Cost-minimizing electricity system models are important tools for understanding conditions for the development of the electricity system. Since the variability of wind and solar power outputs differs between years, a satisfactory representation of variability requires a high time resolution, as well as data that cover multiple decades. This work proposes a weather-year selection method that represents power generation variability by selecting a set of weather years to represent the net-load variability of a broader span of historical weather years (in this work, 39 years). The representativeness is captured in terms of net-load amplitude and duration, such that the electricity demand, as well as the wind- and solar-generation profiles, are considered in their chronologic order, rather than simply as discrete data-points. The weather-year selection method is applied to modeling the North European electricity system with the aims of evaluating the method and investigating the impacts of extreme net-load events on the electricity system composition. The results show that the proposed method can represent the net-load variability of multiple decades using a few selected weather-years. In addition, when the probability of extreme net-load events is accounted for, these extreme events mainly increase the peak thermal capacity and long-term biogas fuel storage capacity.

As electricity systems become increasingly dominated by variable inverter-based generation (such as wind and solar photovoltaics (PV)), additional sources of variability appear, while the share of dispatchable thermal power plants decreases. Maintaining a stable grid frequency requires new sources of inertia to slow the frequency changes, as well as new sources of reserve power to counter the imbalances. This work uses a linear optimization modeling approach to analyze the reserve market of the electricity system during the transition to a carbon-free system with high shares of variable electricity generation. The modeling is performed for three regional contexts and with varying degrees of available flexibility technologies. As for the reserve supply, batteries, electrolyzers, electric boilers and heat pumps for district heating, curtailed wind and solar power, and hydropower and thermal power plants are all included. The results indicate that of these suppliers of reserves, the introduction of grid-scale batteries into the system drastically reduces the reserve market size. Only early in the transition is revenue from the reserve market greater than 5% of the total revenue for any technology. While the demand for reserves increases as the share of solar PV and wind power increases, the modeling reveals that access to flexible loads, storage units, and emulated inertia from wind power also increases. Depending on the choice of flexibility measures available, demand-side participation could play a major role in minimizing the cost of grid stability in the future.

The transition towards an electricity system that is dominated by asynchronous and non-dispatchable generators, such as wind and solar power, entails challenges related to balancing the load and, thereby, keeping the grid frequency stable. Many technologies can contribute to load balancing and frequency control. This study investigates the interactions between electricity generation and frequency control in terms of investments and operation, using cost-minimizing, linear optimization modeling. The model is applied in three different geographic cases and for four future time-points, starting off with the already existing transmission and generation capacities, so as to yield insights into different systems and different stages along the energy transition. The results show that frequency control constraints in the optimization model have a weak impact on the system composition and cost, and that batteries are important for minimizing the impact. Furthermore, inertia requirements without a reserve demand show no impact on the cost or system composition. When allowing for vehicle-to-grid from battery electric vehicles, a large proportion of stationary grid battery investments is displaced, and the impact on system cost from adding frequency control constraints is removed.

In this paper, we define indicators, with a focus on the electricity sector, that translate the results of energy systems modelling to quantitative entities that can facilitate assessments of the transitions required to meet stringent climate targets. Such indicators, which are often overlooked in model scenario presentations, can be applied to make the modelling results more accessible and are useful for managing the transition on the policy level, as well as for internal evaluations of modelling results. We propose a set of 13 indicators related to: 1) the resource and material usages in modelled energy system designs; 2) the rates of transition from current to future energy systems; and 3) the energy security in energy system modelling results. To illustrate its value, the proposed set of indicators is applied to energy system scenarios derived from an electricity system investment model for Northern Europe. We show that the proposed indicators are useful for facilitating discussions, raising new questions, and relating the modelling results to Sustainable Development Goals and thus facilitate better policy processes. The indicators presented here should not be seen as a complete set, but rather as examples. Therefore, this paper represents a starting point and a call to other modellers to expand and refine the list of indicators.

This study investigates how the inclusion of frequency control constraints in electricity system modeling impacts the levels of investment and dispatch in electricity generation and storage technologies for futures that include high-level penetration of variable renewable energy. This is achieved using a linear cost-minimizing investment and dispatch model using historic load, wind and solar conditions from Spain, Ireland, Sweden and Hungary for Year 2050. With an hourly time-resolution, constraints are added so as to ensure that, within each hour, sufficient inertial power and reserves are available to control the frequency of the power grid. Comparing the results obtained with and without these constraints reveals that the main impacts on the results are from battery investments and operation. Furthermore, it is found that the reserve requirements exert a greater impact on system composition and operation than do the inertial power requirements.

This study investigates how thermal energy storage (TES) influences the cost-optimal investment and operation of electricity and district heating (DH) systems in different scenarios. Greenfield energy system modelling for Year 2050 with a high time resolution shows that sensible TES strategies have a strong impact on the composition and operation of the DH system in all investigated scenarios. The introduction of TES displaces to a significant extent the heat-only boilers in all scenarios and can promote solar heating in small DH networks. The modelling shows that TES also promotes the use of power-to-heat processes and enables combined heat and power plants to increase full-load hours, with simultaneous adaptation to the variable production in the electricity system. A major benefit derived from TES is the ability to respond to rapid variations in the electricity system. Thus, the pit and tank storage systems with higher (dis)charging capacities are preferred over borehole storage.

This study investigates how inclusion of frequency control constraints in electricity system modelling impacts the investment and dispatch in electricity generation and storage technologies for high-VRE futures. This is done using a linear cost-minimizing investment and dispatch model using historical load, wind and solar power conditions from Spain, Ireland, Sweden and Hungary for the year 2050. With an hourly time-resolution, constraints are added to ensure that, within each hour, sufficient inertial power and reserves are available to control the frequency. Comparing the results with and without these constraints show that nearly all impact on the results is in battery investments and operation. Furthermore, it is found that reserve requirements have a higher impact on system composition and operation than inertial power requirements.

In the current transition to a carbon neutral society, variable renewable energy sources (VRESs) are becoming ever more important, and so are the strategies and technologies that manage the mismatch in time between the intermittent VRES and the energy demand. This thesis examines the effects of thermal energy storage (TES) as a variation management technology using a greenfield cost-optimising model integrating the district heating (DH) and electricity systems in one model. Wind, solar and hydropower availability is selected according to the Swedish StockholmGothenburg electricity price area, but a low-flex scenario with less hydro, waste and biomass is also investigated. Using projected costs for year 2050 in combination with a zero-limit on CO2 emissions, TES is found to greatly affect the cost-optimal DH system composition and operation while promoting wind power in the electricity system, especially so in the low-flex scenario. This impact is mainly through reducing curtailment but also through increasing the demand for electricity. The CHP and power-to-heat units become increasingly active in the electricity system, using the TES for flexibility and detachment from the heat demand curve. Furthermore, TES is found to be important also when combined with other variation management strategies (demand side management and hydrogen storage), and some synergies are found both in promoting wind power and reducing the total system cost.