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 signalsas 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.
Highlights
A NCILLARY services (AS) are key elements to guarantee the stability and continuity of the electricity supply
An artificial neural network (ANN) model is developed based on the mixed-integer linear program (MILP) problem to generate appropriate prices to achieve the required flexibility
Aggregate price response of consumers is modelled through an aggregate price response (APR) function and appropriate delta prices are generated by a PI controller
Summary
A NCILLARY services (AS) are key elements to guarantee the stability and continuity of the electricity supply. The FlexPower project [14] proposed a real-time market for balancing power considering participation of aggregated small-scale DER In these papers, a holistic approach that can facilitate demand flexibility procurement from different sectors with various capabilities in a simple and practical structure has not been offered and the impact of the proposed method has not been investigated on the performance of frequency and voltage regulation at the TSO and DSO levels, respectively. In this case, every time a change in consumption/generation occurs at one level of the grid, LFC model and PF problem are solved to determine the new condition of the grid, i.e., frequency and nodal voltages.
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