Micro-energy network system and collaborative optimization operation control method thereof
A technology of micro-energy and energy conversion, applied in solar heating systems, design optimization/simulation, single-grid parallel feeding arrangement, etc. Restricting the local consumption of renewable energy and other issues to achieve the effect of alleviating the pressure of environmental pollution, making full use of it and improving energy efficiency
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Embodiment 1
[0032] This embodiment is used to provide a micro-energy grid system. The system is a micro-energy grid system composed of power supply, heating and cooling that operates independently with multiple energy flows. A micro-energy grid is formed through source-grid-load-storage network. Such as figure 1 As shown, the micro-energy grid system includes an energy supply side, an energy conversion device and a load side; the energy supply side includes a wind power generation device, a photovoltaic power generation device, a solar aluminum exhaust pipe heating device, a solar aluminum exhaust pipe refrigeration Boiler; the load side includes electric load, cooling load and heat load; the heat load includes low-temperature hot water load, medium-temperature hot water load, high-temperature hot water load and high-temperature steam load; the energy conversion device includes an electric heat pump; In the micro-energy grid system provided in this embodiment, the heat load is divided in...
Embodiment 2
[0063] This embodiment is used to provide a collaborative optimization operation control method for a micro-energy network system, which controls the above-mentioned micro-energy network system to work, taking into account the randomness and volatility of the power output of renewable energy equipment in the short-term scale of the micro-energy network system and user energy load changes, the real-time rolling optimization operation of micro energy network equipment is realized through the method of model predictive control. Such as figure 2 As shown, the collaborative optimization operation control method includes the following steps:
[0064] Step 101, according to the weather data, predict the power output value of the renewable energy equipment through deep learning to obtain the predicted power output value of the renewable energy equipment; the weather data includes temperature, humidity, air pressure, air density, and solar radiation intensity , cloud coverage, surfac...
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