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Flexible optimization scheduling method considering wind-solar and load uncertainty for comprehensive energy system

An integrated energy system, uncertainty technology, applied in the field of flexible optimal scheduling of integrated energy systems considering wind and load uncertainties, can solve unschedulable, cooling load, heating load and electric load uncertainties, large power generation prediction errors And other issues

Pending Publication Date: 2020-10-23
RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER +1
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AI Technical Summary

Problems solved by technology

[0002] The integrated energy system is a dynamic system that integrates distributed renewable energy such as wind energy and solar energy, and balances the power supply and load in real time. However, wind power generation and solar photovoltaic power generation have the characteristics of randomness, volatility, and non-dispatchability. Large, difficult to control, and there are uncertainties in the cooling load, heating load and electric load provided by the integrated energy system to users, which leads to randomness in the system at both ends of the power generation side and the load demand side

Method used

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  • Flexible optimization scheduling method considering wind-solar and load uncertainty for comprehensive energy system
  • Flexible optimization scheduling method considering wind-solar and load uncertainty for comprehensive energy system
  • Flexible optimization scheduling method considering wind-solar and load uncertainty for comprehensive energy system

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Embodiment

[0218] Taking the IEEE.15 node system as an example, such as figure 2 shown. Validate the effectiveness of the invention by carrying out numerical simulations on a large amount of data and scenarios. The integrated energy system includes DES / CHP unit, plug-in hybrid electric vehicle (PHEV), photovoltaic panel (PV), wind farm (PW) electric boiler and thermal energy storage device (TES). There is an exchange of cold and hot electric energy between each node.

[0219] Step 1: Scenario generation, the stochastic optimization expectation model with random variables can use the expected value model of convex stochastic optimization, as shown in formula (1-1).

[0220] The steps to generate a scene by Monte Carlo sampling are as follows:

[0221] ① Assuming that the random variable obeys a normal distribution, the value of the random variable is discretized into 7 intervals with 0 as the mean value. The width of each interval is the prediction error of the random variable, and ea...

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Abstract

The invention discloses a flexible optimization scheduling method considering wind-solar and load uncertainty for a comprehensive energy system. The method comprises the steps of generating a scene through Monte Carlo sampling; aiming at uncertainty of wind-solar output and cooling-heating-power load requirements of a comprehensive energy system, a processing means of a multi-scene method is adopted for analysis, and a quick preceding generation method of probability distance is adopted for scene reduction; establishing a target function by taking minimum operation cost adjustment of the comprehensive energy system for conversion among multiple scenes as a target; establishing constraint conditions; a genetic algorithm is adopted to solve and analyze a model composed of an objective function and constraint conditions, the adjusted operation cost between system scenes and the influence of LNG cold energy power generation on the operation cost of the comprehensive energy system are compared, and comprehensive energy system optimized operation strategies under different electricity price scenes are provided.

Description

technical field [0001] The invention relates to an integrated energy scheduling method, and more specifically relates to a flexible optimal scheduling method for an integrated energy system that considers wind and load uncertainties. Background technique [0002] The integrated energy system is a dynamic system that integrates distributed renewable energy such as wind energy and solar energy, and balances power and load in real time. However, wind power and solar photovoltaic power generation have the characteristics of randomness, volatility, and non-dispatchability. It is relatively large and difficult to control. At the same time, there are uncertainties in the cooling load, heating load and electric load provided by the integrated energy system to users, which leads to the randomness of the system at both ends of the power generation side and the load demand side. On the one hand, flexible optimal dispatch should consider the risks brought by uncertain factors flexibly a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/06315G06Q10/06312G06Q50/06
Inventor 吴健綦陆杰梁荣崔灿杨波李昭刘蕊张雯刘钊杨慎全王延朔张博颐李昊
Owner RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER
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