Abstract
Virtual power plant is an integrated technology and operation mode to realize air-conditioning load participating in power system operation, further benefitting low carbon renewable energy applications. However, the principle of multi-system coupling in central air-conditioning poses a challenge to normal load regulation. Besides, the uncertainties of demand-side resources bring risks to the operation of virtual power plant. In this paper, the regulation characteristics of central air conditioning are obtained by experiment, while the potential of central air conditioning is quantified by a thermodynamic model, further resulting in the central air conditioning could be transformed into a virtual unit model. Then the dynamic capacity optimization strategy is formulated based on the risk measurement theory, while the generation task decomposition strategy is also formulated based on the equal increase rate criterion, thus forming a two-tier operation strategy of virtual power plant. Finally, illustrative case study is constructed to quantitatively analyze the power generation capacity and effectiveness of the virtual power plant. The effectiveness and practicability of the proposed strategy is also verified to benefit low carbon energy applications.
Highlights
In recent years, the proportion of renewable energy integrated into the power grid has been increasing, and the power load characteristics have been deteriorating
This paper proposes a dynamic optimizing strategy for virtual power plant (VPP) capacity based on the risk measurement method, where risks are simulated through historical losses and updated on a rolling basis according to the operating status of VPP, the operating strategy is actively modified and the risk is averted
This paper proposes a hybrid artificial intelligence strategy to address the operational problem of VPPs containing numerous distributed Central air-conditioner (CAC) resources
Summary
The proportion of renewable energy integrated into the power grid has been increasing, and the power load characteristics have been deteriorating. The coordinated control center calculates the dynamic capacity parameters of the VPP and decomposes the generation tasks to each CAC virtual unit after determining them from the power market. Due to many uncertainties in the real environment, such as the reduction in the number of air-conditioning virtual units, sudden changes in outdoor temperature, and actual output not matching expectations, the VPP is penalized for failing to complete its generation tasks. VPPrisk from the market rises rapidly when the uncertainties exceed this limit
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
