Paper
16 October 2024 Optimized scheduling for demand response in a distributed CHP-VPP park with thermal and cold energy storage devices
Fengqing Du, Tiantian Chen, Zhongfang Li
Author Affiliations +
Proceedings Volume 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024); 132910W (2024) https://doi.org/10.1117/12.3033490
Event: Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 2024, Changchun, China
Abstract
A virtual power plant has the capability to aggregate decentralized energy resources, including generation, storage, and demand, thereby enhancing the flexibility of the power system and providing support for the integration of new energy sources and the development of innovative power systems. This paper focuses on a distributed industrial and commercial park with thermal and cold energy storage facilities, constructing a microgrid structure for the Virtual Power Plant (VPP) park. Unit models for energy production, conversion, and storage devices within the park are established. The objective function of minimizing operational costs for the park is considered, taking into account constraints related to energy balance within the park, grid interactions, and device operations. An optimization scheduling model for the distributed combined cooling, heating, and power (CCHP) VPP park, incorporating thermal and cold energy storage, is developed. The inclusion of energy conversion equipment such as gas-fired boilers and electric refrigeration, along with energy storage facilities like thermal and cold storage, effectively enhances the flexibility of energy supply scheduling within the park. This allows for the decoupling of heating, cooling, and electricity scheduling and enables the time-shifting of energy consumption, leading to a noticeable increase in the potential and profitability of the distributed VPP park's participation in power demand response. Finally, a case study is conducted to validate the proposed model, using a real VPP park in Shanghai, China, participating in peak shaving demand response. The results indicate that the distributed CCHP VPP park, equipped with thermal and cold energy storage facilities, can provide peak shaving and load-filling capabilities to the power system. Furthermore, the effective integration of energy storage enhances the overall flexibility of the VPP park, and appropriate demand response compensation mechanisms effectively incentivize its participation in the demand response market.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Fengqing Du, Tiantian Chen, and Zhongfang Li "Optimized scheduling for demand response in a distributed CHP-VPP park with thermal and cold energy storage devices", Proc. SPIE 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 132910W (16 October 2024); https://doi.org/10.1117/12.3033490
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KEYWORDS
Silicon

Turbines

Distributed interactive simulations

Energy efficiency

Absorption

Autoregressive models

Power grids

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