Uncertain two-stage chance-constraint low carbon power optimized planning method

Abstract

The invention relates to an uncertain two-stage chance-constraint low carbon power optimized planning method, and belongs to the technical field of power planning. The method comprises that a low carbon power planning model is established by combining historical and prediction data obtained from a scheduling system and a load prediction system in the smart power grid with an energy-saving emission-reduction index and carbon discharge transaction price data and taking maximizing the profit as a goal; power demand, carbon discharge quota and an over-generation risk are involved into the plan viaa chance-constraint way, a two-stage random planning method is used, a two-stage chance-constraint low carbon power plane model is established by optimizing, uncertain parameters in the model are setinto an interval form, and a stable feasible interval solution is obtained. The interval solutions obtained for decision targets in different plan periods can help a decision maker make a balance between the system benefit and environment target, a more reliable scheme is provided for power production, the economic benefit of a power enterprise can be improved, and sustainable development of theregional economy is facilitated.

Description

technical field [0001] The invention belongs to the technical field of power planning, and in particular relates to an uncertain two-stage opportunity-constrained low-carbon power optimization planning method. Background technique [0002] CO 2 The total emission control is a complex system engineering with dynamic and uncertain characteristics. With the full implementation of carbon trading in China, power companies, one of the key carbon emission industries, will face more complicated external factors. In addition, the initial allowance allocation method of carbon emission trading will also change after the start-up period of the first phase. The proportion of free allowances will decrease after the carbon trading mechanism matures. Enterprise production planning will have a profound impact. Reasonable and effective power system planning and operation methods will be a powerful means to ensure the safe and stable operation of the power system to achieve efficient carbon...

AI Technical Summary

Problems solved by technology

The current mainstream research tool is to adopt the idea of ​​optimization model, but in the face of a large number of policy variables and technological progress, the existing simple model cannot fully reflect the interaction between energy production mode, consumption technology and policy variables

For example, the LEAP model is difficult to fully consider technological progress and policy implementation costs, and cannot fully reflect market supply and demand signals

The MARKAL model requires a large amount of input data. Due to the limitation of the model's computing power and availability, some data have to be averaged, which will affect the calculation results of the model under different conditions.

[0005] In addition, although researchers have carried out research on the carbon trading market from different perspectives, there are few studies on the impact of different carbon trading policy scenarios on power planning and CO2. 2 The impact of emissions does not provide advance plans for the allocation of various resources for regional low-carbon power production and the optimal production situation under different carbon quota scenarios; and it is rare to incorporate uncertain factors such as power demand and over-power generation risks into power production planning. Related research

Since China's carbon emission trading system is still in its infancy, the trading and allowance allocation mechanism has not yet been perfected

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