The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand

This paper presents an interactive trading decision between an electricity market operator, generation companies (GenCos), and the aggregators having demand response (DR) capable loads. Decisions are made hierarchically. At the upper-level, an electricity market operator (EMO) aims to minimise gener...

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Main Authors: Nur Mohammad, Yateendra Mishra
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/11/12/3296
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spelling doaj-eceebf474b034e64afe785bbe2e56c842020-11-24T21:35:10ZengMDPI AGEnergies1996-10732018-11-011112329610.3390/en11123296en11123296The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of DemandNur Mohammad0Yateendra Mishra1Department of Electrical Engineering and Electronic Engineering, Chittagong University of Engineering and Technology, Chittagong 4349, BangladeshSchool of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane 4000, AustraliaThis paper presents an interactive trading decision between an electricity market operator, generation companies (GenCos), and the aggregators having demand response (DR) capable loads. Decisions are made hierarchically. At the upper-level, an electricity market operator (EMO) aims to minimise generation supply cost considering a DR transaction cost, which is essentially the cost of load curtailment. A DR exchange operator aims to minimise this transaction cost upon receiving the DR offer from the multiple aggregators at the lower level. The solution at this level determines the optimal DR amount and the load curtailment price. The DR considers the end-user’s willingness to reduce demand. Lagrangian duality theory is used to solve the bi-level optimisation. The usefulness of the proposed market model is demonstrated on interconnection of the Pennsylvania-New Jersey-Maryland (PJM) 5-Bus benchmark power system model under several plausible cases. It is found that the peak electricity price and grid-wise operation expenses under this DR trading scheme are reduced.https://www.mdpi.com/1996-1073/11/12/3296Demand responsedemand response exchangeDR aggregatorsgeneration companiesDR transaction costhierarchical decision making
collection DOAJ
language English
format Article
sources DOAJ
author Nur Mohammad
Yateendra Mishra
spellingShingle Nur Mohammad
Yateendra Mishra
The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
Energies
Demand response
demand response exchange
DR aggregators
generation companies
DR transaction cost
hierarchical decision making
author_facet Nur Mohammad
Yateendra Mishra
author_sort Nur Mohammad
title The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
title_short The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
title_full The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
title_fullStr The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
title_full_unstemmed The Role of Demand Response Aggregators and the Effect of GenCos Strategic Bidding on the Flexibility of Demand
title_sort role of demand response aggregators and the effect of gencos strategic bidding on the flexibility of demand
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-11-01
description This paper presents an interactive trading decision between an electricity market operator, generation companies (GenCos), and the aggregators having demand response (DR) capable loads. Decisions are made hierarchically. At the upper-level, an electricity market operator (EMO) aims to minimise generation supply cost considering a DR transaction cost, which is essentially the cost of load curtailment. A DR exchange operator aims to minimise this transaction cost upon receiving the DR offer from the multiple aggregators at the lower level. The solution at this level determines the optimal DR amount and the load curtailment price. The DR considers the end-user’s willingness to reduce demand. Lagrangian duality theory is used to solve the bi-level optimisation. The usefulness of the proposed market model is demonstrated on interconnection of the Pennsylvania-New Jersey-Maryland (PJM) 5-Bus benchmark power system model under several plausible cases. It is found that the peak electricity price and grid-wise operation expenses under this DR trading scheme are reduced.
topic Demand response
demand response exchange
DR aggregators
generation companies
DR transaction cost
hierarchical decision making
url https://www.mdpi.com/1996-1073/11/12/3296
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