The electricity and steam integrated energy systems,which can capture waste heat and improve the overall energy efficiency,have been widely utilised in industrial ***,intensive and frequent changes in demands would le...
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The electricity and steam integrated energy systems,which can capture waste heat and improve the overall energy efficiency,have been widely utilised in industrial ***,intensive and frequent changes in demands would lead to model parameters with strong time-varying *** paper proposes a hybrid physics and data-driven framework for online joint state and parameter estimation of steam and electricity integrated energy *** on the physical non-linear state space models for the electricity network(EN)and steam heating network(SHN),relevance vector machine is developed to learn parameters'dynamic characteristics with respect to model states,which is embedded with physical ***,the online joint state and parameter estimation based on unscented Kalman filter is proposed,which would be learnt recursively to capture the spatiotemporal transient characteristics between electricity and *** IEEE 39-bus EN and the 29-nodes SHN are employed to verify the effectiveness of the proposed *** experimental results validate that the pro-posed method can provide a higher estimation accuracy than the state-of-the-art approaches.
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