Optimal control method for ground source heat pump refrigerating system

Abstract

The invention relates to an optimal control method for a ground source heat pump refrigerating system and belongs to the field of energy-saving optimal control for air conditioning systems of buildings. Multiple models are optimally combined, as along as a prediction model contains contrasting information of the system, the prediction model can be combined with multiple good prediction models for predicting even if the prediction model is poor in effect, and a predicting character of the system can still be improved; in order to improve final predicting precision, a control system operates a combined predicting method to comprehensively utilize information provided by various methods, loss of useful information caused by a single prediction module is avoided, randomness is reduced, and predicting precision is increased. The optimal value provided by the optimal control method is ensured to meet tail end load requirements and capable of minimizing energy consumption of the system. After the optimal set value is determined, a central refrigerating system of the ground source heat pump refrigerating system is controlled to operate in an optimal set working status.

Description

technical field [0001] The invention relates to an energy-saving optimization method for a ground-source heat pump refrigeration system, which belongs to the field of energy-saving optimization control of building air-conditioning systems. Background technique [0002] The energy consumption of the national economy mainly includes industrial energy consumption, transportation energy consumption and building energy consumption. With the steady advancement of my country's well-off society, the pace of urbanization is also increasing. The problem of building energy consumption caused by this cannot be ignored. Two-thirds of building energy consumption is consumed by air-conditioning systems. Under the current situation that building energy consumption accounts for an increasing proportion of total energy consumption, the energy saving of air-conditioning systems in buildings has become a focus and hot spot in the field of energy conservation. Today, when green and low-carbon lif...

AI Technical Summary

Problems solved by technology

[0009] The cooling capacity of the current cold station is determined by the following formula: , However, if a pump needs to be turned on or stopped at a certain moment, resulting in a sudden increase or decrease in the flow rate, it will inevitably lead to a large fluctuation in temperature. If the temperature test time is within the range of this large fluctuation, It will inevitably lead to unreasonable calculation of cooling capacity and large errors. In addition, the flow sensor is less reliable than the temperature sensor. The load calculated by this method may deviate greatly from the actual value under certain circumstances.

[0010]2), the balance between the cooling capacity of the cooler and the required cooling capacity at the end

[0011] Even if the cooling capacity test results are relatively accurate, matching the cooling capacity of the chiller with the required cooling capacity is still a big problem: if the water supply temperature is set at the set value , the chilled water flow rate is large enough, which indicates that the current cooling capacity can meet the requirements of the end of the building, so the actual measured cooling capacity is the required cooling capacity, when the supply water temperature is higher than the set value or the temperature difference between the supply and return water When the flow rate is low, it is very likely that the cooling capacity currently provided is lower than the required cooling capacity. The building has not reached the required working condition, but it may also be that the system is in a suitable operating state. How to distinguish between sufficient and insufficient, only It is often difficult to make judgments based on the water temperature and flow rate of the cold station test

[0012]3), "remedial" regulation lacks theoretical basis

All these factors will make online optimization control difficult in practice

[0023] In addition, because the entire refrigeration system is coupled to each other, to optimize the refrigeration system, the entire system must be analyzed in a closed-loop manner, and a certain subsystem cannot be analyzed separately from the whole. It is this strong coupling that makes it difficult to find a breakthrough in the first step of the optimal control work, which brings great difficulty to the optimal control of the refrigeration system

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