BESS Strategic Investment Decision Tool

Integrated Decision Framework for Battery Energy Storage Investment in the Baltic Energy Sector
Implementation of the six-step integrated framework from the SSE Riga EMBA 2026 Diploma Project
"Strategic Integration of Battery Energy Storage in the Baltic Energy Sector"
Authors: Valdemar Fiodorovič & Ruslans Zavackis  |  Supervisor: Nikita Pusnakovs
New here? Start with Tab 0 (Start Here) β€” it explains the framework, the four decision-science theories behind it, and how to fill it in. Then work through tabs 1 β†’ 6 in order.
Step 0 β€” Start Here

Welcome to the BESS Strategic Investment Decision Framework

This tool implements the integrated six-step decision framework developed in the SSE Riga EMBA 2026 Diploma Project "Strategic Integration of Battery Energy Storage in the Baltic Energy Sector β€” How to make investment decisions in times of uncertainty" by Valdemar Fiodorovič and Ruslans Zavackis (supervisor: Nikita Pusnakovs). It is intended for investment committees, development directors, energy strategists, and policy analysts evaluating Battery Energy Storage System (BESS) investments in Estonia, Latvia, or Lithuania.

Why this framework exists

The thesis surfaced a striking finding from twelve expert interviews: no practitioner used formal frameworks (DCF, ROA, MAUT, IGDT) by name, yet the logic of all four was embedded in their reasoning in heuristic form. Practitioners stage commitments through implicit "real-options gates," weigh multiple criteria intuitively, and stress-test under deep uncertainty β€” but without the discipline that the academic frameworks provide. The result is decisions that are fast but unaudited: profitable outcomes mask process failures, and behavioural biases (herd, FOMO, anchoring to 2022 crisis prices) go undetected.

This tool translates the academic frameworks into a workable, structured instrument that an investment committee can actually use, while explicitly flagging the behavioural traps that fast-moving markets create.

A. The Six-Step Framework β€” What You'll Do

1

Environmental Scan

Classify the regulatory environment (navigable / moderate / high-information-gap) by selecting your country in the Strategic Context Bar at the top of every page.
2

Technology Assessment

Pick the C-rate / duration strategy (2-hr ancillary, 4-hr arbitrage, 10-hr+ multi-hour shift) β€” also via the Context Bar.
3

Organisational Fit

Identify your investor archetype (Entrepreneur/PE / Mid-size IPP / Incumbent Utility). Drives MAUT weights, IRR floors, decision-cycle targets.
4

Evaluation Stack (Tabs 1-4)

Quantitative core: DCF baseline β†’ ROA staging β†’ MAUT multi-criteria β†’ IGDT regime-shift robustness.
5

Behavioural Audit (Tab 5)

12-question bias log: herd behaviour, FOMO, anchoring, bounded rationality. Read the paradox disclaimer carefully.
6

Decision Pack (Tab 6)

Synthesises everything into a Go / No-Go / Defer / Proceed-in-Stages verdict. Confirm the Principles Register. Export the .txt pack as an IC memo.

B. How to Fill It In

  1. Set the Strategic Context Bar (blue gradient at the top of every page) β€” country, archetype, duration. Everything downstream auto-calibrates from this.
  2. Tab 1 (DCF) β€” enter project size, CAPEX, lifetime, revenue streams. The "AntuΕΎs Rule" button strips out ancillary revenue for the conservative case.
  3. Tab 2 (ROA) β€” review the Black-Scholes option premium, then mark each of the four Investment Gates (Land / Grid / Regulatory / Off-take) as Open / Cleared / Failed.
  4. Tab 3 (MAUT) β€” weights are pre-set from your archetype. Score the four investment alternatives.
  5. Tab 4 (IGDT) β€” adjust the three strategies (Oversized / Optimised / Pilot+Expand). The four Baltic regime shifts auto-apply.
  6. Tab 5 (Behavioural Audit) β€” answer 12 questions honestly. Read the self-assessment paradox disclaimer first.
  7. Tab 6 (Decision Pack) β€” tick off the Principles Register. Read the verdict box. Export the pack.

C. Theoretical Foundation β€” The Four Frameworks

Tabs 1–4 each apply a complementary decision-science framework with different epistemic assumptions and decision rules. The matrix below summarises how they relate. Crucially: no single framework is sufficient β€” the thesis's contribution is the integration.

Dimension DCF/NPV ROA MAUT IGDT
Philosophy Discounted cash certainty Strategic flexibility Multi-criteria trade-offs Robustness under deep uncertainty
Uncertainty Type Deterministic Known probability (Οƒ) Risk via utility Deep β€” no distribution
Decision Rule Max NPV Max Expanded NPV Max Expected Utility Max Robustness Ξ±Μ‚
Ideal Baltic User All β€” baseline filter Merchant / PE Mid-size IPP / Policy Utility / TSO / Grid planner
Strength Universal benchmark Captures staging value Integrates non-financial Survives regime shifts
Limitation Ignores flexibility Needs Οƒ estimate Subjective weights Can be over-conservative

D. When Is Each Framework Decisive?

DCF is the primary filter. Every project must pass NPV > 0 at the country-calibrated WACC. If it fails here, the other frameworks cannot rescue it.

ROA dominates when staging genuinely matters β€” when grid clarity, regulatory stability, or off-take security is uncertain but can be resolved by waiting. Less useful if the market window is closing.

MAUT is decisive when stakeholders disagree on what "success" means β€” TSO-led grid stability vs entrepreneur-led IRR. Surfaces those disagreements explicitly.

IGDT is decisive when historical data cannot tell you what tomorrow looks like β€” exactly the Baltic situation post-BRELL desynchronisation. Tests survival against named regime shifts (ancillary collapse, negative prices, tax shock, grid saturation).

E. Country & Archetype Quick Reference

πŸ‡±πŸ‡Ή Lithuania β€” High Information Gap

  • IRR target band: 15–25%
  • Ξ±Μ‚ threshold: 30% (highest)
  • Entrepreneur-led, fastest-moving
  • Bubble risk: 4,000+ MW pipeline

πŸ‡±πŸ‡» Latvia β€” Moderate Gap

  • IRR target band: 12–15%
  • Ξ±Μ‚ threshold: 25%
  • PE-disciplined, conservative
  • DSO fees disadvantage small projects

πŸ‡ͺπŸ‡ͺ Estonia β€” Navigable

  • IRR target band: 8–12%
  • Ξ±Μ‚ threshold: 20% (lowest)
  • Utility-led, longest horizons
  • Ancillary saturation empirically confirmed

Entrepreneur / PE Developer

  • Decision cycle: weeks (4–8 to FID)
  • IRR floor: 15%, WACC β‰ˆ 11%
  • Risk attitude: seeking
  • Default MAUT weight: IRR-heavy

Mid-size Vertically Integrated IPP

  • Decision cycle: months (2–3 to FID)
  • IRR floor: 11%, WACC β‰ˆ 8.5%
  • Risk attitude: neutral
  • Default MAUT weight: synergy-heavy

Incumbent State-owned Utility

  • Decision cycle: quarters (compressible)
  • IRR floor: 7%, WACC β‰ˆ 6.5%
  • Risk attitude: averse
  • Default MAUT weight: strategic-fit-heavy

Ready to begin?

1. Set the Strategic Context Bar at the top of the page (country + archetype + duration).
2. Click 1. DCF / NPV above and enter your project parameters.
3. Work through tabs 2 β†’ 6 in order. The Decision Pack on Tab 6 will produce your Go / No-Go / Defer verdict.

Step 4a β€” Financial Baseline

Module 1: DCF / NPV Baseline

Establishes minimum financial viability. Per the thesis: no expert reported using formal frameworks by name, yet all relied on IRR and payback heuristics. This module makes that heuristic transparent and country-calibrated. Decision rule: proceed only if NPV > 0 and IRR exceeds your archetype's threshold (shown below).

Project Inputs

Revenue Streams (€/MW/year)

Financial Metrics

NPV
€0M
vs threshold
IRR
0%
vs archetype target
Payback Period
β€” yr
years to recover CAPEX
LCOE
€0/MWh
levelised cost
Total CAPEX
€0M
Year-1 Revenue
€0M
Step 4b β€” Strategic Flexibility

Module 2: Real Options Analysis (Black-Scholes) + Investment Gates

Captures the value of staged commitment rather than a now-or-never decision. Per the thesis: "Investors who staged their commitments through conditional investment gates β€” proceeding to the next phase only after securing grid connection or subsidy allocations β€” were implicitly applying Real Options reasoning."

A. Black-Scholes Option Valuation

The strategic flexibility premium: total value = static NPV + option value. Higher volatility increases option value (asymmetric upside, downside protected by deferral).

d1
0.00
d2
0.00
Option Value
€0M
Static NPV
€0M
Expanded NPV
€0M
Option Premium
0%

B. Staged Investment Gates (Step 4 of Framework)

Each gate is an explicit option to abandon, defer, or proceed. Status: Open = milestone not yet reached, Cleared = secured, Failed = blocker that triggers abandonment. The framework requires re-running ROA / MAUT / IGDT at every gate.

1

Land Secured

Site control via lease/option/purchase. Grid-adjacent or hybrid PV/wind injection point preferred (curtailment priority under LT rules).

2

Grid Connection Contract

TSO/DSO connection agreement signed. Per Tjurins: DSO fees disproportionately disadvantage smaller projects. Existing connection (hybrid) is a major accelerator.

3

Regulatory Clarification

Subsidy regime confirmed; BBCM participation rules clear; no retroactive tax exposure. Per CeleΕ‘ius: clarity matters more than favourability.

4

Off-take / Trading Capability

In-house trading team OR PPA / route-to-market partner. Per Krasauskiene: trading expertise is decisive in capturing ancillary revenue.

C. BESS-Specific Real Options

Option to Defer: Wait for cell prices to decline, regulation to stabilise, or competitor saturation to clear. Higher value with longer T and higher Οƒ.

Option to Expand: 2-hour pilot (10–50 MW) with embedded right to scale to full duration. Particularly valuable as longer-duration systems (Tavoras's 4h / 10h trajectory) emerge.

Option to Switch: Dynamically reallocate between FCR / aFRR / mFRR / arbitrage. As ancillary markets saturate (Enefit Narva trajectory), switching to arbitrage and curtailment-priority preserves value.

Step 4c β€” Multi-Criteria Trade-offs

Module 3: Multi-Attribute Utility Theory (MAUT)

Translates conflicting objectives β€” IRR, grid reliability, environmental impact, regulatory exposure, technology maturity, and portfolio synergy β€” into a single composite utility. Weights are auto-calibrated to your archetype (Step 3 of the framework). Per the thesis: "The systematic weighting of IRR, regulatory risk, technical feasibility and market timing across multiple scenarios mirrors the multi-attribute trade-off logic that underpins MAUT."

A. Attribute Weights (sum to 100%)

AttributeWeight%
1. Financial Return (IRR / NPV)
35%
2. Grid Reliability / Energy Security
10%
3. Environmental Impact (COβ‚‚)
10%
4. Regulatory Stability
15%
5. Technology Maturity
10%
6. Portfolio Synergy (curtailment priority, hybrid offset)
20%

B. Risk Attitude (Utility Function)

C. Investment Alternatives (Baltic-tested archetypes)

Score each alternative 0–100 on each attribute. Defaults reflect typical Baltic project profiles documented in the thesis.

Ranked Alternatives

RankAlternativeUtility ScoreVerdict
β€”β€”β€”β€”
β€”β€”β€”β€”
β€”β€”β€”β€”
β€”β€”β€”β€”
Step 4d β€” Robustness Under Deep Uncertainty

Module 4: Information Gap Decision Theory (IGDT)

Key thesis upgrade: Conventional Β±20% sensitivity is structurally inadequate in a market that has produced βˆ’10,000 €/MWh events in Lithuania (30 March 2026), 18 M€ intraday excursions in Latvia (August 2025), and retroactive 10Γ— municipal-tax shocks. These are regime shifts, not perturbations around a regime. This module stress-tests each strategy against four documented Baltic regime shifts and computes the robustness radius Ξ±Μ‚.

A. Base-Case Project Parameters

B. Strategy Comparison (CAPEX vs Robustness Trade-off)

StrategyCAPEX (€M)Expected Rev (€M/yr)Break-even RevΞ±Μ‚ (Robustness)
A. Oversized β€” 200 MW, island-mode ready β€” β€”
B. Optimised β€” 100 MW, market-fit β€” β€”
C. Pilot + Expand β€” 25 MW + option β€” β€”

C. Baltic Regime-Shift Stress Tests

Each scenario is drawn from a documented Baltic event (sources cited). For each strategy, we recompute net revenue under the regime shift and show whether DSCR survives.

Robustness Interpretation Guide

  • Ξ±Μ‚ > 30% β†’ robust to high-information-gap environments (recommended for Lithuania per thesis prescription)
  • Ξ±Μ‚ 20–30% β†’ robust to moderate gaps (Latvia threshold)
  • Ξ±Μ‚ 10–20% β†’ robust only to navigable gaps (Estonia threshold)
  • Ξ±Μ‚ < 10% β†’ fragile β€” single regime shift can break solvency
Step 5 β€” Behavioural Audit

Module 5: Behavioural Bias Audit

Translates the most-cited thesis finding β€” that the Baltic BESS market is in a documented "hype cycle" (NorkeliΕ«nas, Tjurins) with inverted loss aversion ("FOMO > expected value") β€” into a structured 12-question audit. Output: a Bias Log that the framework requires you to revisit at every ROA gate.

⚠ The self-assessment paradox. If the biases catalogued here (herd, FOMO, anchoring, bounded rationality) are real and operating on you right now, they will also distort how you answer the questions below. This module cannot detect what you cannot see in yourself. Three mitigations the framework requires you to consider:
  1. Complete this audit BLIND β€” before reviewing your DCF / IGDT results, so post-rationalisation cannot reverse-engineer your answers to match a desired verdict.
  2. Have an INDEPENDENT REVIEWER (a colleague not on the deal team) complete the same audit separately. Treat any divergence between their score and yours as the signal worth investigating, not noise to be reconciled.
  3. Record your completion mode honestly below β€” it surfaces in the final verdict. Self-assessed scores are interpreted with caution; an independent or dual completion satisfies Principle 6 in the Register (Module 6) and lifts a high-bias DEFER toward CONDITIONAL.
Why this matters: Per the thesis, "the perceived loss from missing the first-mover window exceeds the perceived loss from an unsuccessful investment." This module surfaces the biases that intuition-led practice cannot self-detect.

A. Herd Behaviour Risk Barazza & Strachan (2020); thesis: "hype cycle" framing

A1. Our investment thesis depends on the same market assumptions held by every other Baltic BESS entrant (ancillary revenue stacking, similar IRR targets).
A2. The trigger for analysing this investment was a competitor announcement or government marketing campaign rather than independent thesis development.
A3. Our revenue projections mirror the publicly stated assumptions of the majority of announced Baltic BESS projects (no independent revenue forecast).

B. Inverted Loss Aversion / FOMO Kahneman & Tversky (1979); thesis: "FOMO > expected value"

B1. The primary driver of investment urgency is fear of missing the first-mover window rather than positive expected value relative to alternatives.
B2. We have not formally evaluated what happens if we delay this decision by 12 months (i.e., the "do nothing" baseline is missing).
B3. Our IRR target matches the early-mover 20-30% returns quoted in industry press, without a market-saturation decline curve.

C. Anchoring to 2022 Energy-Crisis Prices Kahneman & Tversky (1979); thesis: "strong anchoring to crisis price levels"

C1. Our revenue base case uses 2022–2024 energy-crisis price levels as the reference point rather than current (May 2026) prices.
C2. We have not constructed a scenario where ancillary market revenues decline by 40-60% (the documented Enefit Narva trajectory).
C3. Our sensitivity analysis uses Β±20% variations around a base case rather than structurally different market regimes (negative prices, tax shock, ancillary collapse).

D. Bounded Rationality & Recognition-Primed Shortcuts Simon (1955); Klein (1998); thesis: "IRR > 10%, payback < 5y heuristics"

D1. Our go/no-go decision rests primarily on heuristic thresholds (IRR > X%, payback < Y years) without a multi-attribute / MAUT evaluation.
D2. We have adopted an external consultant's financial model without independently re-validating its key assumptions.
D3. Pattern-matching to other markets (e.g. UK battery storage 2016–2018) is a primary input to our forecast rather than Baltic-specific structural analysis.

Aggregate Bias Score

0 / 24
Herd Behaviour
0/6
FOMO / Inverted LA
0/6
Anchoring
0/6
Bounded Rationality
0/6

Completion Mode Determines how the bias score is interpreted downstream

Honestly record who completed this audit. The selection appears in the Decision Pack and influences the final verdict.

Step 6 β€” Decision Principles & Post-Decision Review

Module 6: Synthesis & Decision Pack

Integrates outputs from Modules 1–5 into a structured Go / No-Go / Defer recommendation, archetype-specific decision rules, and an exportable Decision Pack. Re-run Steps 1, 4 and 5 at every investment gate; review the Principles Register at every quarterly investment committee.

A. Six-Step Framework Walkthrough

1

Environmental Scan

Classify regulatory environment as navigable / moderate / high-information-gap. Drives IGDT robustness threshold.
β€”
2

Technology Assessment

Score commoditisation + C-rate strategy. 2h = ancillary, 4h = arbitrage, 10h+ = emerging.
β€”
3

Organisational Fit

Decision-cycle target by archetype: weeks (entrepreneur) β†’ months (IPP) β†’ quarters (utility).
β€”
4

Evaluation Stack (ROA + MAUT + IGDT)

DCF baseline β†’ option staging β†’ multi-attribute β†’ regime-shift robustness.
β€”
5

Behavioural Audit

12-question bias log: herd, FOMO, anchoring, bounded rationality.
β€”
6

Principles Register

Confirm decision principles before commitment; review post-decision regardless of outcome.
β€”

B. Decision Principles Register

Confirm each principle before issuing FID. Per Dalio (2017) and the thesis: a profitable decision reached through a violated principle accumulates rather than corrects organisational error.

  • Auxiliary revenue is excluded from base-case (AntuΕΎs Rule) OR explicitly justified with declining schedule
    Source: AntuΕΎs, Enefit Green Latvia β€” converts loss aversion into strategic upside
  • At least one tax-shock IGDT scenario has been run and project remains viable
    Source: CeleΕ‘ius β€” municipal real-estate tax increased 10Γ— post-FID
  • Exit price / abandon trigger is defined before commitment
    Source: thesis decision rule β€” "no commitment without an exit price"
  • Decision-cycle target is defined and matched to archetype before analysis begins
    Source: Karoblis vs CeleΕ‘ius β€” entrepreneurs 3-6Γ— faster than utilities
  • Robustness radius (Ξ±Μ‚) confirmed above country threshold (LT 30%, LV 25%, EE 20%)
    Source: thesis Section 4.8.10 prescriptive decision rules
  • Behavioural bias score < 13/24, OR independent second-team review completed
    Source: thesis rule β€” "high herd-risk score β†’ mandatory independent review"
  • Post-decision review scheduled β€” process audited regardless of outcome
    Source: Dalio (2017) β€” "outcome quality β‰  process quality"

C. Archetype-Specific Decision Rules

D. Decision Verdict

E. Country-Specific Advisory

F. Baltic Reference Projects (Thesis Table 1)

πŸ‡±πŸ‡Ή Lithuania β€” Energy Cells
200 MW / 200 MWh Β· Operational 2022-2023
CAPEX €109M Β· ~80% EU RRF-funded
Use: Island-mode reserve Β· 4 sites (Vilnius, Alytus, Utena, Ε iauliai)
πŸ‡±πŸ‡Ή Lithuania β€” Ignitis (KelmΔ— & MaΕΎeikiai)
291 MW / 582 MWh (planned ~2027)
Largest Rolls-Royce BESS order globally
Use: Wind co-location, price-volatility damping
πŸ‡±πŸ‡» Latvia β€” Tārgale Wind+BESS
10 MW / 20 MWh Β· Operational 2024
First utility-scale BESS in LV
Use: Wind firming, grid-decoupling preparedness
πŸ‡±πŸ‡» Latvia β€” AST RΔ“zekne & Tume
80 MW / 160 MWh Β· 2025
TSO-owned Β· €77M (EU-funded)
Use: Synchronisation balancing capacity
πŸ‡±πŸ‡» Latvia β€” NGEN/Tesla Liepāja
100 MW / 200 MWh (expected 2026)
~€30M private investment
Use: First standalone merchant BESS in LV
πŸ‡ͺπŸ‡ͺ Estonia β€” Auvere (Eesti Energia)
26.5 MW / 53 MWh Β· Operational Feb 2025
CAPEX €19.6M Β· utility-owned
Use: Frequency reserve during synchronisation
πŸ‡ͺπŸ‡ͺ Estonia β€” Baltic Storage Hertz 1 & 2
200 MW / 400 MWh Β· 2025-2026
CAPEX €85.6M Β· EBRD/NIB-financed
Projected IRR 20–30% (merchant)

G. Exportable Decision Pack

Need to review the theoretical foundations? See the Framework Comparison Matrix on Tab 0 (Start Here).