CVaR-LP powered stochastic optimization for energy portfolio management. Run thousands of Monte Carlo scenarios, explore the Pareto frontier between cost and risk, optimize dispatch, make market decisions, and manage fleet scheduling — all under configurable real-world constraints.
play_arrow Launch Interactive DemoRun N stochastic scenarios with configurable risk appetite via the λ slider — from conservative (λ=0) to aggressive (λ=1). The Merit-Order + CVaR-LP engine computes optimal dispatch in under a second, producing cost distributions, VaR/CVaR metrics, and a complete cost breakdown across Gen FC, Gen VC, DAM, GDAM, Deficit Buy, Sell Revenue, and DSM Penalty.
The Dispatch tab visualizes the full optimized schedule with scenario selection (P5, Median, P95 or specific scenario). Shows dispatch volumes, deviation from demand, surplus/deficit profiles, surrender profiles, and unit-level dispatch vs. entitlement for every generator.
The Market tab drives all trading decisions with comprehensive KPIs — Deficit Buy, Econ Buy (DAM+GDAM), Must Sell, Econ Sell, and Net Market Cost. RPO compliance tracking against MoP FY trajectory targets (FY 2025-26 to 2029-30) with Solar and Non-Solar progress bars. GDAM buy/sell decisions driven by REC-aware routing logic.
Two critical risk analytics in one view. The Market Decisions chart breaks down every trade into expected profit (teal, ↑) vs. CVaR 95% downside risk (red, ↓) per decision type — each bar is clickable for block-level drill-down. The Block Level timeline shows Expected P&L and CVaR across all 96 blocks at 15m/60m resolution, with peak annotations and buy/sell indicators.
The Risk tab is the analytical core — starting with Expected Cost (μ), VaR(95%), and CVaR(95%) summary cards showing variance and confidence metrics. Dedicated Over-Drawal and Under-Drawal risk cards with block-level drill-down charts and peak block analysis. The interactive Pareto Frontier explorer lets you navigate the full efficient frontier with what-if analysis at any λ.
Decompose total portfolio risk into its constituent sources using isolated Monte Carlo simulation. Understand exactly how much volatility comes from forecast model uncertainty (demand & RE prediction errors) vs. market price volatility (DAM/GDAM/RTM). The cost distribution chart shows tail behavior with VaR exceedance shading — essential for understanding worst-case scenarios.
The Fleet tab provides a complete view of all generators — Thermal, Hydel (Major), Hydel (Small), Must-Run, ISGS C1, ISGS C2, and STOA/MTOA sources. Track schedule vs. entitlement vs. declared capacity for every category with expandable per-unit drill-down, generation stack chart, and dedicated views for hydel major and bilateral contracts.
PARETO's constraint engine transforms theoretical optimization into real-world dispatch. Nine distinct constraint categories capture every operational, regulatory, seasonal, contractual, network, and penalty constraint — each fully configurable and re-optimizable on the fly with a single RE-OPTIMIZE click.
PARETO consumes multiple real-time and forecast data streams — demand forecasts, renewable energy generation forecasts, market price feeds, generator fleet specifications, and weather data. All sources are configurable and versioned via a dedicated Data Sources modal.
Five integrated modules working together to deliver optimal dispatch under real-world constraints.
Monte Carlo CVaR-LP optimizer. Configurable scenarios, λ risk slider, cost distribution with VaR tail, cost breakdown, and stacked dispatch at 5m/15m/60s.
96-block schedule with scenario selection (P5/Med/P95), deviation analysis, surplus/deficit, surrender tracking (thermal/ISGS/hydel), unit-level dispatch vs. entitlement.
RPO compliance, GDAM routing with REC logic, budget allocation, price forecasts with σ-bands, market position, P&L vs Risk per decision (clickable), block-level P&L.
Pareto frontier (λ vs P&L/OD/UD), what-if analysis, OD/UD block drill-down, cost distribution tail, risk decomposition (forecast vs. market price variance attribution).
Generator fleet management with expandable per-unit rows, generation stack by source, hydel major (SGS/NPH/VARAHI), STOA/MTOA/Banking bilateral contracts.
9 constraint categories: Generation, Gen Costs, Seasonal, SLA, Network, Market Budget, RPO & REC, DSM Penalty (CERC), and Forecast Error — all re-optimizable on the fly.
See how PARETO reduces procurement cost while managing risk within regulatory constraints.