Value

Try and test your new power plant in real conditions before you spend the money on building it!

       Strategy

Coordinate your marketing tactics with business strategy!

       Profit

Use your existing power and process plant in the most efficient way and improve your profit!

       Economy

Don't make expensive experiments with your business.

Use your existing power and process plant in the most efficient way and improve your profit!

 

Mathematical models of existing plants are always unique and tailor made for the existing plant and these are some of examples:

 

Mathematical model of the industrial cogeneration power plant (PDF)

 

Optimisation model for managing operating conditions of the industrial cogeneration power plant is the model of the existing real industrial cogeneration power plant with two steam boilers for production of high pressure steam and two steam boilers for production of middle pressure steam, one back pressure steam turbine without extructions and one back pressure steam turbine with one controlled extruction.

 

 

Thermal energy is produced on up to three energy levels (high, medium and low pressure steam) and electricity for the purpose of industrial needs can be produced in the plant and also bought from electricity system operator and the plant can also operate directly for the needs of customer, separated from the electricity network. The model calculates technical parametres of the power plant for satisfying market needs (HP steam, MP steam, LP steam and electricity) and predicts expected income, costs and profit.

Operating conditions can be optimized in order to maximize energy efficiency or to maximize the profit of the plant.

 

Simulation mathematical model of the refinery (PDF)

 

Simulation model for managing the whole refinery is the model which consists of three basic parts. The first part is the model in which current capacities of refinery plants sre adjusted, in the second part commercial parametres are set and the third one is used for what-if analyses of business result of the refinery for various business cases.

 

Input data of the process model are calacities of refinery units, production level and losses and output data are quantities of products and percentages of high and low margin products.

 

 

 

 

 

 

 

 

Input data of the model of the market are crude oil price, production level, production costs, product's market prices and minimum and maximum quantities and outlet parametres are total production quantities, stocks, income, costs and profit.

 

 

 

 

 

 

 

 

In the end, for the purpose of what-if analyses, input data are the price of crude oil and production level and the output data are production quantities, stock levels, market conditions, profit forecast and simulation of business result for 8 different production levels.