Managing the Mismatch: The Role of Flexibility on the Path to a Carbon-Neutral Energy System

Abstract

A rapid expansion of system flexibility is essential to integrate increasing shares of renewable energy into future energy systems. However, flexibility needs and technology-specific contributions to flexibility remain poorly quantified in energy system modelling. Existing methods are not widely applied, leaving key questions unanswered: which flexibility technologies are critical for climate neutrality, and what are the cost implications of alternative deployment strategies? To address this gap, we apply a correlation-based flexibility metric to a high-resolution, sector-coupled model of the German energy system, covering its transformation towards climate neutrality. For our default scenario, we find that daily flexibility needs increase by a factor of 3.7 between 2025 and 2045, driven primarily by the expansion of solar PV. By 2045, stationary batteries provide 38% of daily flexibility, while flexible electric vehicle charging contributes 30%. Systems with constrained flexibility increase system costs by 6.9%, electricity prices by 14 EUR/MWh and trigger 47% higher hydrogen and e-fuel imports compared to an unconstrained system in 2045. In contrast, scenarios with high shares of flexible electric vehicle charging, vehicle-to-grid, and industrial demand-side management achieve system cost reductions of 3.3%, while also reducing import dependence. Higher flexibility also reduces electricity price ranges, decreases average electricity prices by 3 EUR/MWh, and reduces backup capacity by 22% (22 GW). Overall, our results highlight the decisive role of specific flexibility technologies in achieving cost-efficient and energy-secure climate-neutral energy systems, providing quantitative guidance for policy and investment decisions.

Figures (18)

• Figure 1: Illustration of daily flexibility needs derived from residual load profiles. The residual load fluctuates around its daily mean, with deviations above and below defining the upward and downward balancing requirements for each day. Daily flexibility needs are computed as half the sum of absolute deviations from the daily mean, integrated over time.
• Figure 2: Illustration of the flexibility contribution methodology for different technology types. The left column shows the hourly power profile of each technology alongside its daily mean. The right column shows how each timestep contributes positively or negatively to covering flexibility needs, determined by the product of the technology's FlexSign (deviation from its own mean) and the residual load FlexSign (deviation of RL from its daily mean). Panel (A) defines daily flexibility needs as the total area of deviations from the mean RL. Panels (B)–(D) illustrate a dispatchable generator, a dispatchable consumer, and a partially inflexible consumer, respectively, with the latter producing both positive and negative contributions depending on the alignment of its dispatch pattern with flexibility needs.
• Figure 3: Capacity comparison for different scenarios The Figure shows the capacity of key technologies (Renewables, Backup, Storage, Demand-Side) for different scenarios on the development of the energy system from 2025 until 2045. LF = LowFlex, LB = LowBattery, BA = Base, HF = HighFlex.
• Figure 4: Flexibility causes and provision across different scenarios. The figure shows flexibility needs (A) and provision (B) for different scenarios across various timescales.
• Figure 5: Energy balance for the Base scenario in 2045 showing representative periods with high and low flexibility needs at daily (left) and weekly (right) granularity.