FlexSource - OIES EL36 Electricity Market Design for Decentralized Flexibility (2019)

Source - OIES EL36 Electricity Market Design for Decentralized Flexibility (2019)


The electricity market design for decentralized flexibility sources. OIES Paper EL36, Oxford Institute for Energy Studies, July 2019. DOI: 10.26889/9781784671433. Author: Spyros Evangelakakis (affiliation not given in text). 28 pages.

Bibliographic details

  • Full title: The electricity market design for decentralized flexibility sources
  • Publisher: Oxford Institute for Energy Studies (OIES)
  • Series: OIES Paper EL36
  • Date: July 2019
  • DOI: 10.26889/9781784671433
  • Length: 28 pages
  • Related OIES paper: EL 17 (Keay 2016, “Electricity markets are broken – can they be fixed?”)

Summary

This paper analyses how small, distributed, heterogeneous flexibility assets — collectively called decentralized flexibility sources (DFS) — can participate in electricity markets designed for large, homogeneous, dispatchable generators. The central argument is that existing market structures systematically exclude DFS through barriers that are unnecessary for system security but serve incumbent interests, and that these barriers must be removed for VRE integration to be cost-effective.

The paper covers VRE integration cost categories, DFS characteristics and typology, implicit versus explicit demand-side management, the economics of aggregation, specific market access barriers, and recommendations for market design reforms. The analytical framework is EU-generic but draws on examples from across Europe.

Decentralized flexibility sources (DFS)

The paper defines DFS as flexibility assets located at the distribution level, typically small, and available in large numbers. Characteristics that distinguish them from conventional generators:

FeatureDFSConventional generator
DirectionUni- or bi-directionalUni-directional (output only)
Energy typePower and/or energyTypically energy
Response time (tr)4 seconds to 10 hours depending on asset typeMinutes to hours
AvailabilityIntermittent (dependent on user behavior, SOC, weather)Schedulable within capacity limits

DFS typology (Table 3 in paper):

  • Residential loads (lighting, appliances): slow response (hours), low individual capacity
  • Continuous heating/cooling (heat pumps, HVAC): medium response, high aggregate potential
  • Batteries: very fast (4 s < tr < 10 h); bi-directional; predictable but SOC-constrained
  • EVs: medium-fast (30 min < tr < 6 h); bi-directional in V2G mode; highly intermittent availability
  • Public lighting: fast, reliable but unidirectional; small individual capacity

This typology directly maps onto what Swedish policy calls “flexibilitetsresurser” — the paper’s DFS concept corresponds closely to the resources targeted by the Network Code on Demand Response and Flexibility Market instruments in Sweden.

VRE integration cost categories

The paper provides a systematic breakdown of costs that variable renewable energy imposes on the power system (Table 1):

Cost categoryMechanismWho bears it
Profile costs — overproductionVRE curtailment when supply > demandVRE producers
Profile costs — full-load-hour reductionConventional plants displaced during VRE output hoursConventional generators
Profile costs — adequacyResidual firm capacity still needed for low-VRE periodsSystem/consumers
Balancing costsForecast error → reserve activationTSO / all consumers via balancing charge
Grid-related costsDFS/VRE located far from load or with weak distribution connectionDSO / network users

This cost decomposition is theoretically important: DFS can reduce all three profile cost components and balancing costs by shaping residual demand to match VRE output. The grid-related costs, however, may be increased if DFS are poorly located relative to congested network sections.

Explicit vs implicit demand-side management

The paper draws a sharp distinction between implicit and explicit DSM, analogous to the Demand Response page’s implicit/explicit framework:

Implicit DSM (price-responsive): consumers react to price signals (spot prices, time-of-use tariffs). No contractual commitment; no market participation. Pros: no transaction costs, no aggregation needed. Cons: unpredictable aggregate effect; can create synchronisation peaks; no service guarantee.

Explicit DSM (market-based): consumers or aggregators make commitments in organized markets. Pros: predictable, guaranteeable, dispatchable. Cons: requires registration, baseline measurement, settlement infrastructure.

The paper argues that explicit DSM via aggregators is the correct long-run design: implicit DSM cannot scale without creating systemic balancing risks (the same finding as Source - FlexAbility Delrapport 5 (2025) on implicit flex at scale in Sweden). Aggregation is necessary because individual DFS are too small to meet market minimum bid sizes — typically 1–10 MW in wholesale/balancing markets vs. individual DFS capacities of 1–100 kW.

Aggregation economics and the BRP-aggregator problem

The paper analyses the economics and institutional barriers to aggregation. The fundamental challenge is the BRP-aggregator settlement conflict:

  • When an aggregator activates a DFS resource, it changes the resource’s actual consumption relative to the BRP’s day-ahead schedule.
  • This creates an imbalance in the BRP’s position.
  • Under current EU rules (prior to full NC DR implementation), the BRP bears the financial cost of this imbalance.
  • Result: BRPs are financially harmed by aggregator activations and have strong incentives to block independent aggregation.

This is the structural barrier that Network Code on Demand Response Art. 24–28 (the Elmarknadshubb/FIS framework) and the Art. 18 EB GL national terms obligations are designed to resolve. In Sweden, the BSP role delay to 2028 (see Balancing Markets) means this barrier remains operative for much of the NC DR transition period.

The paper identifies three specific aggregation cost drivers:

  1. Transaction costs: each DFS requires individual contracts, metering agreements, and prequalification
  2. Baseline uncertainty: estimating what a DFS “would have consumed” without intervention is inherently uncertain; baseline errors destroy settlement accuracy
  3. Cross-market optimization: a battery managing its own FCR portfolio cannot simultaneously be aggregated by an independent aggregator for DSO flexibility services without a shared optimization layer

The recommendation: aggregation must be recognized as a licensed, regulated function with clear rules for compensation between aggregators and affected BRPs.

Market access barriers (Table 4)

The paper catalogues barriers that prevent DFS from competing in electricity markets:

BarrierDescriptionEffect
Symmetric bid requirementMany markets require both upward and downward bidsExcludes unidirectional DFS (e.g., heating-only loads that can only reduce)
Minimum bid sizeTypical minimum 1–10 MW in balancing marketsRequires aggregation of hundreds to thousands of individual DFS
Time factorsGate closure, notification lead time, response time requirementsMany DFS have slow ramp-up; residential loads have human reaction time
Baseline requirementsComplex measurement and verification requirementsHigh administrative cost per DFS; not designed for probabilistic resources
Symmetric penalty structureEqual penalty for over- and under-deliveryDFS with availability uncertainty (EVs, batteries) face disproportionate risk

In Sweden, the 0.1 MW minimum bid size in SWITCH and LFM products directly addresses the minimum bid size barrier. The Network Code on Demand Response standardizes prequalification pathways (three-status system) that reduce time-factor barriers.

FCR as the preferred entry point for DFS

A key recommendation: FCR (Frequency Containment Reserve) is the best first balancing market product for DFS, for three reasons:

  1. Low energy imbalance: FCR activations are symmetric and short; the aggregate energy imbalance created is small, reducing the financial exposure for the aggregator/BRP
  2. Fast response well-suited to batteries: FCR-N requires response within 30 seconds; batteries excel at this
  3. Symmetric bidding: FCR is inherently symmetric (both up and down response), so the symmetric bid requirement does not exclude FCR-participating DFS

This recommendation aligns with Swedish practice: the first major DFS aggregator market in Sweden is FCR (via batteries), and the Source - ENTSO-E FCR Technical Requirements Nordic (2023) confirm that prequalification starts at ≤100 kW in the Nordic system — the lowest threshold in any balancing product.

Nodal pricing at distribution level

The paper raises the possibility of nodal/locational marginal pricing at the distribution level as a longer-run market design option. Under nodal pricing, prices would differ at each network node based on local congestion and generation mix, providing implicit DR incentives that are location-specific and proportional to actual grid stress.

The paper acknowledges this is technically complex and politically difficult, but argues it is the theoretically correct long-run design if smart metering and DMS infrastructure supports it. The interim solution — local flexibility markets at congested nodes — is acknowledged as a second-best that avoids the full complexity while providing some locational differentiation.

Sweden’s approach (DNDP-based congestion identification → LFM procurement at congested zones) is consistent with the paper’s recommended interim path.

Relationship to NC DR and Swedish context

This 2019 paper is analytically consistent with the direction EU policy has since taken. The NC DR framework enacted in 2024–2026 addresses precisely the barriers this paper identifies:

Paper recommendationNC DR response
Resolve BRP-aggregator settlement conflictArt. 24–28 FIS and compensation rules
Standardize DFS prequalificationThree-status prequalification system (Art. 49)
Reduce minimum bid sizes0.1 MW target; market-level derogation possible
Enable asymmetric (unidirectional) biddingAllowed under NC DR service providing group structure
Mandatory flexibility registersArt. 24–26 FIS requirement

The paper’s framing of DFS as a distinct product category requiring its own market infrastructure — rather than a scaled-down version of conventional generation participation — is now the conceptual foundation of EU flexibility policy.

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