WHAT IS DISTRICT HEATING CONSUMER THERMAL ENERGY CONSUMPTION FORECASTING?  

Thermal energy forecasting is a process where depending on the weather conditions and information about the consumers, operators forecast thermal energy consumption.

WHY IS IT IMPORTANT TO FORECAST THERMAL ENERGY? 

Precise hourly forecasts allow to manage the district heating network in the most efficient way:

  • Automatic submission of thermal power generation tasks to boiler. Tasks comprise temperature control and fluid mass flow also pressure and variable frequency drives control variables.
  • Human factor is eliminated from the generation and supply planning phase.
  • Reduction of heat losses in the pipelines.
HOW TO FORECAST THERMAL ENERGY?

It is necessary to know district heating network operation parameters in order to properly forecast the temperatures of fluid and mass flow from the boiler. The main purpose of a boiler house is to ensure the correct fluid temperature supply to the consumer to meet their energy consumption requirements.

Small example of DH system is shown in  EA-PSM Hydraulic software. Here we can see all consumers and pipelines which connect every consumer to the boiler house.

In order to start the forecasting calculation process first it is necessary to know the individual consumer historical information on the thermal energy consumption. Information is taken from the smart meters every hour of each consumer. The data is stored in database for future calculations. When historical consumer information is known then the ambient conditions (ambient temperature, wind direction and speed, pressure and humidity) are taken from the weather forecasts suppliers, to calculate the future consumption. In the chart below these parameters are depicted.

Additional technical information is taken from the boiler house operators. These parameters are imputed hourly in order to maintain accurate estimations. In the charts below data from the boiler house operator is shown, such as mass flow rate, boiler return and feed fluid temperature, fluid pressure and thermal power.

With all this information it is possible to forecast what fluid temperature the boiler house should output to meet the demand of the users depending on the weather conditions in the next few days. The chart below shows the forecast results for thermal power and output temperature. Execution tasks are then created for the boiler house. These tasks indicate operators what feeding temperature, mass flow they need to output as well as pressure and variable frequency drives parameters they need to keep. By following these tasks boiler house operators minimize thermal energy losses and meet the consumers demand more accurately. These tasks can be created for multiple individual boiler houses to achieve best network operating conditions.

This information is crucial for operators to accurately estimate what fluid temperature and fluid mass they should output to meet the consumer demands and also to increase the efficiency of the boiler house by accurately calculating what amount of fuel they need to burn to minimize the cost.

CONCLUSION

With the real time thermal energy supply forecasting:

  • Thermal losses in the pipelines can be reduced.
  • Thermal energy for consumers can be forecasted hourly in advance, operator would get thermal energy generation task for the boiler house hourly.
  • Optimal thermal energy task distribution between boiler houses. Tasks are submitted to the operators.
  • Automatic calculation of the best thermal regime, for example: output fluid temperature, mass flow, pressure, frequency converter.
  • Solution Payback period is approximately 2-3 months.

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