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Quantifying the Effect on the Load Shifting Potential of Buildings due to Ancillary Service Provision
Optimization and Control · Submitted 22 May 2016
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Factors affecting the LSP are found to be as: (1) physics of the model, (2) the nature of price signal and (3) the competency of the reserve price with respect to the energy price.
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The abstract, sentence by sentence
This paper analyzes the pessimistic effect on the inherent load shifting potential (LSP) of buildings due to the participation in the reserve market. A generic model-based optimization approach is deployed, which uses a validated dynamic model along with its experienced external and internal disturbances, to quantify the LSP in the presence of various price signals. The theoretical maximum LSP is obtained using a base energy price without the provision of ancillary services (AS). The deviation from the base case LSP is observed after including the time varying energy and the reserve price from the spot market. Factors affecting the LSP are found to be as: (1) physics of the model, (2) the nature of price signal and (3) the competency of the reserve price with respect to the energy price. Due to its simple formulation, low computation requirements, and modular nature, the method proposed in this paper can easily be deployed by retailers and system operators for the assessment of monetary incentives as well as qualified load type for various demand response (DR) services in liberalized markets.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | This paper analyzes the pessimistic effect on the inherent load shifting potential (LSP) of buildings due to the participation in the reserve market. | contribution 0.96 | 0.83 | 0.28 | asserted 0.94 |
| s1 | A generic model-based optimization approach is deployed, which uses a validated dynamic model along with its experienced external and internal disturbances, to quantify the LSP in the presence of various price signals. | method 1.00 | 0.92 | 0.04 | asserted 1.00 |
| s2 | The theoretical maximum LSP is obtained using a base energy price without the provision of ancillary services (AS). | method 0.95 | 0.87 | 0.06 | asserted 1.00 |
| s3 | The deviation from the base case LSP is observed after including the time varying energy and the reserve price from the spot market. | result 0.49 | 0.89 | 0.09 | asserted 0.99 |
| s4 | Factors affecting the LSP are found to be as: (1) physics of the model, (2) the nature of price signal and (3) the competency of the reserve price with respect to the energy price. | result 0.90 | 0.91 | 0.35 | asserted 1.00 |
| s5 | Due to its simple formulation, low computation requirements, and modular nature, the method proposed in this paper can easily be deployed by retailers and system operators for the assessment of monetary incentives as well as qualified load type for various demand response (DR) services in liberalized markets. | contribution 0.60 | 0.52 | 0.13 | asserted 0.66 |
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Original abstract
This paper analyzes the pessimistic effect on the inherent load shifting potential (LSP) of buildings due to the participation in the reserve market. A generic model-based optimization approach is deployed, which uses a validated dynamic model along with its experienced external and internal disturbances, to quantify the LSP in the presence of various price signals. The theoretical maximum LSP is obtained using a base energy price without the provision of ancillary services (AS). The deviation from the base case LSP is observed after including the time varying energy and the reserve price from the spot market. Factors affecting the LSP are found to be as: (1) physics of the model, (2) the nature of price signal and (3) the competency of the reserve price with respect to the energy price. Due to its simple formulation, low computation requirements, and modular nature, the method proposed in this paper can easily be deployed by retailers and system operators for the assessment of monetary incentives as well as qualified load type for various demand response (DR) services in liberalized markets.
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