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
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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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