Integrated energy simulation of a deep level mine cooling system through a combination of forward and first-principle models applied to system-side parameters

Abstract

Highlights• Proposition of an integrated mine cooling system energy modelling method.• The model is be calibrated with system measured or manufacturer data.• Major energy consuming devices include chillers, cooling towers, pumps and fans.• Model parameter identification achieved RMSRE values between 0.0114 and 0.0651.• An overall absolute average error between 2.5% and 3.5% was obtained. 2 AbstractMine cooling systems typically account for around 25% of the total electrical energy consumption of deep level mines. Numerous energy saving strategies have been implemented; with various levels of success. Most of the previously implemented strategies involved load shifting, energy efficiency and demand reduction. To achieve this, some levels of control are often introduced to control chilled water consumption, water and air mass flow rates as well as scheduling cooling system operation in order to shift the load primarily to offpeak periods.To support and sustain further reduction of energy consumption and optimisation of savings, a simulation model of the integrated cooling system represented by smooth and continuous equations is needed to assist the optimisation computation. This study focused on developing such an integrated mine cooling system simulation model to mimic the thermal hydraulic behaviour along with the energy consumption of the complete mine cooling system. This was achieved by coupling various models representing the major cooling system components such as chillers, cooling towers, pumps and fans together. Although various cooling system energy simulations were considered before, very few quantify the simulation accuracy on a component basis; furthermore, only limited cases were found where the entire system was considered. For these cases not all components were always based on explicit models which would eliminate the requirement for iterative computation which deter optimisation applications.The simulation model was used to predict the energy consumption of the integrated cooling system of a deep level gold mine in South Africa. The simulation model obtained an average error when compared to the mine's system data of 3.5% for a selected dataset and 2.5% for 3 another dataset one month later. The successful energy simulation of an integrated mine cooling system would allow for a holistic view on the total power consumption as one parameter or any combination of parameters of the system changes. NomenclatureA area [m²] BAC bulk air cooler C local loss coefficient specific heat capacity [J/kg K] CC cooling capacity [W] CCT condenser cooling tower COP coefficient of performance D h hydraulic diameter [m] f friction factor enthalpy [J/kg] HVAC heating ventilation and air conditioning k flow admittance [m 4 ] L length [m] ̇ mass flow rate [kg/s] MIN minimum N dataset length P pressure [Pa] PCT pre-cooling tower ̇ cooling [W] R correlation coefficient RH relative humidity RMSRE root mean square of relative error 4 SCADA supervisory control and data acquisition system temperature [ºC] V velocity [m/s] ̇ p...

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