An operation optimization method for an electrothermal coupling integrated energy system
An integrated energy system and operation optimization technology, applied in data processing applications, forecasting, instruments, etc., can solve problems such as affecting user comfort, adverse effects of integrated energy system operation, and impact of model resolution on the accuracy of operation optimization results.
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Embodiment 1
[0070] An electrothermal coupling integrated energy system operation optimization method, such as Figure 4 shown, including the following steps:
[0071] S1, establish the objective function for the operation optimization of the electrothermal coupling integrated energy system, the objective function includes the cost of purchasing natural gas for the integrated energy system, the cost of purchasing electricity from the grid for the integrated energy system, and the income from selling electricity to the grid, and the cost of natural gas is The cost of purchasing electricity from the grid for the integrated energy system is The income of the integrated energy system from selling electricity to the grid is Among them, Δt d Scheduling instruction cycles for the integrated energy system; t d is the scheduling period; T d for t d collection; c gas , c grid,s Respectively, the calorific value price of natural gas, the price of electricity purchased from the grid, and t...
Embodiment 2
[0122] Take an electrothermal coupling integrated energy system as an example. Such as Figure 5 As shown, the system includes a 5MW gas turbine (GT), a 5MW gas boiler (GB), a fan with a capacity of 1.5MW and a heat storage tank with a capacity of 5MWh. The heating network consists of 6 nodes, of which node 1 is connected to the CHP system, and nodes 4, 5 and 6 are respectively connected to heat loads. The running optimization period is 24h. Heat network and heat load model resolution △t in the operation optimization process d The values of are 1h, 30min, and 10min, a total of three scenarios.
[0123] The operating costs of the system in several scenarios are shown in Table 1. Taking the heat load at node 5 as an example, the optimized results and actual simulation results of the heat medium temperature at node 5 are as follows: Figure 6 As shown, the optimization results of the indoor temperature of the building at this node and the actual simulation results are as fo...
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