Abstract
In modern power systems with more renewable energy sources connected, the consideration of both security and economy becomes the key to research on power system optimal dispatch, especially when more participants from the source and load sides join in the interaction response activities. In this paper, we propose a two-stage dispatch model that contains a day-ahead multi-objective optimization scheduling sub-model that combines a hyper-box and hyper-ellipse space theory-based system security index in the first stage, and an intraday adjustment scheduling sub-model that considers active demand response (DR) behavior in the second stage. This model is able to quantitatively analyze the relationship between the security and economy of the system dispatch process, as well as the impacts of the interaction response behavior on the wind power consumption and the system’s daily operating cost. The model can be applied to the evaluation of the response mechanism design for interactive resources in regional power systems.
Highlights
With the advancement of green electricity, more clean and renewable power sources have been brought into global power systems
Active demand response (DR) components, such as smart household appliances, energy storage, and electric vehicles, can cooperate with renewable energy sources in power system operation [2], which can promote the consumption of renewable energy and achieve peak-shaving and valley-filling targets
The novel contributions of this work include: (1) a day-ahead multiobjective optimization model is established by extending the application of a hyper-box and hyper-ellipse space theory-based system security index; (2) an active DR model is formed according to different interaction and response characteristics in peak/valley load periods; and (3) by including the active DR model, the intraday rescheduling model is extended, which can conduce wind power consumption
Summary
[15] builds a flexible resource optimization dispatch model, including DR, energy storage, and electric vehicles, as well as designing a flexible ramp market based on interaction and response activities. To deal with the aforementioned issues, we proposed a two-stage cooperative dispatch model for power systems that considers security as well as a source-load interaction and response environment. The novel contributions of this work include: (1) a day-ahead multiobjective optimization model is established by extending the application of a hyper-box and hyper-ellipse space theory-based system security index; (2) an active DR model is formed according to different interaction and response characteristics in peak/valley load periods; and (3) by including the active DR model, the intraday rescheduling model is extended, which can conduce wind power consumption.
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