Allocation of demand response resources: toward an effective contribution to power system voltage stability

In this study, capacity allocation of demand-response (DR) and the real-time savings earned from implementing DR programmes (DRPs) are investigated based on a mixed integer non-linear multi-objective programming (MINMOP) framework according to two conflicting concepts, titled; maximum achievable pot...

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Vydáno v:	IET generation, transmission & distribution Ročník 10; číslo 16; s. 4169 - 4177
Hlavní autoři:	Aghaei, Jamshid, Alizadeh, Mohammad Iman, Abdollahi, Amir, Barani, Mostafa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 08.12.2016
Témata:	augmented ε‐constraint method demand side management demand‐response capacity allocation DR programmes DR resource allocation DRPs IEEE 24‐bus reliability test system incentive payment integer programming maximum achievable potential MINMOP framework mixed integer nonlinear multiobjective programming framework network loss nonlinear programming off‐the‐shelf conventional optimisation software optimal generation scheduling cost power system reliability power system stability power system voltage stability RAP realistic achievable potential resource allocation RTS 24‐bus voltage drop voltage stability margin DR resource allocation RAP augmented ε-constraint method maximum achievable potential integer programming nonlinear programming IEEE 24-bus reliability test system network loss DRPs resource allocation power system reliability DR programmes off-the-shelf conventional optimisation software power system voltage stability optimal generation scheduling cost power system stability realistic achievable potential MINMOP framework mixed integer nonlinear multiobjective programming framework RTS 24-bus voltage drop incentive payment voltage stability margin demand side management demand-response capacity allocation MAP
ISSN:	1751-8687, 1751-8695
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