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Robust stochastic programming method and system for data-driven integrated energy system
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Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
An integrated energy system, data-driven technology, applied in data processing applications, resources, forecasting, etc.
Pending Publication Date: 2022-02-25
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
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However, since the worst case rarely occurs in reality, robust strategies may be conservative and thus suboptimal in practice
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Embodiment 1
[0068] Such as figure 1 As shown, the embodiment of the present disclosure provides a data-driven method for robust stochastic programming of an integrated energy system, including the following steps:
[0069] S01, constructing a supply reliability model of renewable energy generation and load from historical data by surrounding an empirical probability density function with a fuzzy probability density function;
[0070] S02, quantifying the distance between the fuzzy probability density function and the empirical probability density function through the Kullback-Leibler divergence measure;
[0071] S03, under the worst-case distribution of fuzzy set constraints, minimize the sum of investment costs and expected operating costs throughout the service period through the objective function;
[0072] S04, Robust chance constraints are adopted in the supply reliability model under extreme conditions.
[0073] The data-driven comprehensive energy system robust stochastic program...
Embodiment 2
[0249] Such as Figure 4 As shown, the embodiment of the present disclosure provides a terminal energy planning system considering the constraint of the moment of inertia, including:
[0250] Data-driven systems for robust stochastic programming of integrated energy systems, including:
[0251] a modeling module configured to: construct a supply reliability model of renewable energy generation and load from historical data by surrounding an empirical probability density function with a fuzzy probability density function;
[0252] A quantization module configured to: quantify the distance between the fuzzy probability density function and the empirical probability density function through the Kullback-Leibler divergence measure;
[0253] The calculation module is configured to: under the worst-case distribution of fuzzy set constraints, the sum of the investment cost and the expected operating cost during the entire service period is minimized through an objective function;
...
Embodiment 4
[0257] An embodiment of the present disclosure provides a storage medium on which a program is stored, and when the program is executed by a processor, the steps in the method for robust stochastic programming of a data-driven integrated energy system provided by the above-mentioned embodiments are implemented, including:
[0258] S01, constructing a supply reliability model of renewable energy generation and load from historical data by surrounding an empirical probability density function with a fuzzy probability density function;
[0259] S02, quantifying the distance between the fuzzy probability density function and the empirical probability density function through the Kullback-Leibler divergence measure;
[0260] S03, under the worst-case distribution of fuzzy set constraints, minimize the sum of investment costs and expected operating costs throughout the service period through the objective function;
[0261] S04, Robust chance constraints are adopted in the supply re...
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Abstract
The invention provides a robust stochastic programming method for a data-driven integrated energy system, and belongs to the technical field of energy planning. According to the specific scheme, a fuzzy probability density function surrounds an empirical probability density function to construct a renewable energy power generation and load supply reliability model from historical data; the distance between the fuzzy probability density function and the empirical probability density function is quantized through Kullback-Leibler divergence measurement. under the worst condition distribution of the fuzzy set constraint, the sum of the investment cost and the expected operation cost in the whole service period is minimized through an objective function; under extreme conditions, the supply reliability model adopts robust opportunity constraint. And under the constraint of the worst distribution condition of the fuzzy set, the sum of the construction cost and the expected life cycle operation cost is minimum. The network energy flow under the normal operation condition and the supply and demand reliability under the extreme condition are considered. The invention further discloses a receiving end energy planningsystem considering the rotational inertia constraint.
Description
technical field [0001] This application relates to the technical field of energy planning, in particular to a data-driven method and system for robust stochastic programming of an integrated energy system. Background technique [0002] The statements in this section merely provide background art related to this application and do not necessarily constitute prior art. [0003] The excessive consumption of coal has caused serious air pollution problems in modern society. The shale revolution has made natural gas a promising clean fuel of the future. At the same time, the increased use of renewable energy sources such as wind and solar has significantly reduced CO2 emissions from the power sector. However, the power generation of wind farms and photovoltaic panels fluctuates greatly, requiring sufficient backup capacity and flexible resources to compensate for real-time imbalances, which pose great challenges to the operation of power systems. Gas-fired units can respond to ...
Claims
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