Comprehensive energy system scheduling method of dynamic time interval
An integrated energy system and dynamic time technology, applied in resources, instruments, data processing applications, etc., can solve problems such as scheduling methods that are rarely considered
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Embodiment 1
[0046] In terms of optimal dispatching of integrated energy systems, the current research can be based on the establishment of physical models of equipment for independent units and coupled units, economic models, and steady-state power flow models for power, natural gas, and thermal energy subsystems. The comprehensive energy optimal dispatch of specific systems such as heat can also form an optimal regulation strategy including energy conversion equipment. For the uncertainty of renewable energy such as wind power, it can also perform robust collaborative dispatch optimization, and it can also be mined through price information. However, most of these optimization scheduling methods are for optimal scheduling control of a certain time section or multiple time periods, and are still static optimization. Aiming at the fast dynamic and slow dynamic characteristics of electric power system, natural gas system, and thermal system at different time scales, there are also related st...
Embodiment 2
[0119] refer to image 3 , which is an example test system of an integrated energy system based on the improved IEEE 14-node distribution network system, 11-node natural gas distribution system, and 11-node thermal system, that is, the test example diagram. The natural gas flow rate is converted to the success rate unit according to the natural gas calorific value, and the day-ahead scheduling plan refers to Figure 4 , which is the day-ahead scheduling scheme of the dynamic time interval integrated energy system scheduling method in the test example. The day-ahead scheduling plan is also the reference trajectory of the intraday scheduling plan. The intraday scheduling plan is obtained based on the scheduling method. Refer to Figure 5 For illustration, take the intraday scheduling results in the time period of 18:00-20:45 as a display.
[0120] When the state error of the system is small, it can reduce the issuance of scheduling instructions and reduce the scheduling cost. ...
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