Industrial energy balance optimization software

Module 1: Monitoring & reporting   |   Module 2: Forecasting & planning Module 3: Energy optimization

Utilize energy price volatility and process flexibility for optimal production scenarios

Holistic energy supply & demand optimization depending on your business objectives:

  • minimize the total energy cost, reduce emission levels or maximize the total profit of the operations
  • leverage process flexibility for peak shaving, load shedding, shifting production when energy is cheaper
  • leverage flexibility in energy sources to enable effective energy procurement strategy

Supports multiple energy
types and optimization
scenarios

Optimizes energy
generation,
procurement, trading

Shifts consumption
to off-peak hours

Provides decision support
& APC set points for
optimal startup / operation

In contrast to energy efficiency strategies, which aim to produce the same using less energy, demand-side response focuses on profitable shifting of the load in time

Pulp mill

  • Situation: Highly volatile electricity spot price. High energy costs with significant impact on operations (two board machines, creating 520,000 t/year, refined mechanical pulp plant, 10 MW power, feeds board machines; 500 m3 / 130 000 gal storage tank between RMP plant and board machines)
  • Solution: Optimal production timing minimizes the electricity costs by optimizing the refined mechanical pulp (RMP) operation according to electricity spot price. Accurate energy planning and power consumption forecast for electricity purchase. 14.5% total savings over two sample periods (when optimization was possible and results were utilized by operators). The system has been extended to the biogas power plant. Learn more

Industrial steam and power plants

  • Situation: In the industrial boilers, not only is the steam needed at different, very specific pressures and temperatures, but its consumption rate is also highly variable due to the variability of the process conditions, trips and/or starts of steam consumers, etc. Steam network stability and reliable power output are difficult to attain. Further complexity is added by energy market variables, prices, local rules for energy markets and when distributing excess heat to residential and commercial heating networks..
  • Solution: ABB's Advanced Process Control solution takes advantage of asset flexibility to achieve 3 % to 5% savings in steam costs with ROI below 1 year. Industrial users improve steam network stability, with enough steam at required parameters and ensure more reliable power output - as much as economically optimal. Learn more

Cement plant

  • Situation: Ad hoc reactive schedules result in higher energy costs. Lack of predictive consideration of equipment availability and insufficient anticipation of power caps. Not leveraging opportunities from electrical grid varying prices and power availability
  • Solution: Optimal production schedule minimizes energy costs. Acquiring on-line information about energy tariffs, equipment availability, product demand and silo inventory. Schedule is calculated to satisfy demands while minimizing the costs. As a result, the company has realized savings in energy bills with more consistent and systematic planning procedures

Steel plant

  • Situation: Scheduling production in a steel melt shop is not easy, partly due to the extreme processing and material temperatures. For example, each production delay leads to cooling and later a reheating need. Therefore, there is a strong demand in the industry for automatic production schedule optimization. The scientific challenge arises in simultaneously optimizing the production schedule and the electricity purchase strategy.
  • Solution: The production scheduler can automatically and optimally create a new schedule, or update an existing one to optimize energy cost - leveraging flexibilities associated with the batch-oriented nature of steel process. The system includes all necessary information: external day-ahead electricity market,processing, transportation, setup and cleanup times, maintenance plans, and availability of equipment. Learn more

Steel plant

  • Situation: Annual capacity 4,5 million tons of steel, complex distribution networks for electricity, steam, by-product gases and imported fuels make up 20% of production cost. Energy-rich (~ 700 – 4300 Kcal/Nm3) byproduct gases are generated in large volumes during iron- and steel-making processes. Byproduct gases are consumed  by processes and also to generate power in captive power plants. Momentary excess of byproduct gas results in flaring of gases and hence economic loss. Operation constraints, unplanned scenarios result in suboptimal performance.
  • Solution: Energy management with integrated by-product gas network assists gas dispatching, calculates optimal power production based on real-time data and adapted to power marke. It optimizes energy consumption and secures energy availability considering steam yield, consumption of by-product gases, energy purchase and production including site power plants and turbines. Results: 10% less flaring of gases thanks to data and optimization model, 15% accuracy improvement of electricity procurement forecasts, 15 k€ per month saved (yearly average)

Balancing time-varying energy consumption with supply resources allows to minimize the total energy cost or to maximize the total profit of the operation over a specified time range.

Based on the predicted energy consumption schedules, the Energy Optimization module of the ABB Ability™ Energy Management System for industries software can:

  • calculate the optimum use of supply resources to meet the predicted consumption at minimum total cost
  • optimize running schedules for selected consumers based on minimum energy cost and given restrictions
  • utilize a real-time LP / MILP optimization environment and economic flow network, in which the energy process is divided into logical sub-processes which are connected to each other through a flow network
  • optimize the complete energy flow network in real-time when any of the input parameters change, allowing the facility operators and management to maintain the most cost-effective operating mode in changing production conditions.

In the balancing process, the schedules are calculated and agreed daily for the next day. In strategic planning and budgeting, the schedules may extend over several months, or even years, while during real-time monitoring they may cover only the next few minutes or hours.

For a corporate customer multiple facilities can be integrated to provide a company-wide solution and to allow comparisons, benchmarking and sharing best practices between the production facilities.

Popular use cases

Balancing model
Real-time balance monitoring
Tie-line power monitoring / demand by contract

ABB Ability™ EnMS for industries balances time-varying energy consumption with supply resources. Your energy system is modeled as an Economic Flow Network. The Economic Flow Network considers the transfer and conversion of utilities such as fuel to steam, steam to electric power, fuel to CO2, etc. Depending on your objectives, energy resources are scheduled / dispatched to minimize the total energy cost or to maximize the total profit of the operation over a specified time range.

This configurable model is populated with data such as prices, volumes, validity times and other relevant information. The data may be either manual entered or acquired automatically, where available.

Benefits:

  • Employ optimal power resources
  • Lower power price by sending load schedules to power supplier
  • Avoid expensive power by demand scheduling
  • Lower balancing power and cost
  • Lower demand charges and penalty fees
  • Higher energy efficiency and reduced carbon footprint

ABB Ability™ EnMS for industries can be used during the real-time operating phase to monitor the execution of power schedules. With real-time monitoring, deviations or unexpected events are detected and reported to help you minimize their costs.

The load planning module automatically recalculates the load schedule based on changes in process measurements, production plans or user inputs. If an imbalance between predicted power consumption and planned supply is detected, the deviation from plan may be balanced through additional power trading.

The tie-line power monitoring / (monthly) electricity demand by contract predicts total utility consumption within the current billing period by integrating and extrapolating the flow in the tie-line. If the predicted volume exceeds pre-set or calculated alarm limits, alarms can be generated enabling the operator to take action to limit the deviation.
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