Evaluation Study of Distributed Energy System Integrating PV Power, Ground Source Heat Pump, and CCHP


Student thesis: Doctoral Thesis

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Awarding Institution
  • Shengming Liao (External person) (External Supervisor)
  • Wei WU (Supervisor)
Award date11 Oct 2021


The distributed energy system (DES) integrating with renewable energy can efficiently realize energy supply, reducing pollutant emissions. Therefore, the research on DES is significant. The DESs integrating photovoltaic, ground source heat pump (GSHP), and natural gas-based CCHP (combined cooling, heating, and power) are established. Renewable energy in the DESs is prioritized, resulting in a higher share of the primary energy consumption and emission reduction. The multi-objective optimization design and the multi-criteria comprehensive evaluation for DES are also studied. The main work is as follows.

The DES dominated by photovoltaic and CCHP is established and simulated by a transient simulation platform (TRNSYS). The exergy flow is analyzed to illustrate the local and global energy utilization. The energy, environmental, and economic performances under different clean electricity supplies are compared with the conventional system that consists of electric chillers, gas boilers, and the utility grid. The sensitivity of energy price and the monthly performance is also studied. Results show that the exergy efficiency is 23.91%. The gas turbine and PV array have large exergy loss. As the relative PV electricity supply ratio, the primary energy saving and total cost saving ratios increase by 7.95% and 3.50%, respectively. In contrast, as the relative PV electricity supply ratio increases, the two ratios decrease by 23.35% and 35.18%, respectively. The comprehensive emission reduction ratio increases with increasing relative PV electricity supply ratio. The total cost saving ratio decreases with increasing natural gas price while it increases with increasing grid electricity price. Overall, the clean electricity supply and energy price greatly affect the DES performances. The monthly performance has a positive correlation with the monthly heat-to-electricity ratio.

The DES dominated by GSHP and CCHP is established and analyzed from thermodynamic, energy, environmental, and economic aspects. The exergy flow is depicted to illustrate the local and global energy utilization. The effects of the GSHP chilled water supply temperature and relative PV electricity supply ratio are scrutinized. The results show that the system exergy efficiency is 27.82%. The exergy loss of the gas boiler is very large, indicating using gas boilers to produce domestic hot water is not efficient from the exergy perspective. The primary energy saving ratio decreases with increasing relative PV electricity supply ratio. The CO2, SO2, and comprehensive reduction ratios increase with increasing relative PV electricity supply ratio. However, the three ratios increase and then level off with increasing GSHP chilled water supply temperature. It is because the electricity consumption of GSHP decreases for some time, and the natural gas consumption of CCHP increases continuously. The total cost saving ratio increases with increasing relative PV electricity supply ratio. Overall, An increased relative PV electricity supply ratio can improve the primary energy saving ratio, pollutant emission reduction ratio, and total cost saving ratio of DES. The GSHP chilled water supply temperature affects the DES environmental performance greatly.

The multi-objective optimization for the DES design is conducted. Seven operation strategies are considered, including the following electric load, following thermal load, following hybrid load with no surplus energy, following hybrid load with maximal surplus energy, following hybrid load with no thermal startup threshold, following monthly electric-thermal load ratio, and following seasonal electric-thermal load ratio operation strategies. The optimization selects the rated capacity of the prime mover and the electric cooling ratio as the decision variables, the maximal comprehensive performance as the optimization objective, and is performed using a genetic algorithm. The comprehensive performance is the weighted average of primary energy consumption saving ratio, total cost saving ratio, operation and maintenance cost saving ratio, increased exergy efficiency, and CO2 and PM2.5 emission reduction ratios. The results show that when the DES is applied to office buildings, hotels, and shopping malls, the prime mover’s rated capacity is 623–1 682 kW, and the electric cooling ratio is 0.5–0.9. The optimized DESs are beneficial for energy saving and emission reduction but not cost saving. The optimal comprehensive performance decreases as the coal-to-gas consumption ratio increases.

The establishment of criteria systems and the determination of criteria weight are refined to build the multi-criteria comprehensive evaluation framework for DES. Specifically, an evaluation criteria system consisting of 21 sub-criteria is established. These sub-criteria are from technological, economic, environmental, and socio-political aspects. The subjective, objective, and comprehensive weights of the framework’s sub-criteria are respectively determined by the triangular fuzzy number-analytic hierarchy process, Shannon entropy, and the combination of single-objective optimization and Jaynes’ maximal entropy principle. The scheme ranking is determined by the improved grey relational analysis method. A cultural industry park is selected for a case study. Results show that the optimal systems are the WSHP+CCHP system under the integrated evaluation and evaluations prioritizing technology and economy. Their grey relational degrees are respectively 0.5764, 0.7475, and 0.7239. However, in the evaluation that prioritizes environment, the optimal system is the CCHP system, with a grey relational degree of 0.8143. The results facilitate the decision-making on the district-level DES.

    Research areas

  • Distributed energy system; Photovoltaic, Ground source heat pump, Natural gas-based cooling, heating, and power, Multi-objective optimization, Comprehensive evaluation