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A major U.S. chemical production plant can cogenerate over 50 MW of power, offering a major savings opportunity through optimization of the electricity to steam balance. SmartCloud is implementing a CHP Optimization solution in three phases to speed up delivery of value.

Customer Success

Technologies:

  • AI modeling: Represent dynamics of steam and production systems by using AI techniques in combination with first-principle engineering models to model relationships of facility equipment and processes.

  • AI reasoning and optimization:  Employ neural networks and other machine learning techniques to forecast steam demand, in addition to using genetic algorithms, linear programming, and other techniques to optimize overall electricity-to-steam balances.

  • Simulations: Assess various steam-to-electricity balance scenarios using AI and first-principle models to automatically run simulations.

  • Logic flow orchestration:  Optimize cogeneration control settings in real time by orchestrating data collection, models and simulations, and forecasts. Communicate decisions as guidance to operators (open-loop control) or commands to the control system for automatic actions (closed-loop control). 

  • Three-phase deployments: Lower project risks and speed up delivery of value via agile solution development over three situational management phases:

    • 1) Situational Awareness to fuse and visualize disparate, siloed data sources;

    • 2) Situational Intelligence for proactive, predictive alerts to problems that can adversely impact optimization decisions; and

    • 3) Situational Control for automating optimization of power-to-steam balances in real time.    

  • Cloud / SaaS: Reduce overall solution costs by deploying in the cloud using a software-as-a-service model. 

 

Optimally balance cogenerated electricity and steam across a wide range of operating conditions to cut costs and improve overall performance.  

Results:
Solution: 

Use Industrial AI technologies to model, optimize, simulate and control cogeneration settings in real time.

Use Case Problem:

Inefficiently using energy generated by CHP reduces profits and competitiveness.

Many industrial facilities use Combined Heat and Power or CHP, also known as cogeneration, to simultaneously supply electric power and steam for production. Striking an optimal balance in real time between cogenerated power and steam, production requirements, and purchased grid power can cut operational costs substantially.  But reaching optimal decisions requires timely analysis of many constantly changing factors such as electricity prices, fuel costs, energy storage options, dynamic behavior of connected steam and production systems, steam demand forecasts, steam header pressures, production schedules, equipment health, and weather.

 

Optimized Combined Heat and Power (CHP)

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