Yokogawa Energy Management Solutions

Succesfull EMS Applications in Europe

AbstractSecond only to raw materials costs, energy is the leading cost pressure currently affecting manufacturer’s performance. Under the current market environment, a better energy management in industrial facilities can make the difference between profit and losses. Energy Real Time Optimization, ERTO has been proven as an effective work process to capture additional energy savings. On top of the traditional focus on reliability, the addition of the optimization culture to the energy operations is helping refineries and petrochemicals to improve company margins. Modern industrial facilities operate complex and inter-related utilities systems. In a de- regulated market the utilities tradeoff between producing vs. importing, and consuming vs. exporting (steam, electricity, fuels), along with the degrees of freedom of the energy system itself, an energy real-time optimizer finds the optimal way to operate the entire energy system at minimum cost while respecting the environmental, contractual and operational constraints.

In one French refinery a set of manual operating recommendations given by the optimizer during an operational Shift have been:

Perform a few turbine/motors pump swaps. Change the fuels to the boilers (i.e., Fuel Gas and Fuel Oil)

Obtained benefits can be summarized as follows: Almost 1 tons per hour less Fuel Oil consumed Approx. 7 tons per hour less high pressure steam produced Approx. 2 tons per hour less CO2 emitted Approx. 200 kW more electricity imported (which was the lowest cost

energy available)

In one Spanish refinery with an olefins Unit, Over that period, in 2003, 4% of the energy bill of the Site was reduced, with estimated savings of more than 2 million €/year.

In a Dutch refinery the EMS online optimization is running in closed loop. Typical optimization handles include letdowns, load boilers steam flow, gas turbine generators/steam turbine generators power, natural gas intake, gas turbine heat recovery, steam generators duct firing, extraction of dual outlet turbines, de-aerator pressure, motor/turbine switches, etc. Typical constraints are the steam balances at each pressure level, boiler firing capacities, fuel network constraints, refinery emissions (SO2, NOx, etc.) and contract constraints (for both fuel and electric power sell/purchase contracts).

Benefits are reported to come from the load allocation optimization between boilers, optimized extraction/condensing ratio of the dual outlet turbines, optimized mix of discretionary fuel sales/purchase, optimized gas turbine power as a function of fuel and electricity purchase contract complexities (trade-off between fuel contract verses electricity contract penalties).

In one Italian refinery, a detailed model of the steam, fuels, electric, boiler feed water and condensates systems was built, contemplating all the real constraints and degrees of freedom for their operation. Such a model is continually fed and validated with live data. A complete model of the overall energy system was built. The model included the whole fuel, steam, boiler feed water, condensate and electrical systems. SARAS operates an integrated gasification combined cycle (IGCC) power station, which is integrated with the refinery. The gasification feed stream is tar (heavy residue from visbreaker unit), and the plant produces, along with electric power, hydrogen and medium and low pressure steam that are used by the refinery. The complex (refinery plus IGCC) is optimized as a whole, minimizing the total operating cost. The three steam pressure levels, as well as all the utilities and process units, were modeled with a high level of detail, including all the consumers and suppliers to the respective steam, boiler feed water and condensate headers. The electricity contracts were also modeled in detail. The fuel system was also modeled, taking into account all its constraints and degrees of freedom, as it is involved with the steam and power generation equipment.

The objective function that the software optimizes is the total operating cost of the system, which is: Total operating cost = Total fuel cost + Total electric cost + Σ Other costs

Approximately 60 optimization variables have been selected and approximately 25 constraints are included in the optimization problem. As a result, a better coordination between IGCC and refinery has been achieved. Steam savings, steam letdown and condensing reduction resulting in one energy cost reduction estimated about 4% of the total energy cost. Another 3% has been achieved by improved fuels management. Finally, about 1% cost saving has been obtained by optimizing Electricity system management based on market/contract prices.

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