Excellence

Main Objective

This project aims to create an operating system for adapting factory production processes and other energy use to maximise the internal use of rooftop solar energy generation. A simple example would be to use the solar energy generated on weekends, by automatically switching on a self-contained production process.

The market: The 2 million manufacturers in Europe employ 29 million people, contribute nearly 20% to the EU gross value added and consume 26% of EU energy, just after transport and households.

The opportunity: Energy costs have been high for a number of years now, and are unlikely to fall fast. So self-sufficiency is becoming more interesting for manufacturers, with rooftop solar PV being the obvious choice. Factories put enough solar on their roof to cover all or most of their operations, and then add batteries or grid-supplied power to balance out intermittency.

This project looks at the problem in a different way - instead of adapting energy supply to demand, demand can be adjusted to generation. The aim is to use finely grained real-time energy measurements for each machine or process. This data is then used to create AI prediction models of production, which can then be compared with solar generation forecasts (which are readily available). This in turn enables factory managers to plan and control their production, or to let some of their production processes run automatically as and when there is solar.

Approach: Diversey, Metal Office and TEC Eurolab have submitted lists of their machines, appliances and energy-consuming circuits. From those lists we will pick machines/systems that have the flexibility to be switched on and off independently. These include for example the robotic 5 liter canister filling & sleeving production line at Diversey, several compressors and a fully automated powder coating production line at Metal Office, and several thermal testing systems (e.g. climatic chambers, heating baths etc.) at TEC Eurolab.

As a second step, we are already analysing how to integrate with these. GridDuck has experience of data collection via data feeds, software APIs, building communication standards (ModBus, MBus etc.) as well as by using IoT communication hardware (CT clamps, relays, sensors). For this project direct software (API, ModBus) integrations are preferred, but we have also budgeted for installing smart controllers (e.g. connected thermostat for air con), gateways (e.g. Ewon/HMS to connect to PLC controllers) and SaaS connection software (e.g. Atlas Edge from ATS Global) that can act as bridges to legacy production systems. Production systems that have to manually measured and managed can still be included, by attaching IoT sensors (e.g. CT clamps) for data capture and by providing production managers with email forecasts and immediate SMS alerts to perform an action manually (press button) or via a remote desktop application (remote connection to the PC that controls the production line).

A third step is to understand production flows & timings, customer order and the available of solar electricity, and to use AI to see how well they can be predicted. This will enable the project to then optimise the times (weekdays and weekends) when stand-alone processes or larger production lines are scheduled to take advantage of solar electricity.

The impact is that maximising the use of rooftop solar generation reduces grid-energy consumption (which has a high carbon content), and increases competitiveness. The effects can be measured daily, as two of the end users (Metal Office, TEC Eurolab) already have rooftop solar, and as all three partners are already interested in making their production greener and more cost effective. The ambition is to never drop any solar kWh into the grid, without relying (too much) on batteries, which is achievable.

Key Marketable Innovation

The key marketable innovation is to match up finely grained real-time energy measurements for each machine or process with solar generation forecasts. The production data is used to create AI prediction models of production, which can then be compared with the solar forecast to see how they align.

This in turn enables factory managers to plan and control their production, or to make some of their production processes run automatically as and when there is solar, to maximise solar self-consumption. This is easier with factory automation already in place but can also be done with automated SMS alerts for manual processes.

The improvement is to coordinate generation, storage and consumption to maximise energy security and minimise the need for grid- supplied electricity or expensive capex from buying batteries.

The innovation will be a software system communicating with production systems via software interfaces (APIs), IoT sensors and smart controllers.

Gender Balance, Demographic Diversity and Inclusivity

The Consortium agreed to aim at promoting gender diversity and inclusion within a largely male-dominated sector. 

Some key elements of the agreement:

• Recruitment of more women, including to management positions

• Teleworking to be possible during pregnancy

• Communication promoting women's careers, also in social media

• Pregnant women will have the right to a one-hour reduction in daily working hours, without any reduction in pay, after three months of the pregnancy.

• Recruiting and retaining a demographically diverse workforce and leveraging the differences between people to improve organizational outcomes

• Improving the well-being of members of minority communities through outreach and community involvement

Our project will be in line with above mentioned and these principles will be implemented during whole phase of this project.