Abstract
This paper presents a new methodology to exploit consumers’ flexibility for the provision of ancillary services (AS) in the smart grid era. The proposed framework offers a control-based approach that adopts price signals as the economic driver to modulate consumers’ response. In this framework,
various system operators broadcast price signals independently to fulfil their AS requirements. Appropriate flexibility estimators are developed from the transmission system operator (TSO) and distribution system operator (DSO) perspectives for price generation. An artificial neural network (ANN) controller is used for the TSO to infer the price-consumption reaction from pools of consumers in its territory. A proportional-integral (PI) controller is preferred to represent the consumers’ price-response and generate time-varying electricity prices at the DSO level for voltage management. A multi-timescale simulation model is built in MATLAB to assess the proposed methodology in different operational conditions. Numerical analyses show the applicability of the proposed method for the provision of AS from consumers at different levels of the grid and the interaction between TSO and DSOs through the proposed framework.
various system operators broadcast price signals independently to fulfil their AS requirements. Appropriate flexibility estimators are developed from the transmission system operator (TSO) and distribution system operator (DSO) perspectives for price generation. An artificial neural network (ANN) controller is used for the TSO to infer the price-consumption reaction from pools of consumers in its territory. A proportional-integral (PI) controller is preferred to represent the consumers’ price-response and generate time-varying electricity prices at the DSO level for voltage management. A multi-timescale simulation model is built in MATLAB to assess the proposed methodology in different operational conditions. Numerical analyses show the applicability of the proposed method for the provision of AS from consumers at different levels of the grid and the interaction between TSO and DSOs through the proposed framework.
Original language | English |
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Journal | IEEE Transactions on Power Systems |
Volume | 35 |
Issue number | 3 |
Pages (from-to) | 1868 - 1880 |
ISSN | 0885-8950 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- Ancillary services
- TSO-DSO interaction
- Flexibility resources
- Demand response
- Artificial neural network