Open AccessEnvironmentally constrained reliability‐based generation maintenance scheduling considering demand‐side management
Author(s) -
MollahassaniPour Mojgan,
Rashidinejad Masoud,
PourakbariKasmaei Mahdi
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5713
Subject(s) - scheduling (production processes) , reliability (semiconductor) , incentive , time horizon , reliability engineering , computer science , total cost , operations research , mathematical optimization , economics , engineering , power (physics) , mathematics , microeconomics , physics , quantum mechanics
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.