Gas Industry

Close to the market and stochastic valuation

in the rapidly developing gas markets, close to the market and stochastic valuation of natural gas storages, contracts and procurement portfolios becomes more and more important. With stochastic optimization, uncertainties in future gas market and demand evolutions can be modelled. Therewith, close to market valuations of flexible assets as well as more efficient decision making in gas portfolio operation is achieved. Amongst others, we offer solutions in the following areas:

Gas Procurement Portfolio Optimization

  • Decision support for structured gas procurement in day ahead and forward gas markets
  • Flexibility to cover retail load profiles even in partially illiquid gas markets is ensured by flexible gas supply contracts or gas storages
  • Modelling of the full complexity of procurement portfolios: several oil and gas market indexed supply contracts, gas storages, transport restrictions, multiple market areas, different retail loads etc.
  • Our Solution: Optimization with stochastic market prices and retail loads, risk-adjusted management of open positions in natural gas forward markets

Valuation of Gas Storages and Flexible Gas Supply Contracts

  • Intrinsic and extrinsic valuation of gas storages and flexible gas supply contracts with highly complex volume restrictions and price formulae
  • Modelling and scenario generation for day ahead and forward prices on natural gas markets
  • Estimation of volatility, mean reversion and corrlelation parameters based on historic price evolutions
  • Modelling of real sales and operations of gas storages and flexible gas contracts: joint modelling of day ahead and forward market operations
  • Dynamic hedging: riskless profits by restructuring forward market portfolios are modelled
  • Our Solution: Joint optimization of forward and spot market operations in all paths of the scenario tree in stochastic optimization

Your advantages of stochastic optimization

Often an intrinsic valuation could noch represent the reality good enough. Therefore, use is made of stochastic optimization, which usually deliver significantly better results. The following components are simulated stochastically:

  • Stochastic Simulation of Day-Ahead-Markets
  • Scenarios of Forward-Products, among others to simulate a dynamic hedging
  • Stochastic Simulation of load profiles
  • Correlation between markets are taken into account
  • Joint optimization of all portfolio components

More detailed information about our modeling can be found in the brochure.