Energy Generation Optimiser

AFRY's digital tool creates optimal loading curves
for power plant equipment

The optimal way of generating energy, i.e. loading the assets (dispatch order) changes constantly due to changing power price, changing energy demand, and even changing fuel prices.

A versatile mix of generation units, energy storages, and demand management makes defining the optimal generation plan complex. Therefore, the system operators and optimisers are struggling to reach the full potential of the energy generation mix. The operation is often done in the simplest way or as always before.

The Energy Generation Optimiser solves this problem by automatically defining the optimum asset loading. The information can then be utilised by system operators, energy traders, or/and even connected to the plant DCS.

Optimal Asset Loading

The Energy Generation Optimiser automatically defines the optimum asset loading (dispatch order). This helps users capture the financial potential of volatile power prices, changing energy demand, and varying power prices which changes the optimal way of generating energy.

Streamlined Efficiency

The tool reduces the manual work needed by the system operators and production planners and helps them to utilise the full potential of the versatile mix of generation units.

Real-Time Precision

The tool follows the actual operation and compares it to the optimised plan.

Seamless Integration

The optimised setpoints can be given to the operators or directly connected to the plant DCS.

Maximising Efficiency with the Energy Generation Optimiser

The Energy Generation Optimiser automatically creates an optimal production plan for the energy generation based on:

• Power and fuel price forecasts
• Energy demand forecasts (heat, steam, and/or electricity demand)
• The asset constraints, availability, and system initial status

The optimum production plan created by the MILP-based optimisation model gives:

• The optimised energy generation plan by unit (power, steam, heat)
• The corresponding load for boilers and heat/steam accumulators

These outputs are visualised to the operators or connected directly to the automation system, if applicable.

The process: How to implement the Energy Generation Optimiser

• Development of the optimisation model:
  • Defining required outputs and available inputs
  • Defining system constraints such as unit capacities, ramping rates, power-to-heat ratios, etc.
  • Programming and testing the model
• Data transfer:
  • Creating or defining a platform or database where the required fixed and updating input data is collected and where the output data is stored for further use
  • Establishing the MILP calculation on an applicable platform

  • Creating the visualisation for the outputs and/or the connections to the automation system

     

Porvoon Energia, Finland

Porvoon Energia in Finland operates a CHP plant and a complex heat network with heat storages. AFRY developed and implemented the Energy Generation Optimisation tool for Porvoon Energia’s generation portfolio and it was commissioned in 2021-2022.

The tool calculates the optimised generation profiles for all power plant main equipment and the information is led directly to the plant automation. The Energy Generation Optimisation tool has helped the power plant staff significantly.