scholarly journals Green Environment: Decision-Making and Power Utility Optimization towards Smart-Grid Options

2010 ◽  
Vol 01 (01) ◽  
pp. 32-39 ◽  
Author(s):  
Dolores DeGroff
Keyword(s):  
Decision Making ◽  
Smart Grid ◽  
Power Utility ◽  
Utility Optimization

Decision Making for Energy Management in Smart Grid

2019 ◽  
pp. 264-297
Author(s):  
Vira Shendryk ◽  
Olha Boiko ◽  
Yuliia Parfenenko ◽  
Sergii Shendryk ◽  
Sergii Tymchuk
Keyword(s):  
Decision Making ◽  
Information System ◽  
Smart Grid ◽  
Energy Management ◽  
Management Information System ◽  
Information Technologies ◽  
Information Flows ◽  
Management Information ◽  
Microgrid Energy Management ◽  
Planning And Operation

The chapter discusses the problem of energy management in Smart MicroGrid. The strategies of Smart MicroGrid energy management and objectives of Smart MicroGrid operation have been analyzed. The chapter emphasizes the potential of information technologies implementation to achieve energy management goals and provide a description of energy management information system which is used for MicroGrid planning and operation. The information flows which are used for making decision on Smart MicroGrid energy management have been analyzed.

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

2021 ◽  
Vol 13 (16) ◽  
pp. 9091
Author(s):  
Mohamed Gaha ◽  
Bilal Chabane ◽  
Dragan Komljenovic ◽  
Alain Côté ◽  
Claude Hébert ◽  
...  
Keyword(s):  
Decision Making ◽  
Asset Management ◽  
Electrical Power ◽  
Informed Decision ◽  
Informed Decision Making ◽  
Power Utility ◽  
Important Indicator ◽  
Power Utilities ◽  
The Impact ◽  
Electrical Utilities

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.

scholarly journals A Review on Big Data Management and Decision-Making in Smart Grid

2019 ◽  
Vol 4 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Amira Mohamed ◽  
Shady S. Refaat ◽  
Haitham Abu-Rub
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Smart Grid ◽  
Energy Security ◽  
Energy Use ◽  
Essential Element ◽  
Existing Problems ◽  
Data Process ◽  
Equipment Failures ◽  
And Control

AbstractSmart grid (SG) is the solution to solve existing problems of energy security from generation to utilization. Examples of such problems are disruptions in the electric grid and disturbances in the transmission. SG is a premium source of Big Data. The data should be processed to reveal hidden patterns and secret correlations to extrapolate the needed values. Such useful information obtained by the so-called data analytics is an essential element for energy management and control decision towards improving energy security, efficiency, and decreasing costs of energy use. For that reason, different techniques have been developed to process Big Data. This paper presents an overview of these techniques and discusses their advantages and challenges. The contribution of this paper is building a recommender system using different techniques to overcome the most obstacles encountering the Big Data processes in SG. The proposed system achieves the goals of the future SG by (i) analyzing data and executing values as accurately as possible, (ii) helping in decision-making to improve the efficiency of the grid, (iii) reducing cost and time, (iv) managing operating parameters, (v) allowing predicting and preventing equipment failures, and (vi) increasing customer satisfaction. Big Data process enables benefits that were never achieved for the SG application.

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