This letter illustrates two multi-agent greedy demand-side response control schemes for networks of Thermostatically Controlled Loads. The objective is to provide simple but effective local control actions such that the overall power consumption tracks an aggregated desired profile. Compared with the existing literature the novelties are twofold. Since model-free, our schemes possess certain robustness features to the model deterioration and exogenous disturbances. Since greedy, they are of easy implementation also on cheap development boards which do not support optimization software, moreover because asynchronous do not require any network-wide synchronization event. Specifically, Algorithm 1 is very simple but it is applicable only on K-regular communication topologies. Such prerequisite is then removed in Algorithm 2 by including within its instruction list a dynamic consensus protocol to estimate the mean network power consumption. Performance analysis and numerical simulations confirm the effectiveness of the schemes.

Distributed Asynchronous Greedy Control of Large Networks of Thermostatically Controlled Loads for Electric Demand Response

Kaheni, M.;Pilloni, A.;Usai, E.;Franceschelli, M.
Ultimo
2022-01-01

Abstract

This letter illustrates two multi-agent greedy demand-side response control schemes for networks of Thermostatically Controlled Loads. The objective is to provide simple but effective local control actions such that the overall power consumption tracks an aggregated desired profile. Compared with the existing literature the novelties are twofold. Since model-free, our schemes possess certain robustness features to the model deterioration and exogenous disturbances. Since greedy, they are of easy implementation also on cheap development boards which do not support optimization software, moreover because asynchronous do not require any network-wide synchronization event. Specifically, Algorithm 1 is very simple but it is applicable only on K-regular communication topologies. Such prerequisite is then removed in Algorithm 2 by including within its instruction list a dynamic consensus protocol to estimate the mean network power consumption. Performance analysis and numerical simulations confirm the effectiveness of the schemes.
2022
Demand response
greedy control
multiagent systems
thermostatically controlled loads
Demand Response; Greedy Control; Multiagent Systems; Thermostatically Controlled Loads; Multi-agent Systems; Electric Demand Response
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/340591
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