IntegrCiTy - D4.2 Report - Method towards key bottlenecks identification

The increasing use of renewable energy is a deep going trend [1] mainly supported by the sustained annual growth rate of solar photovoltaic (+45.5%), wind power (+24.0%) and Biogases (+12.8%) (Figure 1). In this context, decentralized power generation and heat pumps technologies are expected to play an increasing role [2]. This evolution is going to increase the stress on the electricity and gas distribution network while pushing the development of district heating and cooling (DHC) networks. At the grid level, the uncertainty in energy generation from renewable energy, the trend towards decentralisation and the emergence of new energy prosumers are going to increase bi‐directional energy interconnections [3], therefore challenging the energy networks to balance supply and demand. Therefore, there is a need for a method to identify actions and opportunities for the design and retrofit of future resilient urban energy systems. The IntegrCiTy project demonstrates the use of co‐simulation techniques to support the growing penetration of renewables systems through the interconnection of energy conversion technologies with multi‐energy urban networks supplying natural gas, electricity, heating and cooling. This report presents a method using co‐simulation models to identify and characterize the key bottlenecks (such as pipe sizes, heat exchangers or limiting transformers) of urban energy system from a multi‐energy perspective. Bottlenecks are defined and characterized at the level of the electricity, gas and heating/cooling distribution networks in Chapter 2. In Chapter 3, the selection of extreme operating conditions are presented to identify the bottleneck with a minimum set of operating points. Based on the definition of the bottlenecks, a stochastic hosting capacity approach is proposed in Chapter 4 to evaluate the penetration of renewable energy technologies resulting from the capacity limit of the existing infrastructure. Finally, the approach is demonstrated with the identification of the bottlenecks in the photovoltaic (PV) conversion of solar energy on the roofs of a district.