Improved hierarchical decision making policy for reliable and green electricity grid

Jain, Parikh; Batra, Varun; Darak, Sumit J.

doi:10.1109/comsnets.2018.8328241

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…Finally, the unit commitment problem can also be addressed with a reinforcement learning approach. In [171], the authors exploit reinforcement learning to choose a unit commitment and economic dispatch in a hierarchical way, while minimising operation cost or CO 2 emissions; and in [172] the unit commitment problem is modelled as a Markov decision process. The unit commitment problem can also be defined as a multiobjective problem, for example to both minimise operating costs and maximise system reliability [173] or minimise both operation costs and wind curtailment [174].…”

Section: Unit Commitment Predictionmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

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This paper reviews recent works applying machine learning techniques in the context of energy systems reliability assessment and control. We showcase both the progress achieved to date as well as the important future directions for further research, while providing an adequate background in the fields of reliability management and of machine learning. The objective is to foster the synergy between these two fields and speed up the practical adoption of machine learning techniques for energy systems reliability management. We focus on bulk electric power systems and use them as an example, but we argue that the methods, tools, etc. can be extended to other similar systems, such as distribution systems, micro-grids, and multi-energy systems.

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Section: Unit Commitment Predictionmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

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Decision making methods used for improving power quality to meet the sustainable energy targets

Eroğlu,

Kurtuluş,

Can

2024

Energy & Environment

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A higher quality energy demand in line with sustainable goals has led researchers to new studies. The concept of power quality has become very popular in this direction in the last decade. Decision making concept, which is another important and popular concept, has become an indispensable tool in solving difficult decision making problems in many areas. The main starting point of this study was to unearth the crucial studies on “decision making for a better power quality,” which is at the intersection of these two important issues. In this direction, the deficiency in the literature was noticed, the related studies were examined, and the methodological features and prominent aspects of the studies in different categories were examined. The active use of many decision-making methods in the search for solutions to different power quality problems has been demonstrated. The conclusion that decision-making mechanisms offer effective solutions in solving power quality problems has been more clearly emphasized in this study. This review furnishes researchers with crucial insights into current trends in power quality and multi-criteria decision-making research. It also delineates potential avenues for additional research in this increasingly popular field.

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Improved hierarchical decision making policy for reliable and green electricity grid

Cited by 2 publications

References 2 publications

Recent Developments in Machine Learning for Energy Systems Reliability Management

Recent Developments in Machine Learning for Energy Systems Reliability Management

Decision making methods used for improving power quality to meet the sustainable energy targets

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