Source - Local Flexibility Markets in Europe Critical Review (2025)

Bibliographic reference: Sassone, A. et al., “Local flexibility markets in Europe: A critical review of market designs, operational maturity and stakeholder perspectives,” Renewable and Sustainable Energy Reviews, published 2025-08-08. DOI: 10.1016/j.rser.2025.116434

Source type: Peer-reviewed academic paper (systematic review + case studies + structured stakeholder interviews)

Scope: Pan-European review of local flexibility markets (LFMs), covering literature analysis, case studies of 7 live/concluded market initiatives, and 16 structured stakeholder interviews.

Methods

Three parallel tracks:

1. PRISMA systematic literature review — bibliometric analysis of academic literature on LFMs, organized into five macro-areas: market design, service typology, flexibility-providing technologies, TSO-DSO coordination, and communication infrastructure
2. Case studies — detailed market design documentation for 7 European LFM initiatives (GB, Netherlands, France, Sweden, Portugal, Slovenia, Italy)
3. Stakeholder interviews — 16 structured interviews: 6 DSOs, 7 BSPs, 3 MPOs, conducted via video call; questionnaires standardized per group; qualitative analysis followed by a 1–5 quali-quantitative barrier scoring

Markets covered

Market product designs (Table 3)

Detailed product parameters per country:

Sweden (sthlmflex) product detail:

• ShortFlex: day-ahead or intraday auction, hourly resolution, utilisation payment only
• ShortFlex Availability: days-ahead capacity reservation, availability + activation payment
• LongFlex: structural congestion, months-ahead multi-month reservation, availability + activation payment
• BSPs were also given opportunity to bid simultaneously for Svk’s national mFRR service — testing TSO-DSO coordination via NODES platform

France (Enedis) design note: DSO specifies direction, min quantity, availability window, max activation time (25 min), min duration (30 min). BSP may reject any individual dispatch order without penalty provided rejection occurs ≤15 minutes after dispatch order.

GOPACS (Netherlands) note: No baseline is required because each accepted bid constitutes a modification to a market operator’s commercial schedule — validation carried out by comparing updated commercial program with actual delivery.

Baseline definition methodologies (Table 4)

LFMs must verify delivered flexibility against a reference “baseline” of what would have happened absent activation. Methods range from simple historical averages to advanced ML:

Netherlands exception: GOPACS requires no baseline (see above).

Key limitation of historical methods: weather-driven demand shifts between observation period and activation day can cause large errors. Addressed by H-hour correction factors (e.g., E-distribuzione uses 2-hour correction).

Research perspective: Lind et al. (2023) provide a decision framework for method selection by DER technology (accuracy, simplicity, integrity). Ziras et al. argue that capacity-limitation services (rather than baseline-based energy services) are a simpler, more transparent alternative for distribution congestion management.

See also: Source - Lind et al Baseline Methods (2023).

Market outcomes (Section 3.3)

Data limited to markets with public historical records. Sthlmflex data was removed from the NODES platform following project conclusion and is no longer publicly available.

Prices observed in non-GB/NL markets

The ENW (Electricity North West, UK) pricing outlier illustrates that thin markets are highly vulnerable to strategic bidding at price caps.

Stakeholder interviews (Section 4)

Participants

• 6 DSOs: Unareti, Areti, E-distribuzione (Italy), E-REDES (Portugal), Elektro Ljubljana (Slovenia), AEM (Switzerland)
• 7 BSPs: Politecnico di Milano, A2A, EPQ, Energy Team, Octopus Energy, Hive Power, Free2Move e-Solutions
• 3 MPOs: PicloFlex (Piclo), NODES, GME

DSO perspectives (Section 4.1)

Key findings from DSO interviews:

Spatial granularity vs. liquidity tension: High granularity (specific streets or grid segments) helps target real needs but creates areas too small to attract sufficient BSP participation. This is a fundamental design trade-off in LFM architecture.

Baseline accuracy: DSOs exploring ML algorithms and digital twins to improve baseline reliability. Manual review of baseline submissions is operationally burdensome.

Limited network observability: Smart meter and DERMS deployment insufficient for real-time high-resolution monitoring in many distribution networks. DSOs often rely on static models and historical data.

Manual activation still dominant: DSOs communicate dispatch via phone, email, or SMS. API-based integration is in early development; lack of technical standards slows progress.

TSO-DSO coordination gap: Activation is handled independently by DSOs and TSOs with limited data sharing; no shared framework for prioritizing simultaneous activations. Some DSOs proposed that LFMs serve as a qualification platform for DERs seeking national market access — improving transparency and aggregator economics.

BSP perspectives (Section 4.2)

Revenue unpredictability: Major obstacle to business model development. BSPs need 3–5 year DSO need outlooks to plan investments.

Availability payments preferred: More certain revenue stream than utilisation; especially critical in pilot phases with unknown activation frequency.

GB as positive reference: When DSO commitment to procure and activate is clearly communicated (as in GB), market participation becomes economically viable.

Interoperability uneven: Automation of dispatch and remote control highly variable across BSPs and countries. In GB, BSPs can automatically control resources using locational price signals. In Switzerland, cloud-to-cloud communication and MODBUS-TCP being adopted.

Metering cost barrier: Field-level instrumentation required even for small resources; user interfaces described as “costly and inefficient,” discouraging new participants.

Italy-specific: No national platform explaining LFM rules and remuneration. Italian BSPs request unified national platform with standardized participation rules (as in GB framework).

Baseline adequacy for new DER types: Existing methods inadequate for PV, heat pumps, EVs. BSPs request ML-based methods that go beyond historical patterns.

BRP-LFM integration: Significant regulatory work needed to integrate LFM outcomes into spot markets — particularly BRP commercial exchanges during flexibility activation.

MPO perspectives (Section 4.3)

Platform capacity not the constraint: MPO platforms already able to handle far greater volumes than current market activity. The binding constraint is liquidity (demand side — DSO need activation — and supply side — BSP participation).

Market integration strategies differ:

• GME (Italy) integrated LFM section into existing national market platform (same web infrastructure as other markets)
• Piclo pursuing PicloMax — cross-market integration service, expanding from GB to other countries

Security and compliance: Robust infrastructure for data confidentiality; regulatory compliance central to platform positioning.

Five barrier dimensions — comparative synthesis (Section 4.4, Fig. 13)

Stakeholder grading (1–5 scale, 5 = strongest barrier):

Key conclusions

1. Forward auctions best for early-stage LFMs — provide DSOs planning security and lower BSP entry barriers. As markets mature, spot markets increase competition and enable emergency service procurement.
2. Locational pricing is the long-term direction — uniform pricing (pay-as-bid to all) is inadequate for capturing the actual congestion impact of flexibility.
3. Service expansion beyond active power — literature gradually moving to reactive power support, islanding, black start capabilities.
4. Technology prioritization: BESS, EVs, and DR consistently cited. Industrial electrification and district heating as sector-coupling flexibility sources are underexplored.
5. Centralized TSO-DSO coordination — most literature supports TSO-level optimization with DSO implementation.
6. Residential flexibility is the untapped frontier — still largely absent from less mature LFMs despite being essential for long-term market depth and liquidity.
7. NC DR as harmonization vehicle: The forthcoming Network Code on Demand Response is identified as the EU regulatory instrument expected to address the main gaps: standardized products, baseline methodologies, TSO-DSO coordination frameworks, and national/pan-EU market integration.

Relevance to wiki topics

• Flexibility Market: Major European comparative reference; products table (Table 3) documents non-Swedish LFM product designs; baseline methodology comparison (Table 4) is the most comprehensive in the wiki; price data for non-mature markets; stakeholder barrier synthesis
• Swedish Flexibility Market Landscape (sthlmflex): Independent academic confirmation of sthlmflex conclusion (“very low market liquidity”); notes data removal from NODES platform; documents TSO-mFRR dual-participation experiment in sthlmflex
• NODES: Confirmed as MPO for sthlmflex (and Effekthandel Väst); interview participant
• Network Code on Demand Response: Cited as the expected EU harmonization vehicle; common terms and conditions (DER aggregation, baselining, flexibility register, local market design, TSO-DSO coordination) and Union-wide provisions (standardized product attributes, metering device requirements)
• Congestion Management: Confirms spatial granularity vs. liquidity tension as fundamental design challenge
• TSO-DSO Coordination — The Central Design Problem: Four models taxonomy corroborated (separate, sequential, common, P2P); centralized approach preferred by literature

Data quality note

This is a peer-reviewed academic review (published in a top-tier Q1 journal in the field). Case study data is based on official market documents and direct DSO/BSP/MPO interviews. Price data is limited to markets with public historical records; sthlmflex data was removed from NODES after project conclusion. The stakeholder barrier scoring (Fig. 13) is a quali-quantitative synthesis by the authors, not direct quantitative data.