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Joint Operation System


Due to recent turns of events such as electricity liberalization and deregulation, factory management has entered a new competitive era, and a factory with steam power facilities is now strongly required to operate in a more economically efficient way than ever. Mitsubishi Power JOINT OPERATION SYSTEM (Mitsubishi Power JOS) supports this trend in factory management.
In private power plants or factories with multiple boilers and turbines, in order for each boiler and turbine to operate with most economical steam and power generation, an Mitsubishi Power JOS performs real-time optimization calculations, displays the results, and controls each boiler and turbine accordingly.

In paper factories, iron foundries, and the like, in some cases, the boilers, turbines, and air pipes in are constructed in a complex way, and various types of fuels such as coal, fuel oil, and surplus blast-furnace gas must be burned in an efficient way. In addition, various requests regarding power demand, electricity trading, steam demand, and others have to be satisfied.
At any moment, the most economical operation pattern needs to be found based on overall evaluation of all those conditions. An Mitsubishi Power JOS formulates those conditions as a multivariable equation, and solves it in real time.
This is enabled by the following three functions:

  1. Economical operation solver for an n-th degree equation as a conditional non-linear optimization problem
  2. State estimation function as a countermeasure against detection error; Automatic update function for operation characteristics of each piece of equipment to compensate for changes in characteristics over time.
  3. A function to send the values of control variables to a control system such as a distributed control system (DCS) or to a direct control panel, based on the calculation result from a JOS.

Based on the vast experience as a leading plant manufacturer, an Mitsubishi Power JOS offers optimal operation of factory steam power and meets our customers' needs by constructing a flexible and distributed PC and server system using the latest software technology.

System Configuration

System configuration of an Mitsubishi Power JOS

System configuration of an Mitsubishi Power JOS

An Mitsubishi Power JOS is the latest Windows-based PC that comes with realtime operation software with Mitsubishi Power JOS functions. You can operate an Mitsubishi Power JOS on an ergonomics-based operator station (OPS). The operation is based on general-purpose package software.
Functions are distributed to a JOS and a control system. Some functions need to be handled solely by the control system, and others need to be shared between the two. Functions are distributed so that, even if the Mitsubishi Power JOS PC fails, stable control functions over all units can be maintained with backup from the control unit.


  • On-line realtime optimization calculation
    The optimal values of control variables are automatically calculated in accordance with changes in power and steam demand over time and are sent to operators as target values.
  • Off-line optimization calculation
    You can decide the number of operating boilers and turbines for each year, month, and week and create an optimal operation plan based on the production plan and energy demand in the factory. An estimate of the benefit of using a JOS can be calculated from the actual operation data and the design documents of equipment in real time or offline.
  • Calculation of the operation characteristics models for equipment
    The characteristics of boilers and turbines are calculated using n-th order polynomials in consideration of non-linearity regarding the amount of fuel, factory air supply, and power generation.
  • Calculation for the economical operation solver model
    The input/output relationships in both the power and steam systems are formulated as equality conditions. The operational constraints are formulated as inequality conditions. The total power generation cost is formulated as a solution of a non-linear optimization problem while the unit price of purchased power for each time slot and the unit price of fuel are formulated as inputs to the optimization problem.
  • Calculation for automatic update of non-linear models using the learning function
    The characteristics of each boiler and turbine change slightly over time. This change cannot be neglected if only a one to two percent margin is allowed for optimal operation. Based on the static characteristics and design data, the change of characteristics over time can be automatically calculated and adjusted using actual operation data.
  • Setup for an electricity rate pattern/Calculation of input power calendar setting
    Electricity rates depend on time slots in each day. An optimal operation pattern is expressed as a combination of those time slots. The economical operation solver model calculates an optimal operation pattern for each day from all possible combinations.
  • Calculation for state estimation
    A differential pressure type flow meter is used to measure steam (and other) flow rates. The meter has a larger error when the flow rate is smaller.
    You can increase the precision by using state estimation in consideration of the mass balance and heat balance of the plant.
  • Calculation for demand control function
    In order to suppress the purchased power within the contract demand, the power consumption at the end of each demand period is predicted. If there is not much margin for the generator output in the predefined order, selected feeders are shut down with advance notices.
  • Reporting service in an iron factory
    In order to follow the power demand from both the energy management center in the factory and the load dispatching center of the electric power company, this function reports the data necessary for optimal operation to the sections relevant to operation management. This function also manages demand.

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