Renovation and optimization of existing district heating networks : towards smart low carbon thermal grids

District heating and cooling (DHC) systems are attracting increased interest for their low carbon potential. However, most DHC systems are not operating at the expected performance level. Optimization and Enhancement of DHC networks to reduce (a) fossil fuel consumption, CO2 emission, and heat losses across the network, while (b) increasing return on investment, form key challenges faced by decision makers in the fast developing energy landscape. This thesis hypothesises that optimization of existing district heating networks can contribute to the development of smart thermal grids by integrating sustainable energy and intelligent management technology. This requires an accurate simulation capability at the district level factoring in building fabric and optimization of the system through energy generation, energy distribution, heat substation and terminal users. First, the thesis presents a novel concept to determine building envelope thermal transmittance (known as U-values) and air infiltration rate by a combination of energy modelling (DesignBuilder and EnergyPlus), regression models and genetic algorithm at quasi-steady state conditions. The calibrated U-values and air infiltration rate are employed as inputs in EnergyPlus to model one workday heat consumption. When compared with thermal demand from measured data, the accuracy of the calibrated model has improved significantly. Next, dynamic simulation of distribution network is demonstrated. A numerical simulation model is developed in Simulink to analyse dynamic heat losses in the pipe network at different periods of the week. Results show that heat losses vary between 1-2% during the weekday daytime, while the heat losses increase to 8-12% at other time periods. Supply and return temperatures of each building are presented and simulation results are in line with measured data. Meanwhile, Heat losses of the next generation DH are investigated based on the constructed model. Results show that lower distribution temperature and advanced insulation III technology greatly reduce network heat losses. Also, the network heat loss can be further minimized by a reduction of heat demand in buildings. Finally, a holistic district heating simulation capability is proposed. The simulation capability is carried out under the BCVTB (Building Controls Virtual Test Bed) environment. And the results display the operational schedule under the current operation scheme. Economic and environmental evaluation of the current operation scheme shows that biomass boiler is the cheapest option for heat generation due to renewable heat incentive. This district simulation capability is used to perform day-ahead optimization to determine the optimal schedules, targeting operation cost minimization. MILP is employed for optimization as it can be used to represent non-linear boiler efficiency without sacrificing the advantages brought by linear programming. Efficiency with respect to heat output level is introduced. The results indicate that smart control can be used for peak shaving, installation capacity reduction and operation cost saving. Future work involves investigating the optimization in a broader perspective sense toward smart thermal grid realization.