PCI GenTrader® has powerful and flexible forecasting tools for energy generation and transmission professionals to model complex portfolios of power and fuel resources, including generators, contracts, options, and ancillary services. GenTrader® ensures consistent and accurate forecasting and evaluation by assessing an array of asset positions over any time frame – all within the same software tool – so power suppliers can determine short to long-term portfolio viability and profitability. 

GenTrader® maximizes portfolio profits by minimizing costs. Some applications include:

  • Daily operational planning
  • Fuel burn forecasting
  • Asset acquisition
  • Post-analytics
  • Transaction structuring
  • Assessing emissions (and emissions compliance) impacts
  • Valuing the impact of potential plant upgrades
  • Determining the relative economics of generation assets in varying LMP (locational marginal pricing) scenarios


Traders, asset/portfolio managers, planners, and risk analysts can use GenTrader® software to run multiple valuation and forecast studies including:

  • Post-analyzing operational efficiency, transaction/outage costing, and more
  • Co-optimizing energy and ancillary service (AS) positions and opportunities
  • Using case comparisons to see detailed differences between designated studies
  • Defining purchase/sale market structures
    • Inputting “bid” and “ask” prices to define a commodity market
  • Performing Stochastic analyses to:
    • Simulate the value and risk of a position or a portfolio
    • Generate a probabilistic distribution of profit and loss for each position, as well as the entire portfolio
    • Construct tornado diagrams showing the contribution of each risk driver to overall portfolio risk
    • Value generation assets as options based on a user-defined price model
    • Assess the impact of market price volatility, unit forced outages, and load uncertainties
  • Developing market price scenarios to analyze how a portfolio’s profit and loss would behave under varying market conditions.
  • Calculating transaction pricing (e.g., break-even cost) for proposed purchases/sales.
  • Configuring and creating “block prices” for a stack of generic purchases/sales.