Optimal Dispatch of Multiple Interconnected-Integrated Energy Systems Considering Dynamic Interactive Pricing Mechanism and Aggregated Demand Response
SSRN, ISSN: 1556-5068
2024
- 113Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This paper investigates the balancing and scheduling of integrated energy systems (IESs) spanning across geographically adjacent areas and regions that involve multiple energy vectors and multiple stakeholders. This is through an extremely complex problem to be formulated and solved, but often leading to enormous technical and economic benefit if the synergies among different energy vectors and the aggregated demand response (ADR) are fully utilized. To achieve the objective, a multiple interconnected-integrated energy systems (MI-IESs) model based on energy interaction and ADR is first established to capture the coupling relationship between different energy vectors. Then, an ADR mechanism is proposed, based on centralized dispatching by the IES operator (IESO) and distribution coordination of IESs, and further assisted with a dynamic interactive pricing mechanism based on load time distribution and renewable energy consumption level. To optimize the operation of such a complex energy system, the MI-IESs model is first decoupled, then an adaptive step size regularized alternating direction multiplier method (AR-ADMM) is proposed to solve the energy dispatch problem, while the information privacy of each IES is also preserved. The simulation results show that the proposed scheduling strategy can not only effectively balance the benefits of individual IES and MI-IESs, but also achieve a win-win situation between MI-IESs and the IESO, and the adopted solution algorithm protects the data privacy of MI-IESs. Furthermore, the solution time of the proposed AR-ADMM algorithm is 13% less than that of the conventional ADMM (C-ADMM) algorithm.
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