Optimering av last och produktion i Gävles fjärrvärmenät : Reducering av effekttoppar via värmelagring i byggnader
Sammanfattning: District heating is today the most common way of providing a building with heat and hot water in Sweden. It is an environmentally friendly product mostly used with renewable fuel. However, at power peaks most companies use production units that are more expensive and worse for the environment and should therefore be avoided as much as possible. This can be done with a method called load management. When a power peak occurs, the heat supply to buildings connected to the district heating system can be temporarily reduced. The heat energy can later be returned when the heat demand is lower. Thanks to the heat inertia of the buildings, the indoor temperature will not fall within the time frame for the load management. Historical data has been analysed to identify when and why power peaks occur in the district heating network. Power peaks throughout the district heating network have proved difficult to identify. However, for individual consumers clear patterns of power peaks have emerged. These power peaks mainly occur because of large use of hot water but also because of the shifting outdoor temperature. In order to see how the production cost would differ from the actual outcome load management was applied for Gävle's district heating 2018. The load management was calculated manually by identifying the most expensive production unit on an hourly basis. If a cheaper production unit had the potential to deliver higher power the next hour, the production was moved to the cheaper production unit. The process was repeated for each hour during 2018. After carrying out load management for Gävle's district heating network, 1 457 MWh had been shifted to a cheaper production unit. This resulted in a financial saving of 1,0 % of the total production cost. The environmental savings showed a reduction from 6.1 to 5.9 g CO2eq /kWh a total of 197 tonne CO2eq. In the exact same way, a load management was performed for a scenario where Gävle and Sandviken's district heating network were connected. The gain for a load management with Sandviken will be considerably larger, a reduced production cost of 3.6 % is possible. The environmental savings showed a reduction from 8.4 to 7.8 CO2eq /kWh a total of 575 tonne CO2eq. For future efficient load management, buildings should be divided into different classes depending on the building's time constant. User patterns for the entire district heating network have proved difficult to detect. Artificial intelligence can be an option for short-term forecasting of the power output
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