In this work the impact of a high penetration of air to water heat pumps and PV plants on the distribution grid in residential areas is investigated. Results show that increasing PV penetration increases the hours of critical states in the distribution grid. Air to water heat pumps reduce those effects slightly when they are added to the grid. With an increasing penetration of heat pumps new problems, such as load peaks in the mornings, arise. By integrating voltage dependent droop control into the heat pumps, the negative effects on the distribution grid can be reduced. This reduction comes with a loss of HP efficiency and shows strong seasonal variability. For this study a set of representative grid layouts is used. Electric and thermal load profiles for each house are generated using the synPRO stochastic bottom-up model. The thermal load is covered by variable speed electric heat pumps combined with thermal storage. Resulting electric loads are used as input for a probabilistic load flow model
The increasing prevalence of distributed photovoltaic (PV) units raises stress on distribution grids and necessitates increased grid planning efforts. We present a decision support system (DSS) based on integer programming that is able to determine cost-optimal grid reinforcements at the level of individual grid segments. The functionality of the DSS is demonstrated in a scenario analysis of a rising adoption of PV units relying on 1,000 simulation runs in a real-world grid. Based on the results, we provide guidelines for operative grid planning and illustrate how the system assists in the evaluation of reinforcement technologies as well as in long-term investment planning. Furthermore, thanks to segment-specific optimization, the DSS shows that at constant adoption levels, reinforcement cost can vary largely depending on the location of the PV units in the grid. Therefore, a high amount of uncertainty seems unavoidable in long-term prognoses on the effects of solar power on distribution grids
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