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.
Decision Trees welcomes Anukta Banerjee as its new Business Development Manager. She brings over 13 years of international experience in the energy domain and is excited to support organizations in their quest for energy optimization.