Renewable geothermal utilization is a significant approach for residential heating with two principal modes, direct geothermal district heating systems (DGDHSs) and indirect geothermal district heating systems (IGDHSs). The key principle of geothermal development design is to prevent premature thermal breakthrough, which could result in low efficiency of geothermal heating systems. In this paper, a new approach considering building heating demand, geothermal water resource protection, and optimal economic benefits is presented systematically. The results simulated by OGS software show that well spacing, reinjection temperature, and production rate are the most significant parameters affecting thermal breakthrough in geothermal reservoirs. In addition, production rate and reinjection temperature have a huge effect on the payback period of investment. Comparing IGDHS to DGDHS, the investment in construction of geothermal wells and the annual water consumption decrease by up to 10% and 50%, respectively. Additionally, electricity costs increase by 5% to 30%. The indirect geothermal district heating system with a well spacing of 300 m, a production rate of 100 m3/h, and a reinjection temperature of 301.15 K is much better for this case, both technically and economically. The systematic calculation approach can be reasonably applied to other regions with geothermal energy utilization.

Occupant presence and behavior are non-negligible factors affecting building energy consumption. It should be emphasized: guaranteed building core functions is a prerequisite for energy saving. This paper proposes a method that can minimize building energy consumption and improve occupant comfort. Through monitoring the entry and exit of a 24-person office, occupant presence is obtained. And the difference in comfort of occupants is investigated and analyzed. The occupant is moved to a seat that is more thermally comfortable. Then occupants with a high degree of overlap in-room time are gathered in the same lighting area to reduce lighting energy consumption. Through the multi-objective optimization model, the lighting energy consumption is reduced by 16.2%, and the overall indoor comfort is slightly improved.