Utilising Distributed Flexibilities in the European Transmission Grid

Abstract

In this paper, we investigate the effect of distributed flexibilities on the operation of the transmission grid. The flexibilities considered are heat pumps, electric vehicles, battery energy storage systems and flexible renewable generation. For this purpose, we develop a two-stage approach of first determining an optimal electricity market solution considering the optimal dispatch of each generation element and flexibility. In the second step we determine the required dispatch adjustments due to transmission grid constraints and investigate the effect of integrating battery energy storage systems into the adjustable generators to solve congestions. In our case study, we investigate the central European transmission grid for a scenario based on the Distributed Generation scenario of the Ten-Year Network Development Plan for the year 2030. Integrating distributed flexibilities leads to a strong increase in the security of supply, while the overall effect on the generation adjustment is small. A comparison of the results for an AC and DC formulation shows that both approaches differ significantly in individual cases.

Impacts of electric vehicles on the European high and extra high voltage power grid

“…Our approach based on previous work on the European electricity network (Hartel et al, 2019;Ruppert et al, 2020) and the allocation of fast charging stations by Jochem et al (2019) For addressing the first issue of a consistent parametrization of the future power system we integrated the FCS related data based on Jochem et al ( 2019) into a framework for modeling the development of the future power system (Hartel et al, 2019;Ruppert et al, 2020). As illustrated in Figure 1, this framework includes a tool chain for a techno-economic optimization of the power system based on hourly resolved renewables and demand profiles and potentials on the European high voltage distribution grid level.…”

“…Flexibility in the sense of balancing demand and supply over multiple time steps is modeled following Ruppert et al (2020), based on a general storage equation with losses neglected.…”

“…The energy level v s,t of a storage s ∈ S at time step t ∈ T results from its previous level, the external power inflow 𝜁 in s,t or outflow 𝜁 out s,t and the sum of charged and discharged power provided by connected generators p g,t ∈ G S ⊆ G. Besides modeling classical storage applications such as hydro pump storages and batteries, this equation might be used to model the flexibility of generators following a demand or generation profile by modifying the bounds on variables. That way, the load shifting potential of flexible demands, such as home charging PEV and distributed heat pumps (HP), might be modeled as described by Ruppert et al (2020). The basic idea of this approach is to derive the bounds for the shifting from the profile itself, based on the assumption that a certain share of a specific load/generation profile might be shifted within a certain time range to a certain degree.…”

Impact of Flow Based Market Coupling on the European Electricity Markets

“…The grid model is the detailed transmission grid model presented in Ruppert et al (2020), which is extended for the countries to complete the Core region (Croatia, Hungary, Romania, Slovenia, Slovakia) and the high voltage direct current (HVDC) inter-connectors to neighbouring bidding zones. Grid data for these countries are based on ENTSO-E (2021b) and ENTSO-E (2016) including expansion measures from the Ten Year Network Development Plan (TYNDP) 2018 (ENTSO-E ( 2018)) and national expansion plans, where applicable.…”

Comparing empirical and model-based approaches for calculating dynamic grid emission factors: An application to CO2-minimizing storage dispatch in Germany

“…In light of global decarbonization efforts, flexibility becomes increasingly important in energy systems [1]. Energy storage systems (ESS) in industry can contribute to the needed flexibility in two ways: First, they allow for a time variable consumption of electricity in good adaptation to volatile supply of renewable energies [2,3].…”