Emissions of electric vehicle charging in future scenarios: The effects of time of charging

Electrification of transport is an important option to reduce greenhouse gas emissions. Although many studies have analyzed emission implications of electric vehicle charging, time-specific emission effects of charging are inadequately understood. Here, we combine climate protection scenarios for Europe for the year 2050, detailed power system simulation at hourly time steps, and life cycle assessment of electricity in order to explore the influence of time on the greenhouse gas emissions associated with electric vehicle charging for representative days. We consider both average and short-term marginal emissions. We find that the mix of electricity generation technologies, and thus, also the emissions of charging, vary appreciably across the 24-h day. In our estimates for Europe for 2050, an assumed day-charging regime yields one-third-to-one-half lower average emissions than an assumed night-charging regime. This is owing to high fractions of solar PV in the electricity mix during daytime and more reliance on natural gas electricity in the late evening and night. The effect is stronger during summer months than during winter months, with day charging causing one-half-to-two-thirds lower emissions than night charging during summer. Also, when short-term marginal electricity is assumed, emissions tend to be lower with day charging because of contributions from nuclear electricity during the day. However, the results for short-term marginal electricity have high uncertainty. Overall, our results suggest a need for electric vehicle charging policies and emission assessments to take into consideration variations in electricity mixes and time profiles of vehicle charging over the 24-h day

Aggregation methods for modelling hydropower and its implications for a highly decarbonised energy system in Europe

Given the pursuit of long-term decarbonisation targets, future power systems face the task of integrating the renewable power and providing flexible backup production capacity. Due to its general ability to be dispatched, hydropower offers unique features and a backup production option not to be neglected, especially when taking the flexibility potential of multireservoir systems into account. Adequate hydropower representations are a necessity when analysing future power markets and aggregation methods are crucial for overcoming computational challenges. However, a major issue is that the aggregation must not be a too flexible representation. In a first step, a novel equivalent hydro system model implementation including a possibility to integrate pumping capacity and appropriate handling of multiple water paths (hydraulic coupling) by making use of an ex-ante optimisation is proposed. In a second step, a clustered equivalent hydro systemmodel implementation employing k-means clustering is presented. A comparison of both aggregation approaches against the detailed reference system shows that both aggregated model variants yield significant reductions in computation time while keeping an adequate level of accuracy for a highly decarbonised power system scenario in Europe. The aggregation methods can easily be applied in different model types and may also be helpful in the stochastic case

Introducing system flexibility to a multinational transmission expansion planning model

Grid investments are considered as sunk costs with a very long lifetime, particularly in an offshore grid context. The market mechanisms for cost recovery of these investments are exposed to an increasing share of variable power generation at the supply side, demanding more flexibility in the system. Hence, it is of great interest to account for these changes in tools being used for decision support. This paper presents an extension of an already existing mixed integer linear program (MILP) for transmission expansion planning (TEP), by including system flexibility in the form of energy storage and demand-side management. Moreover, an enhanced description of variable power generation is used to construct production profiles with a higher level of detail. The latter is achieved by simulating weather data for wind and solar incorporating higher temporal and spatial resolution than in previous studies. The impact of using new times series for variable power generation, and the introduction of system flexibility, are both presented separately using the North Sea area for a comparative case study with 2030 scenarios provided by ENTSO-E. The consequent results of interest include lifetime operational costs (OPEX), investment costs (CAPEX), and offshore wind power curtailment

Long-term electricity load forecasting:Current and future trends

Long-term power-system planning and operation, build on expectations concerning future electricity demand and future transmission/generation capacities. This paper reviews current methodologies for forecasting long-term hourly electricity demand on an aggregate scale (regional or nationally), for 10–50 years ahead. We discuss the challenges of these methodologies in a future energy system featuring more renewable energy sources and tighter coupling between the power sector and the building and transport sectors. Finally, we conclude with some recommendations on aspects to be taken into account regarding long-term load forecasts in a changing power system