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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Online Access: | https://www.mdpi.com/1996-1073/11/12/3296 |
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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 |
work_keys_str_mv |
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