysis, control and operation of renewable power systems. Finally, this paper outlooks the theoretic developments of stochastic processes in future’s renewable power systems.