Abstract
With the development of smart grid and low-carbon electricity, a high proportion of renewable energy is connected to the grid. In addition, the peak-valley difference of system load increases, which makes the traditional grid scheduling method no longer suitable. Therefore, this paper proposes a two-stage low-carbon economic scheduling model considering the characteristics of wind, light, thermal power units, and demand response at different time scales. This model not only concerns the deep peak state of thermal power units under the condition of large-scale renewable energy, but also sets the uncertain models of PDR (Price-based Demand Response) virtual units and IDR (Incentive Demand Response) virtual units. Taking the system operation cost and carbon treatment cost as the target, the improved bat algorithm and 2PM (Two-point Estimation Method) are used to solve the problem. The introduction of climbing costs and low load operating costs can more truly reflect the increased cost of thermal power units. Meanwhile, the source-load interaction can weigh renewable energy limited costs and the increased costs of balancing volatility. The proposed method can be applied to optimal dispatch and safe operation analysis of the power grid with a high proportion of renewable energy. Compared with traditional methods, the total scheduling cost of the system can be reduced, and the rights and obligations of contributors to system operation can be guaranteed to the greatest extent.
Highlights
At present, a strong smart grid and ubiquitous power Internet of things are vigorously promoted in China
Considering the uncertainty of wind power, the thermal power unit and the incentive-based demand response (IDR) are adjusted in the storage station, which relieves the peaking pressure of the thermal power unit to a certain extent, so intraday scheduling, and the optimization scheduling results of each scheduling scene are analyzed
In case3, the demand response virtual unit participates in the scheduling, which reduces the system load uncertainty during the day-ahead and intraday stage, and effectively avoids the
Summary
A strong smart grid and ubiquitous power Internet of things are vigorously promoted in China. This paper comprehensively considers the characteristics of wind, solar, thermal units and demand response in different time scales, and proposes a day-ahead and intraday scheduling model to solve the low-carbon economic dispatch problem of multiple energy. In this model, the uncertainty model of day-ahead price demand response virtual units and intraday IDR virtual units are established, and the operation cost and slope climbing cost of thermal power units in deep peak regulation are concerned.
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