Increasing distributed photovoltaic (PV) systems can lead to overloading of grid assets and voltage violations at grid nodes, especially in distribution systems. This raises the necessity to consider the future growth of installed PV capacity for the mid- and long-term planning process of distribution system operators (DSOs). Considering solar roof potential analysis derived from an airborne light detection and ranging (LIDAR) mission, the evaluation of the hosting capacity of a given distribution grid can be improved. This paper compares different methods to allocate the future PV capacity based on such solar roof potential analysis at the distribution system level. Rule -Based methods are developed and compared with a probabilistic method, which is repeated several times as a Monte Carlo analysis, in order to define the allocation of PV power to grid nodes. The developed deterministic methods can provide DSOs with simple and reliable indication about the hosting capacity of PV and the need for grid reinforcement compared to other methods.

Increasing distributed photovoltaic (PV) systems can lead to voltage violations and overloading of grid assets in distribution grids. This raises the necessity to consider the future growth of installed PV capacity for the planning process of distribution system operators (DSOs). This paper proposes the combination of a solar roof potential analysis and grid integration studies at the medium voltage (MV) level based on detailed input at low voltage level. Three different methods were developed to define the distribution of PV along the feeders based on the solar roof potential, and subsequently to estimate the PV hosting capacity of these feeders. The results show that the approach with an even distribution of PV systems along the feeders leads to higher hosting capacity of PV for the analyzed grids. In addition, for most analyzed feeders in this study, an overloading of MV/LV (low voltage) transformers is expected to be the limitation of hosting capacity for potential PV systems.

Aging is an important factor to be considered by distribution grid operators when using oil-immersed power transformers. The life-time consumption mainly depends on the decomposition of the organic parts in the isolation paper and the oil. With a high number of photovoltaic systems in the distribution grid the worst-case-scenario changes from high power demand during low outdoor temperatures times in the winter to high feed-in power with high outdoor temperatures in the summer. The temperature increases the reaction rate of the chemical processes and affects the life-time consumption exponentially. An alternative to the evaluation of the highest power value per year is introduced by the national standard DIN 60076-7. The standard considers transferred power and transformer environment temperature as time series. By extending the simulation model with a simulative representation of the transformer housing it is possible to consider the influence of the housing in more detailed way. This allows the evaluation of the stress to the transformer by using available data without the need for additional field measurement. The benefit of this extension is demonstrated for six different scenarios of the PV penetration. The results of the first analysis demonstrates that the temperature and power combination in areas with a high amount of PV feed-in power gains additional life-time consumption that are not calculated in the common evaluation methods of distribution system operator.

The OrPHEuS project elaborates hybrid energy network control strategies for smart cities implementing novel cooperative approach for the optimal interactions between multiple energy grids. The OrPHEuS project aims at optimising the synergies between multiple energy grids by enabling simultaneous optimization for individual response requirements, energy efficiencies and energy savings as well as coupled operational, economic and social impacts. The project will investigate the implementation of the control strategies on specific use cases scenario in two demonstration sites located in the City of Skelleftea in Sweden and in the City of Ulm in Germany. The operational focus of the project is the cross-domain coupling of energy infrastructures in order to increase energy efficiency through energy transformation and grid coupling. In particular, the project researches scenarios for transition between energy resources and flexible infrastructures e.g. along Power-to-Heat processes. It investigates the balancing of fluctuating renewable energy generation against the flexibility in supply, demand and storage capacities within the power grid and via process coupling across energy networks. The project will look on technical as well as socio-economical aspects considered as multi-dimensional strategy framework. With respect to the hybrid energy characteristics, both demonstration sites are quite distinct. At the demonstration site in Sweden, the reduction of vertical production (driven unsustainable with fossil fuel) is in the centre of the targeted control strategies. Looking on the specifics of the Ulm testing site, the major issue is the balancing of the high penetration of solar generation under today’s operation with a pre-dominant operational challenge for PV control. The key focus is to define control strategies to increase the intake of the energy supply from PV on the roof generation into the grid while maximizing the benefits for the low voltage power grid. The 29th European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC) in Amsterdam represented a unique opportunity to present information on the methodology adopted by the OrPHEuS Consortium to optimise the synergies between multiple energy grids. On the occasion of the EU PVSEC the OrPHEuS Consortium focused the project presentation on how to optimise the PV electricity production with the implementation of Information and Communication (ICT) devices at the Ulm demonstration site, the Test area in Einsingen, which presents an over production of the PV electricity of 230 MWh annually. The average annual electrical consumption is around 1000 MWh.