Spain Methodology

Modo Energy provides benchmark data for battery energy storage systems across global energy markets. We apply the same standardised methodology everywhere, so every Index we produce is consistent and transparent.

1. Introduction

This document explains how Modo Energy calculates and constructs its battery energy storage Indices in Spain. It covers four things:

• the assumptions that define a representative asset;
• the components that make up published revenues;
• the optimisation model that simulates asset dispatch; and
• the data inputs and transformations that feed the simulation.

Together, these ensure accurate and reliable benchmarking for Spain's battery energy storage sector.

1.1 Why Spain requires a simulated index

The Spain Index differs from our GB Index in one fundamental respect: it is simulated, not measured.

In Great Britain, utility-scale batteries are registered as Balancing Mechanism Units (BMUs). BMU status comes with strict data-sharing obligations. This lets us compute revenues from publicly reported physical notifications, bid-offer acceptances, ancillary contracts, and settlement metered volumes. The GB Index reflects what a representative portfolio of real assets earned.

Spain has no equivalent data regime. Battery activity in the wholesale and ancillary markets is published only at programming-unit (UP) level, not per asset. Public BESS revenue disclosures are sparse and uneven across markets. The installed fleet is also still small enough that fleet-wide measurement would not be statistically representative.

To produce a benchmark under these conditions, we simulate the dispatch of a representative battery asset against publicly available market data. We use our Global Dispatch Model, a mixed-integer linear programme (MILP) that maximises battery revenues subject to market participation rules.

1.2 What the Spain Simulated Index represents

The Modo Energy Spain Index family (the ME BESS ES Indices) represents the simulated revenue performance of grid-scale lithium-ion battery energy storage systems in Spain. The family includes variants grouped by system duration, so revenues can be compared across different types of utility-scale battery systems. The indices reflect revenues that a representative asset could earn.

2. Index Construction

2.1 The ME BESS ES Indices

Modo Energy currently produces the following indices for Spain:

All indices use the same published methodology. The only difference is the duration parameter of the representative asset.

2.2 Representative BESS specification

The representative asset is specified as follows:

2.3 Index calculation methodology

We calculate the Index in four steps:

1. Run the Global Dispatch Model over the assessed period, using the representative asset in §2.2 and the input data in §4.2.
2. Compute the simulated revenue of the representative asset in EUR, for each modelled market and direction.
3. Sum revenues per settlement period and divide by the rated power (50 MW). This gives an Index value in EUR/MW per settlement period.
4. Aggregate these values into monthly, quarterly, and annual indices as described in §2.4.

The calculation follows a clearly defined, rule-based methodology. As of the initial publication, no post-hoc calibration factor is applied (see §5.9).

2.4 Index value representation

All Index values are reported as net revenues per unit of rated power. We use two representations:

• EUR/MW (period): total Index revenue for the assessed period (e.g. EUR/MW/month, EUR/MW/year).
• EUR/MW/year (annualised): total Index revenue for the assessed period, divided by the number of days in the period, multiplied by 365.

2.5 Publication cadence and revisions

The Spain Indices update daily. We ingest source data from all markets in §4.2 every day and publish Index values for delivery day D-2 every calendar day. The two-day lag gives settlement, late submissions, and backfills on aFRRE, mFRR, and TTRR P2 activated-energy series time to complete before we compute the Index for that day.

We may revise previously published Index values in three cases: when upstream providers (ESIOS, OMIE) correct values for periods already covered by a published Index; when additional source data becomes available that materially improves the accuracy of a historical value; or when a methodology change under §7 applies retrospectively. We log every revision with the affected period and the reason, and communicate it to users in line with §7.2.

2.6 Market evolution reflected in the Index

The Index reflects each market structure only for the periods in which its native mechanism and data were in force. The key Iberian milestones are:

3. Revenue Components

3.1 Revenue components included in the Indices

The Spain Indices capture the primary revenue opportunities available to a representative BESS in Spain's wholesale and ancillary markets. The table below shows each component, the market it is modelled from, and the price signal used.

3.2 Excluded revenues

The Spain Indices exclude revenues from the following sources:

• Primary reserve (Regulación Primaria / RPF): in Spain, primary frequency response is a mandatory, unpaid obligation for generators above a size threshold. It is not a traded product, so there is no revenue stream to model.
• Imbalance penalties: we assume positions are fully closed out in the real-time settlement step, so no residual imbalance exposure is modelled.
• Capacity mechanism payments: Spain's capacity mechanism is still in implementation. We will add capacity market revenues once the market starts clearing and prices are published publicly.
• Curtailment compensation: site-specific, so not modelled.
• Other network access charges: site-specific. They default to zero in the representative asset.
• Bilateral contracts (PPAs, tolls, floors): not modelled. They do not change the optimal battery dispatch, except in some co-located cases.
• Battery operator fees, warranty costs, and O&M: the Index reports gross market revenue, not net-of-opex.

4. Data Inputs and Use of Discretion

4.1 Data visibility and quality

The Spain Index is built exclusively from publicly available market data. The only exception is the representative asset parameters in §2.2, which Modo Energy sets.

4.2 Data inputs and sources

The inputs and their providers are listed below. All transformations are documented in §4.3.

We ingest all inputs into our data lake daily and version them at the source-table level. Eighteen distinct ESIOS / OMIE source tables underpin the Index.

4.3 Use of discretion

Modo Energy applies discretion strictly within predefined parameters. We select sources based on reliability, relevance to BESS operations, and the activity, depth, and transparency of the underlying market. All discretionary decisions follow the benchmark methodology and are subject to internal governance oversight.

5. Modelling Methodology

5.1 Overview of the Global Dispatch Model

We produce the Spain Index by simulating the dispatch of the representative asset in §2.2 against historical market prices, using our Global Dispatch Model (GDM). This is the same proprietary optimisation framework behind our Indices in other regions and our forecasts. For each day in the assessed period, the GDM works out how the representative asset would have scheduled its power across the markets in §3.1 to maximise revenue, given the physical limits of the battery and the rules of each market.

5.2 What the model is solving for

The GDM answers one practical question: given the prices observed on a given day, and the physical and regulatory limits of the asset, what is the highest revenue a well-run battery could have earned?

To answer it, the model allocates the battery's power and stored energy across three families of market opportunities:

• Energy markets: the day-ahead market and the intraday continuous market.
• Ancillary capacity markets: aFRR (Banda Secundaria), where the battery is paid to hold capacity available for the TSO (REE).
• Ancillary activated-energy markets: aFRRE, mFRR, and TTRR P2, where the battery is paid in EUR/MWh for the energy it actually delivers when called.

Revenue is the sum of these streams, net of the charging energy cost. The model also applies internal consistency rules that stop it from scheduling trades that look profitable on paper but that a physical battery could not execute (§5.4).

5.3 Three-step optimisation sequence

A real BESS trader in Spain does not make all decisions at the same moment. Each market gate closes before the next, and traders commit at each gate using only the information available at that point. The sequence of the Spanish power market is:

Three timing features shape the optimisation sequence:

• The MIC has no single gate close. It is a continuous bilateral market. Positions roll until the T-60 / T-30 hard stops per delivery period. The dual gate close took effect on 1 January 2026, and the cross-zonal window after T-60 carries a large share of near-delivery re-optimisation.
• mFRR and aFRRE share the same BSP gate closure time (T-25 minutes). This is set by the ACER-approved Implementation Frameworks and transposed into PO 7.2 and PO 7.3. They differ in clearing speed: aFRRE clears every 4 seconds, mFRR every 15 minutes.
• Granularity is now 15-minute across the stack. Intraday auctions and the MIC moved on 18 March 2025, and day-ahead on 1 October 2025 (96 periods per day, up from 24). The January 2026 reform (BOE-A-2026-1377) also shortened the PDBF publication window from 30 to 15 minutes after day-ahead results.

A further shift is on the way. When PO 7.4 introduces zonal voltage-control auctions (dynamic service expected around 17 March 2026, zonal auctions live no later than 26 December 2026), the aFRR capacity gate is expected to move one hour later (17:00 GCT, results by 17:30). We will review the methodology when this takes effect (§7).

The model reflects this sequence by solving the dispatch problem in three sequential steps:

1. Day-ahead step: sets aFRR capacity commitments and day-ahead energy positions. In the Backtest scenario, TTRR P2 commitments are also co-optimised at this step. System-activated energy is published with day-of resolution, so the Backtest scenario uses historical realised activations as the forward signal.
2. Intraday step: rebalances day-ahead positions through the OMIE intraday continuous market (ICM).
3. Real-time step: sets aFRRE activated-energy positions and, in the Backtest scenario, mFRR activated-energy positions. The intraday continuous market is also considered in this step.

Each step takes the positions committed in earlier steps as fixed. Once a decision is locked in, the model cannot unwind it. This sequencing is what makes the simulation directionally realistic, rather than a single idealised all-markets optimisation.

5.3.1 Day-ahead step

• Granularity: 60 minutes before 2025-10-01; 15 minutes from 2025-10-01 onward, reflecting the OMIE / SDAC move to a 15-minute day-ahead auction.
• Foresight: perfect foresight of day-ahead energy prices and aFRR capacity prices over the full day.
• Markets optimised (Central / Low scenarios): day-ahead energy, aFRR capacity.
• Markets optimised (Backtest scenario): day-ahead energy, aFRR capacity, TTRR P2 activated energy.

5.3.2 Intraday step

• Granularity: 60 minutes before 2025-03-18; 15 minutes from 2025-03-18 onward.
• Rolling horizon: 2-hour windows, advanced sequentially.
• Foresight: perfect foresight of OMIE ICM continuous prices over each 2-hour rolling window.
• Markets optimised: OMIE intraday continuous (ICM index).
• Commitments carried in: day-ahead energy positions and aFRR capacity from Step 1 are fixed.

5.3.3 Real-time step

• Granularity: 60 minutes before 2025-03-18; 15 minutes from 2025-03-18 onward.
• Rolling horizon: 2-hour windows, advanced sequentially.
• Foresight: perfect foresight of real-time prices and activation prices over each 2-hour rolling window.
• Markets optimised (Central / High / Low scenarios): real-time energy, aFRRE activated energy.
• Markets optimised (Backtest scenario): real-time energy, aFRRE activated energy, mFRR activated energy.
• Commitments carried in: all prior steps' positions are fixed.

5.4 Market stacking and physical limits

Spain's market design lets a battery hold simultaneous positions across day-ahead energy, intraday continuous energy, real-time energy, aFRR capacity, aFRRE energy, mFRR energy, and TTRR P2 energy. The limits are physical: the battery itself and the grid connection. The model enforces stacking through three families of constraints:

1. Sufficient state of charge for ancillary delivery. The battery's state of charge at each timestep must be enough to deliver every discharging-direction ancillary product it holds at that moment, over each product's delivery horizon (15 minutes for aFRR / aFRRE / mFRR, 60 minutes for TTRR P2). These horizons come from the energy reservoir requirements in the REE prequalification conditions.
2. No double-counting between aFRR and aFRRE. aFRR (capacity reservation) and aFRRE (energy activation) are distinct products. The model applies a pair of parallel constraints so that each physical limit (grid, battery, SOC) is checked once including aFRR and once including aFRRE, but never both in the same inequality. Reserved aFRR capacity must bid into aFRRE but is not necessarily activated, and it cannot bid into other energy markets at the same time.
3. One direction at a time in activation markets. For the three energy-activation markets (aFRRE, mFRR, TTRR P2), the LP allows only one direction (POS or NEG) per timestep per market, enforced through a binary variable v_binary_{market}. This stops the model from earning revenue on both sides of an activation product in the same settlement period, which is physically impossible.

5.5 Battery physical model

The representative asset is modelled as a single lumped battery governed by four technical characteristics:

• Round-trip efficiency of 88%. Efficiency losses apply to the charging flow: 1 MWh drawn from the grid stores 0.88 MWh of usable energy.
• Continuous state of charge. Stored energy in each timestep equals the previous level, plus charging (net of efficiency), minus discharging. The SOC adjustment uses the net energy flow across energy markets within each 15-minute timestep. Paper trades that net out within a settlement period therefore incur no round-trip efficiency penalty.
• State of charge boundaries. To allow day-by-day solving, SOC is assumed to be 0% at midnight each day. During the day, SOC can vary freely between 0 and 100%, subject to the cycling cap below.
• Cycling limit per day. Total discharge throughput per day is capped at the daily cycling limit (2.0 cycles) times the battery's usable capacity. Both wholesale discharge and ancillary activation count toward the cap. Warranties are typically written on total throughput, not on the market the energy was sold into.

Cell-level degradation is intentionally disabled in the published Index (§2.2). This keeps the asset's duration constant across the full history, so years remain comparable.

5.6 Ancillary services: capacity vs activated energy

Spain's balancing stack separates two things: reserving capacity (Banda Secundaria capacity payments) and delivering energy when called (aFRRE, mFRR, and TTRR P2 activation payments). The two product families bid into different gates, and the model treats them differently:

• Capacity market (aFRR / Banda Secundaria). REE pays the battery for holding capacity available. The bid is set in the day-ahead step. Revenue accrues at the cleared capacity price (EUR/MW/h) over each delivery hour. Capacity held reduces the power and SOC available for energy markets. Holding capacity is independent of activation: it does not drain SOC or count toward cycling on its own, so the capacity payment is the only revenue from aFRR itself. Since the 20 November 2024 SRS reform, aFRR energy bids are formally decoupled from the capacity allocation. A provider could, in principle, price its energy bid out of activation. In practice, REE expects allocated capacity to stay available, and repeated withdrawal draws regulatory scrutiny. The model therefore assumes that capacity allocated in the day-ahead step remains fully available to the aFRRE energy market.
• Activated-energy markets (aFRRE, mFRR, TTRR P2). The battery is paid in EUR/MWh on the energy it actually delivers when called. Revenue is recognised on the activated MWh, not the contracted MW. The energy flow moves SOC and counts toward the daily cycling limit.

aFRRE held volume in any settlement period is further capped at the system aFRRE activation ratio for that direction, multiplied by the battery's rated power:

The battery is a price-taker, so we assume it is always activated up to this ratio if it bids. If 20% of the aFRR reserve is activated, up to 20% of the battery can be activated in aFRRE. The aFRRE (or TTRR or mFRR) activation ratio is determined by the BESS fleet (the higher the BESS fleet considered, the lower the factor). This is done to capture the cannibalisation process that occurs in mature BESS markets for ancillary services.

5.7 TTRR P2 (technical restrictions, phase 2)

TTRR P2 is phase 2 of the technical restrictions process that REE runs immediately after the day-ahead market clears. REE checks the day-ahead schedule (PDBF) for network constraints and publishes a viable schedule (PDVP) by D-1 14:45. The process runs in two phases:

• Phase 1 is locational. REE dispatches specific assets to resolve network constraints identified in the day-ahead schedule (PDBF). Upward dispatch is paid as bid. Downward curtailment is not paid.
• Phase 2 is open country-wide. Any unit in Spain can participate. REE rebalances the system as a whole, keeping Phase 1 commitments fixed.

Phase 1 mostly dispatches thermal generation upward to resolve constraints. Phase 2 then nets that energy off through downward activations. The result: Phase 2 is structurally a downward market. Downward activations exceeded upward activations by more than an order of magnitude in 2025. This creates a systematic interaction between day-ahead positions and Phase 2 activations, which is why the Backtest scenario co-optimises day-ahead energy and TTRR P2 in the same step (§5.3.1). In dispatch, the model uses TTRR P2 downward activations in two distinct ways:

• Same-period netting. Energy sold in the day-ahead market is bought back in TTRR P2 within the same settlement period. The position nets out financially without moving the battery's state of charge. Under the net-flow SOC rule in §5.5, it incurs no round-trip efficiency penalty.
• Charging source. The battery charges at the TTRR P2 downward activation price and discharges the stored energy later into the day-ahead, intraday, or balancing markets. In these periods, TTRR P2 is simply an alternative to charging at the day-ahead or intraday price.

Unlike the frequency-control markets, TTRR P2 activations are zonally driven and persistently asymmetric, especially in periods of high renewable curtailment. The Index reflects these properties as follows:

• Granularity: ESIOS publishes TTRR P2 prices and activations at hourly resolution. The LP models the market at 60-minute granularity even when other markets run at 15 minutes.
• Backtest-only: TTRR P2 activations are zonal, and our price-forecast service does not yet emit a forward signal for them. TTRR P2 therefore enters the LP only under the Backtest scenario. Central / High / Low scenarios omit it. We will revisit this when forecast-side coverage is added.
• Asymmetric coverage: where ESIOS publishes only one direction (commonly NEG), the symmetric-band fallback in §4.3 does not apply. TTRR P2 is intrinsically asymmetric. The gap is real, not a measurement artefact.

5.8 mFRR (Reserva de Regulación Terciaria)

The mFRR market compensates manual frequency restoration as an energy-only product. REE calls mFRR-qualified plants per event and pays the cleared marginal price on activated MWh. Spain has no separately paid mFRR capacity product. The market connected to the European MARI platform on 10 December 2024, with clearing per 15-minute MTU and a BSP gate closure of T-25 minutes.

The mFRR price signal is asymmetric and tail-heavy. Upward activation prices average well above day-ahead levels and spike hard in scarcity events. Downward activation prices average close to zero. Capturing this signal is the main reason mFRR is in the Backtest. The model treats mFRR as follows:

• Granularity: 15-minute, matching ESIOS publication of activated mFRR energy.
• Backtest-only: ESIOS publishes mFRR activations only after the fact, and our price-forecast service does not yet emit a forward mFRR signal. mFRR therefore enters the LP only under the Backtest scenario.
• Energy-activation only: revenue is recognised on activated MWh. There is no capacity payment.

5.9 Revenue calibration

In other Modo Energy indices (for example ME BESS DE), we apply a flat calibration factor to all simulated per-timestep revenues. It bridges the gap between perfect-foresight modelled revenues and what a real fleet can earn, covering residual foresight, availability, and execution gaps.

For the initial publication of the ME BESS ES Index, no post-hoc calibration factor is applied (calibration factor = 1.00). Three reasons:

• Public per-asset BESS revenue disclosure in Spain is too sparse to anchor a Spain-specific factor empirically.
• The model's day-ahead-only sub-line is directly comparable to publicly available Iberian BESS TBx benchmarks (~€80k/MW for 2024; ~€130k/MW for 2025), and matches within a tight band.

We may introduce a calibration factor in a future methodology version, once enough disclosed Iberian BESS revenues exist to anchor one. Any such change would be a single scalar, to preserve the internal revenue ratios produced by the optimisation, and would follow the methodology change process (§7).

6. Governance and Compliance

Modo Energy is committed to transparency. We publish detailed explanations of calculation methodologies, revenue components, and benchmark updates, so stakeholders can fully understand how the benchmark works. Transparency measures include:

• Publication of methodology documents outlining calculation processes and revenue components.
• Historical data updates to maintain accuracy and consistency.
• Advance notification of significant changes, with a two-week consultation period.
• Documentation of stakeholder feedback and responses, available on request by emailing team@modoenergy.com.

7. Methodology changes

7.1 Review and update process

The methodology goes through a structured review process to stay aligned with evolving market conditions and regulatory requirements. Reviews are conducted:

• Annually, by the Benchmark Oversight Function.
• Quarterly, through manual audits of data accuracy and consistency.
• Whenever we identify material changes in market conditions or data availability (for example: the OMIE move to 15-minute day-ahead auctions; the SRS reform of aFRR procurement; ESIOS publication of new activated-energy series).
  • Direct back-testing against observed transactions is not possible, because per-asset revenue is not publicly disclosed in Spain. Instead, we cross-check the model's day-ahead-only sub-line against publicly available Iberian BESS benchmarks (see §5.9), and validate the revenue stack composition against Modo's published Iberian BESS market analysis.

Each review follows a documented approval process. Updates are evaluated thoroughly before implementation.

7.2 Notification of changes

We communicate significant methodology changes to stakeholders with advance notice and a clear timeline for review and feedback. The process includes:

• Publishing proposed changes with a detailed impact analysis.
• A two-week consultation period for stakeholder comments.
• Formal responses to stakeholder feedback, with adjustments incorporated where appropriate.
• An archive of all changes, to preserve historical comparability and transparency.

8. Consistency and continuity

8.1 Quality assurance

Modo Energy applies rigorous quality assurance to protect benchmark integrity:

• Continuous automated validation checks that flag discrepancies in input data.
• Automated regression tests on every change to the Global Dispatch Model.
• Quarterly manual audits of data sources and methodology compliance.
• Internal audits for alignment with regulatory standards.

8.2 Data integrity

We maintain data integrity through:

• Secure data management protocols, including access controls and regular backups.
• Clear traceability from raw source (ESIOS, OMIE) into the model feed.

8.3 Handling data quality issues

When input data falls below the standard needed for accurate benchmark determination, we follow a clear procedure:

1. Verify the issue: we confirm the problem with the upstream data provider.
2. Tell customers: we inform customers of any confirmed data issue, and the corrective actions taken, within 48 hours of confirmation.
3. Handle unavailability: if the provider cannot supply the required data, we notify customers of the impact and publish the Index only once finalised data is available.

8.4 Traceability and verification

Every benchmark calculation is fully traceable and verifiable:

• We keep comprehensive records of input data, model version, and calculation outputs.
• Reproducibility: every published Index value can be reproduced from the archived input data and the model version in use at publication.
• We publicly disclose material methodology changes.

Appendix I: Methodology changes

Methodology changes since first publication will be tracked here.

Internal calibration notes (pre-publication)

The following calibration adjustments were made during model development and are recorded here for traceability. They predate the initial published version, so they do not constitute methodological changes relative to published data.

• mFRR and TTRR P2 modelled as energy-activation, not capacity. Initial drafts modelled them as capacity-contract markets. Corrected to throughput-scaled revenue on the activated MWh, consistent with how the products clear in Spain.
• Sign map extended to AFRRE, MFRR, TTRR_P2. The charging_price_positive flag on the _NEG direction of each activation market was being ignored in the original sign-handling code. The European-wide sign map was extended to cover all three families.
• P95 throughput normalisation. Activation throughput is now normalised by the P95 of the historical activated-energy series (clipped to [0, 1]) rather than a fixed fleet-size constant, which had been saturating the normalisation series at 1.0 across most of the period. (This is not present in the latest operation of the benchmark).
• Symmetric-band fallback for pre-2024-11-20 aFRR and aFRRE. ESIOS published only one direction of the symmetric Banda Secundaria before the SRS reform. The model now mirrors the published direction onto the absent direction to preserve revenue comparability across the reform boundary.
• Both directional columns enforced present. Empty one-side rows in the directional price/volume joins were causing downstream task failures. The data-pivot now guarantees both directions are present, with NaN filled by the symmetric-band fallback rule where applicable.
• SOC adjustment now uses net energy-market flows. The state-of-charge update now nets paper trades within each 15-minute timestep before applying the round-trip efficiency penalty. The previous implementation applied the (1 − η) loss to gross trades, producing a phantom penalty on paper trades that financially netted out within a single settlement period.

Clarification updates

None at initial publication.

Disclaimer

This document, including the methodologies and indices described herein, is the proprietary work of MODO ENERGY LIMITED ("Modo Energy") and is provided solely for informational purposes. These indices are designed for use in financial analysis, benchmarking, and decision-making. However, they do not constitute investment advice or a recommendation regarding any specific financial instrument, asset, or strategy.

While Modo Energy strives to ensure the accuracy, reliability, and transparency of the indices and methodologies, all information is provided "as is", without any express or implied warranties, including but not limited to warranties of merchantability or fitness for a particular purpose. Users should be aware that the indices are derived from publicly available market data that may be subject to revisions, delays, or inaccuracies, and that the Spain Indices are simulated from a representative asset rather than observed from underlying transactions. Past performance is not indicative of future results, and external factors such as regulatory changes, market conditions, and asset-specific characteristics may impact index performance.

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