The Effect of Technical Risks on the Achievement of Goals for Distributed Energy Supply Concepts in Residential Neighbourhoods

Kurzfassung

Distributed energy systems can significantly contribute to reducing the environmental impact of humanity by increasing energy efficiency and reducing energy losses. The Energetic Neighbourhood Fliegerhorst Oldenburg (ENaQ) is a research project where distributed energy system technologies are planned to be implemented. This thesis uses the risk analysis method of Monte Carlo simulations to assess uncertainties in ENaQ for two heat supply cases: combined heat and power (CHP) plant and heat pump (HP). Sensitivity analysis was conducted on the The Renewable Energy Sources Act (EEG) levy, Photovoltaics, offshore and onshore wind capacities, and the CO2 price on buildings to identify the most insignificant uncertainties on the Key Performance Indicators (KPIs) of ENaQ. The results showed that the CO2 price on buildings was on average the least significant parameter amongst those investigated. Following the selection of input parameters via sensitivity analysis, the scenarios for the Monte Carlo simulations were determined using probability distribution functions of parameters and Latin hypercube sampling. After performing Monte Carlo simulations with 1000 scenarios in each case, statistical analyses of the KPIs’ distributions were carried out. The expected value of CO2 emissions was significantly smaller, and own consumption greater, in the HP case than in the CHP case; however, the expected value of operational costs for the CHP case was smaller than the HP case. The distributions of the CO2 emissions and own consumption were distinctively in favour of HP considering the project’s targets. There was an overlapping of operational costs distributions for CHP and HP. The bimodal distributions of the own consumption and operational cost were further analysed using conditional distributions with and without the EEG levy. Lastly, Spearsman’s rank correlation coefficients were calculated to evaluate the effect of individual uncertainties on the overall risk. The own consumption was most sensitive to the EEG levy’s variation in both of the cases. The renewable energy capacities were the most influential on the CO2 emissions in both of the cases.