Demand profile simulation
Various calculation and simulation methods can be used to generate demand profiles, which differ in their level of detail.
Consistent demand profiles are one of the most important prerequisites for planning district energy systems. If the demand is over- or underestimated, systems will be oversized or undersized. Oversizing increases investments and costs during the later operation phase. Undersizing, in turn, leads to unmet demands and outages. Relevant energy demands for districts include heating demands (space heating, domestic hot water, and possibly process heating demands), electrical demands (plug loads, e-mobility), and cooling demands (space cooling, server cooling, refrigeration applications for food retail, etc.).
Although demand profiles are of great importance for planning district energy systems, there is a lack of suitable calculation tools and methods for generating profiles. Often, existing profiles are merely scaled. However, specific neighborhood requirements or specified peak loads are insufficiently taken into account. Detailed simulation methods (building performance simulation), on the other hand, allow buildings to be mapped in great detail and their annual demand to be estimated quite accurately. However, uncertainties remain here as well, since user behavior, for example, can only be taken into account statistically, and deviates from actual user behavior. Another problem with detailed simulation methods is that they require a very large number of input parameters to generate demand profiles with sufficient accuracy. For example, information on shading techniques, wall constructions, insulation thicknesses, window types, or occupancy densities is needed to determine the cooling or heating demand of the building. However, this information is only available in the late planning phases. In the early planning phase of districts, simplified methods are therefore often used, which are based on the degree-day method, for example.
Thermal building models are used to determine thermal energy demands (space heating and air conditioning). In the simulation, all heat flows and resistances within the building are then mapped. For this purpose, a number of assumptions have to be made, for example, transmission and ventilation heat losses, solar gains from solar radiation, building shading, internal heat gains by the building occupants and technical systems. In particular, user behavior (attendance times, habits in ventilation behavior) can often only be roughly estimated. In detailed building models, the building is divided into several thermal zones and the heat flows between the individual zones are taken into account. For the derivation of heating and cooling demands of a building over the course of a year, very detailed models are necessary, which include, for example, all external surfaces of the building including geographical orientation as well as wall structures (materials used and layer thicknesses, glazing proportion, as well as existing thermal bridges).
Typically, demand profiles with hourly resolution for a typical reference year are used for district planning. For the simulation of demand profiles, a typical weather year is used (test reference year). For Germany, weather data can be downloaded free of charge from the DWD for many locations; for other locations, Energy-Plus weather years can be downloaded free of charge. The use of profiles with an hourly resolution is particularly important when considering renewable energy, especially photovoltaics. A 15-minute resolution is also common for electrical simulations. When planning districts, the advantage is that often a large number of buildings is considered and peak loads are averaged out. For a single family house, for example, individual peak loads can occur (hair dryer, stove top) that only last a few minutes. If these peak loads are averaged hourly, the resulting average powers are much lower. In the case where photovoltaic power is used, there would be a much higher overlap if considered on an hourly basis than if demands and power generation were considered on a minute-by-minute or even second-by-second resolution. This illustrates that different calculation methods are needed for individual buildings and for district energy systems. With districts, the peak loads average out more and more as the number of buildings increases, resulting in smoothed demand profiles for which an hourly resolution is usually sufficient (standard load profiles). For systems with high thermal inertia, such as district heating networks, peak loads are less relevant - in contrast to electrical grids - because they do not have to be covered directly by the generation units, but the thermal inertia smoothes peak loads.
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