English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The close integration of increasing operating units into an integrated energysystem (IES) results in complex interconnections between these units. Thestrong dynamic interactions create barriers to designing a successfuldistributed coordinated controller to achieve synergy between all the units andunlock the potential for grid response. To address these challenges, weintroduce a directed graph representation of IESs using an augmented Jacobianmatrix to depict their underlying dynamics topology. By utilizing thisrepresentation, a generic subsystem decomposition method is proposed topartition the entire IES vertically based on the dynamic time scale andhorizontally based on the closeness of interconnections between the operatingunits. Exploiting the decomposed subsystems, we develop a cooperativedistributed economic model predictive control (DEMPC) with multiple globalobjectives that regulate the generated power at the grid's requests and satisfythe customers cooling and system economic requirements. In the DEMPC, multiplelocal decision-making agents cooperate sequentially and iteratively to leveragethe potential across all the units for system-wide dynamic synergy.Furthermore, we discuss how subsystem decomposition impacts the design ofdistributed cooperation schemes for IESs and provide a control-oriented basicguideline on the optimal decomposition of complex energy systems. Extensivesimulations demonstrate that the control strategies with different levels ofdecomposition and collaboration will lead to marked differences in the overallperformance of IES. The standard control scheme based on the proposed subsystemconfiguration outperforms the empirical decomposition-based control benchmarkby about 20%. The DEMPC architecture further improves the overall performanceof the IES by about 55% compared to the benchmark.

Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy