Five practice areas. One coherent view of the energy system.

We build hybrid forecasting stacks, ARIMA, LSTM/GRU, Transformer architectures and reinforcement-learning agents, calibrated to your market’s microstructure. Outputs feed bidding, hedging, and PPA structuring decisions.

Scenario-based studies that integrate macroeconomic signals, policy trajectories (CERC, FERC, EU ETS, IRA), and technology cost curves to project capacity, generation mix, and price corridors out to 2035.

Stochastic optimization, digital twins, and reinforcement learning applied to dispatch, augmentation, and degradation strategies. Built for owners optimising across energy, ancillary services, and capacity revenue stacks.

Load-flow, short-circuit, dynamic stability, hosting capacity, and protection coordination studies. In plain terms: we check whether the grid stays within voltage, current, and frequency limits under normal operation, faults, and after disturbances. We pair classical power-system engineering with modern data tooling so results actually inform planning decisions. Recent scopes include demand–supply gap analysis, MW / MWh / MVAR (active power, energy, and reactive power) assessments across CTU & STU (Central & State Transmission Utility) corridors, contingency load flow for 2025–2030, and viability studies covering pumped storage and BESS (battery energy storage system) alternatives to thermal additions.

Financial models that survive lender scrutiny, sensitivity analyses on price and policy risk, and structuring advice across PPA, merchant, contracted-revenue, and tax-equity frameworks.