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      Environmentally constrained reliability-based generation maintenance scheduling considering demand-side management

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          Abstract

          This study scrutinises the impacts of demand-side resources (DSRs) on the power system reliability via a novel multi-target generation maintenance (GM) model. The nominated model uses the lexicographic preferences to hierarchically consider the environmental issues, economics, and reliability of power systems. In this regard, the produced emission, which reflects the per unit produced pollutant values in different locations, is minimised. Taking into account the environmental constraints, the total incurred expenditures, including operating and maintenance costs, reserves costs, and total incentives are also minimised. Subsequently, the GM problem considering the correlation constraints is handled while the reliability index, the average net reserve value, is maximised over the scheduling horizon. The DSRs improve the system reliability such that the total costs, and emission level, do not exceed the situation in which DSRs are not available. The GM scheduling is a highly complicated problem and considering DSRs makes it even more complicated. To handle this problem more efficiently, appropriate linearisation technique is used, while the proposed model is formulated in GAMS modelling language. To evaluate the capability of DSRs in system reliability improvement, the modified 24-bus IEEE-RTS is conducted. Results indicate that by selecting proper location and incentives, significant improvement is obtained.

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          Most cited references29

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          IEEE Reliability Test System

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            GAMS, a user's guide

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              Investigation of Economic and Environmental-Driven Demand Response Measures Incorporating UC

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                Author and article information

                Contributors
                Journal
                IET-GTD
                IET Generation, Transmission & Distribution
                IET Gener. Transm. Distrib.
                The Institution of Engineering and Technology
                1751-8687
                1751-8695
                19 December 2018
                26 March 2019
                9 April 2019
                : 13
                : 7
                : 1153-1163
                Affiliations
                [1 ] Faculty of Electrical and Computer Engineering, University of Sistan and Baluchestan , Zahedan, Iran
                [2 ] Department of Electrical Engineering, Shahid Bahonar University of Kerman , Kerman, Iran
                [3 ] Department of Electrical Engineering and Automation, Aalto University , Maarintie 8, 02150 Espoo, Finland
                Article
                IET-GTD.2018.5713 GTD.2018.5713.R1
                10.1049/iet-gtd.2018.5713
                28c4da22-1d13-4f72-94bf-72250b4e3764
                © The Institution of Engineering and Technology
                History
                : 6 February 2018
                : 24 October 2018
                : 18 December 2018
                Page count
                Pages: 0
                Funding
                Funded by: Iran National Science Foundation
                Award ID: 96000319
                Categories
                Research Article

                Computer science,Engineering,Artificial intelligence,Electrical engineering,Mechanical engineering,Renewable energy
                power system reliability,reliability-based generation maintenance scheduling,reliability index,multitarget generation maintenance model,power generation scheduling,power systems,average net reserve value,environmental issues,emission level,GM scheduling,linearisation techniques,lexicographic preferences,GAMS modelling language,demand-side management,power generation reliability,demand-side resources,correlation constraints,power generation economics,GM problem,demand side management

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