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A method for optimize thermoelectric load distribution of a regional multi-energy system

A load distribution and optimization method technology, applied in system integration technology, information technology support systems, instruments, etc., can solve problems such as inability to guarantee work efficiency, energy waste, and inability to respond in time to real-time demands of thermal and electrical loads, etc., and achieve high precision The effect of optimal operation allocation strategy, avoiding energy waste, and good market application prospects

Pending Publication Date: 2018-12-14
HARBIN INST OF TECH +4
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The present invention aims to solve the problem that the existing thermoelectric load distribution method cannot respond in time to the non-determined real-time demand of thermoelectric load. On the other hand, while all units meet the total demand for power generation, it is impossible to ensure that each unit can be distributed through thermoelectric distribution among units. The working efficiency is the highest, which leads to the problem of energy waste. The present invention provides a thermal and electrical load distribution optimization method for cogeneration units

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  • A method for optimize thermoelectric load distribution of a regional multi-energy system
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specific Embodiment approach 1

[0038] Specific implementation mode 1: A method for optimizing thermoelectric load distribution of a regional multi-energy system described in this implementation mode, the method includes the following steps:

[0039] Step 1. According to the principle of maximum consumption of new energy, obtain the historical data set P z ' and Q z ';

[0040] P z ′ means that all heating and extraction units should reach the total amount of electricity;

[0041] Q z ′ means that all heat supply and extraction units should reach the sum of heat;

[0042] Step 2: Establish a thermoelectric load forecasting model, and for the historical data set P z ' and Q z 'Carry out data training and calculate P z and Q z predicted value of

[0043] P z Indicates that all heating and extraction units within the next 0 to 24 hours should reach the total amount of electricity;

[0044] Q z Indicates that all heating and extraction units within the next 0 to 24 hours should reach the total heat; ...

specific Embodiment approach 2

[0049] Specific embodiment 2: The difference between this embodiment and the method for optimizing thermoelectric load distribution in a regional multi-energy system described in specific embodiment 1 is that in step 1, the historical data set P z ' and Q z 'Specifically:

[0050]

[0051] Among them, P all Indicates the total power demand, P wind Indicates the real-time maximum power generation of wind power, P sun1 Indicates the real-time maximum power of photovoltaic power generation, P sun2 Indicates the real-time maximum power of solar thermal power generation, Q all Indicates the total calorie demand, Q sun Indicates solar heat storage, Q d Indicates the electric heat generated by the electric boiler.

[0052] In this implementation mode, a regional energy complementary model considering the maximum consumption of new energy is proposed, see formula (1) for details, and fundamentally save coal consumption.

specific Embodiment approach 3

[0053] Embodiment 3: The difference between this embodiment and the method for optimizing thermoelectric load distribution in a regional multi-energy system described in Embodiment 1 is that in step 2, the thermoelectric load forecasting model is implemented using a BP neural network model.

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Abstract

The invention relates to a thermoelectric load distribution optimization method of a regional multi-energy system, belonging to the technical field of energy saving. The method solves the problem thatthe existing thermoelectric load distribution method cannot make timely response to the uncertain thermoelectric load real-time demand, and all the units cannot guarantee the maximum work efficiencyof each unit through the thermoelectric distribution between the units while meeting the total power generation demand, which leads to energy waste. According to the principle of maximum new energy dissipation, the historical data sets Pz' and Qz' are obtained. The thermoelectric load forecasting model is established, and the data of Pz 'and Qz' are trained to calculate the forecasting values of Pz and Qz. The predicted values of Pz and Qz are modified according to the coupling relationship between the number of all heat-supply and extraction units and the heat and electric load of all back-pressure units. The corrected values of Pz and Qz are distributed by the optimization algorithm, and the thermoelectric load distribution results of each heat-supply and extraction unit are calculated,thus the optimization of thermoelectric load distribution is completed. It is mainly used to jointly forecast and optimize the thermoelectric load of regional multi-energy system.

Description

technical field [0001] The invention belongs to the technical field of energy saving. Background technique [0002] With the development of renewable energy and the increase in the cost of fossil fuels, the power industry is paying more and more attention to the strategy of hybrid power generation; especially to maximize the use of wind, light and other renewable energy for power generation, and fundamentally reduce the consumption of fossil fuels. However, the uncertainty of the form of wind power and photovoltaic power generation brings challenges to the stability of the regional energy complementary system; at the same time, how does the power plant distribute the heat and electricity load among the units according to the type of the unit and the difference of the unit type, so that The lowest energy consumption and the best economic benefits of the entire power plant are practical problems faced in the production and operation of the power plant. [0003] In order to so...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02E40/70Y04S10/50
Inventor 付俊丰万杰叶青俞卫星姚坤李逸飞徐新果郑敏聪居国腾陈欢陈小强顾涤枫赵佳俊金康华沈伟军鄂鹏
Owner HARBIN INST OF TECH