All current modules and features in Aurora by Sigholm have been developed based on our customers’ needs and the constant, rapid changes of the market. We don’t know what the future holds, but we are ready to add whatever is needed to optimize the energy systems of tomorrow.
How do we operate our energy system in the most optimal way going forward?
Production optimization based on heat load forecasts and availability information. Presents a production plan (standard 7 days ahead) in graphical and tabular views for users. The production planning supports heat planning, day-ahead planning, and intraday trading.
How did it go? What potential did we miss? What can we learn from this to develop our business and our strategies?
Follow-up and optimization of different scenarios. Presentation of scenarios and production results together with KPIs.
What are our best predictions about what is needed in the system?
Demand forecasts based on weather data, historical demand data, behavioural data and input from the latest measurement data.
ChatGPT said: What is the current status and condition of the system?
Gain a clear overview of current conditions, such as availabilities and constraints that prevent the system from reaching its full potential.
When do I need updated information? By default, automatic optimizations are scheduled to run every hour to regularly generate updated plans and follow-ups, in connection with other automated events and changing conditions. Optimizations can also be started manually.
An environment to explore, experiment, and test different scenarios and comparisons. Standard optimization period of 7 days with a selected start date.
What happened during the shift? Collaboration support between shifts. Reports are created based on the shift schedule and include information about plans, results, availability, and input fields for operator comments that are passed on to the next shift.
What do we pay each other? For partners within an energy system collaboration that have a settlement agreement, this can be automated through specific optimizations and calculations. Make the terms and limitations in different scenarios transparent to all parties involved in the collaboration.
What should we pay for surplus heat? Support for dynamic business models with heat collaborations between, for example, smaller industries, grocery stores, and other actors that feed surplus heat from their processes into the network. Marginal cost optimizations can help create a more dynamic spot price for surplus heat.
How much fuel do we need? 30-day scenarios for production planning and fuel planning, with presentation of fuel quantities and costs. Expected inventory consumption based on the production plan. Option to add repurchase prices for fuels.
How can the power grid and customers contribute to creating flexibility? Load balancing as part of the optimization for customers who have hardware and software for such operations. Forecasting and modeling of the distribution network should be included in the optimizations.
How should our energy system act on the electricity market? Possibility to further automate day-ahead trading with, for example, suggested electricity bids based on production optimization, while still allowing manual bid editing. API support for sending and collecting bids and plans from trading partners/systems. Production optimization can be restricted to follow the purchased electricity plan.
Book a demo and gain insights into how you can work in a more data-driven way.
