Utilities are told to decarbonise, maintain reliability, hold affordability, and stay inside the revenue cap. The four constraints fight each other. Simeo by Oxand models them together — at the asset level — so the trade-offs are visible, defensible, and revisable.
is the analytical discipline of quantifying the cost, carbon, and reliability impact of every investment decision — simultaneously — so that utilities can make asset-level choices that satisfy regulators, boards, and customers across a fixed CAPEX envelope. Simeo by Oxand brings 1,300+ energy performance models and 10,000+ degradation models to bear on this problem at the asset level, not the portfolio average.
Retire the gas peaker — what is the SAIDI cost on the worst weather day? Add the battery instead — at what capital cost and what carbon saving? The answer has to be quantified, not estimated.
The decarbonisation pathway needs investment over the next decade. Customer rates absorb how much? Where does the regulator say no? The model has to show the line.
Hardening every asset against the worst storm is unaffordable. Hardening none is irresponsible. The optimal line between them is an asset-level calculation, not a policy position.
The approved revenue cap is fixed. Trade-offs across all four mandates are zero-sum. Every decision to fund one asset is a decision not to fund another — and both need to be defended.
Every maintenance and investment action is quantified for kWh saved, GHG reduced, and CAPEX/OPEX cost. Optimise €/tCO₂ across the portfolio. No action is evaluated in isolation — all compete for the same envelope.
Every action's effect on failure probability and service consequence is quantified. SAIDI and availability impact calculated per scenario — not as a portfolio average but traced to the specific asset and the specific investment decision.
"Aggressive decarbonisation," "Reliability-first," "Balanced" — run side by side. See where each pathway breaks down. Every trade-off decision traceable to its inputs, the model, and the asset. Defensible to regulator, board, and customer advocate.
Every action quantified for kWh saved, GHG reduced, and CAPEX/OPEX cost. Optimise for €/tCO₂ across the portfolio — not against high-level targets.
Every action's effect on failure probability and service consequence. SAIDI and availability impact quantified per scenario, per asset.
Total CAPEX/OPEX trajectory matched against the revenue cap. Customer-rate impact visible for every scenario — before the submission, not after.
"Aggressive decarbonisation," "Reliability-first," "Balanced" — run side by side. See where each pathway breaks down at the asset level.
Forward weather exposure layered onto asset condition. The reliability cost of climate volatility — storms, heat, drought, fire — quantified per investment scenario.
Every trade-off decision traceable to its inputs. Defendable to regulator, board, and customer advocate without additional preparation.
"When does the coal unit go offline?" The answer affects emissions, reliability, customer rates, and capital programmes simultaneously. Simeo models them together — so the decision is defensible on all four dimensions.
Distribution capacity, transformer ratings, voltage management — all reshaped by heat-pump and EV adoption. Carbon win on the demand side; CAPEX challenge on the network side. Both quantified.
Same network, three futures: natural gas only, blend, full hydrogen. Asset-level investment requirement for each. Carbon and cost trade-off explicit and comparable.
Hardening against storm, heat, flood, and fire. Reliability win; carbon-and-cost question. Quantified at asset level so the optimal hardening boundary is evidence-based, not arbitrary.
No. Simeo integrates with carbon accounting and ESG reporting tools. The difference: Simeo models the carbon impact of investment decisions before you make them — your accounting tool tracks the result after. The two complement each other.
Yes. Hard constraints are supported — for example "stay under X tCO₂/year by 2030." The engine solves for an asset-level investment plan that fits the carbon budget, the CAPEX cap, and the reliability target simultaneously.
Yes. Multiple-future modelling is core to the platform. Run "100% renewable by 2035," "50% by 2035 with hydrogen blend," and "business as usual" side by side. Compare asset-level investment requirements for each future.
Yes. Real estate, social housing, infrastructure, and health buildings all face equivalent carbon-vs-CAPEX trade-offs. The same engine handles them with sector-specific predictive models for each asset family.
Constrained scenarios run in seconds. A new constraint set — a changed carbon budget, a revised revenue cap, an updated reliability target — produces a new plan in minutes, not weeks.
Bring your decarbonisation targets and reliability obligations. We'll show you what the asset-level trade-offs look like in your planning model.
