Optimal Duration of Reserve Capacity Ancillary Services for Distributed Energy Resources

TL;DR

The paper addresses how to design the duration of reserve-capacity ancillary services for distributed energy resources to balance availability and system needs. It introduces a three-step method: derive representative imbalance profiles from historical data, model a technology-diverse VPP's reserve supply as a function of product duration $t^{\text{p}}$, and select $t^{\text{p}}$ by jointly maximizing average availability and minimizing misalignment with system imbalances $P^{\text{act}}$. A Swiss low-voltage network case with solar, heat pumps, batteries, and EVs demonstrates that shorter durations ($t^{\text{p}}$ < 3 h) maximize availability, while longer durations ($t^{\text{p}}$ = 12–24 h) better align with balancing needs, with $t^{\text{p}}=1$ h identified as a practical compromise. The study provides a practical framework for TSOs and DER aggregators to tailor reserve products to DER portfolios and evolving balancing requirements.

Abstract

The increasing integration of distributed energy resources (DERs) into power systems presents opportunities and challenges for ancillary services (AS) provision. Technical requirements of existing AS (i.e., duration, reliability, ramp rate, and lead time) have been designed for traditional generating units, making their provision by DER aggregates particularly challenging. This paper proposes a method to design the duration of reserve capacity AS products considering the operational constraints of DERs and the temporal dynamics of system imbalances. The optimal product duration is determined by maximizing product availability and aligning the supply profile with the system's balancing needs. We apply the methodology to a realistic Swiss low-voltage network with a diverse DER portfolio. The results reveal that (i) shorter product durations maximize average availability and (ii) long product durations improve the alignment with system balancing needs. This paper offers valuable insights for system operators to design AS products tailored for DER participation.

Figures (3)

• Figure 1: Reserve capacity supply profiles for different product durations. Positive values denote upward reserve and negative values downward reserve.
• Figure 2: Value of the two objectives for each considered $t^{\text{p}} \in \Omega$, highlighted through the numbers in the data points. The left panel shows the upward reserve and the right panel shows the downward reserve. Better designs are located in the upper-right part of each graph.
• Figure 3: Balancing needs and reserve capacity supply profiles for 1-hour product duration. Positive values denote upward reserve and negative values downward reserve.