An advanced reliability reserve incentivizes flexibility investments while safeguarding the electricity market

📅 2025-06-17
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🤖 AI Summary
Under high renewable energy penetration, effectively incentivizing demand-side flexibility investment via capacity mechanisms to ensure supply security remains a critical challenge in power market reform. This paper develops an open-source capacity expansion model integrating multi-dimensional demand-side flexibility resources—including industrial loads, process heat, and district heating—and comparatively evaluates the incentive effects of Germany’s conventional capacity market versus a newly proposed Advanced Reliability Reserve (ARR) mechanism for its 2030 power system. The ARR achieves equivalent supply security and total system cost while significantly increasing demand-side flexibility investment, primarily through a moderate uplift in activation prices. Compared to the traditional capacity market, the ARR enables faster deployment and greater policy adaptability. It thus offers a novel capacity mechanism design that jointly enhances economic efficiency, supply security, and implementation feasibility for transitioning power systems.

Technology Category

Game Theory and Economic Paradigms: Mechanism DesignMultiagent Systems: Mechanism DesignPlanning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystemsSystems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environmentsSecurity and Privacy: Large-scale security measurements
📝 Abstract
To ensure security of supply in the power sector, many countries are already using or discussing the introduction of capacity mechanisms. Two main types of such mechanisms include capacity markets and capacity reserves. Simultaneously, the expansion of variable renewable energy sources increases the need for power sector flexibility, for which there are promising yet often under-utilized options on the demand side. In this paper, we analyze how a centralized capacity market and an advanced reliability reserve with a moderately high activation price affect investments in demand-side flexibility technologies. We do so for a German case study of 2030, using an open-source capacity expansion model and incorporating detailed demand-side flexibility potentials across industry, process heat, and district heating. We show that a centralized capacity market effectively caps peak prices in the wholesale electricity market and thus reduces incentives for investments in demand-side flexibility options. The advanced reliability reserve induces substantially higher flexibility investments while leading to similar overall electricity supply costs and ensuring a similar level of security of supply. The advanced reliability reserve could thus create a learning environment for flexibility technologies to support the transition to climate neutral energy systems. Additionally, an advanced reliability reserve could be introduced faster and is more flexible than a centralized capacity market. While concrete design parameters are yet to be specified, we argue that policymakers should consider the reliability reserve concept in upcoming decision on capacity mechanisms in Germany and beyond.
Problem

Research questions and friction points this paper is trying to address.

How capacity mechanisms impact demand-side flexibility investments
Comparing capacity markets vs reliability reserves in electricity systems
Evaluating flexibility options for renewable energy integration in Germany
Innovation

Methods, ideas, or system contributions that make the work stand out.

Advanced reliability reserve boosts flexibility investments
Centralized capacity market caps peak prices
Demand-side flexibility potentials in industry analyzed
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DIW Berlin
F
Franziska Klaucke
DIW Berlin, Climate Policy Department, Mohrenstraße 58, 10117 Berlin, Germany
Karsten Neuhoff
Karsten Neuhoff
German Institute for Economic Research AND Technical University of Berlin
Alexander Roth
Alexander Roth
Software Engineering RWTH
Software EngineeringModel-Driven DevelopmentCloudGenerative ProgrammingCode Generation
W
W. Schill
DIW Berlin, Energy, Transportation, Environment Department, Mohrenstraße 58, 10117 Berlin, Germany
L
Leon Stolle
DIW Berlin, Climate Policy Department, Mohrenstraße 58, 10117 Berlin, Germany