All this has exposed the need for change in companies in the heating industry. What has worked traditionally for years has no chance of working in such a dynamic environment. Decisive steps towards full control of efficiency are needed to be able to think at all about profits and defend margins. And in the background, continuing restrictions on C02 emissions and rising charges are constantly an issue.
How to do this mindfully?
ConnectPoint has a ready and proven recipe for this: Smart RDM, a platform for Reporting, Diagnostics and Monitoring with modules built with district heating companies in mind. Many elements of the heat production and supply process affect efficiency, but one essential requirement must be met first - the system must work.
To ensure continuity of operation of equipment in the infrastructure, Smart RDM provides real-time detection of failures, diagnostics of operation of individual infrastructure elements, and forecasts necessary repairs. Specialised algorithms analyse data from boilers, turbines, network systems or heat substations in real-time, automatically distributing the results of these analyses to designated persons or departments. Quick information about anomalies allows for immediate reaction to maintain efficiency.
Predictive maintenance, i.e. maintaining the infrastructure in an almost failure-free state by replacing elements of equipment or the network precisely when needed, allows for maintaining appropriate economic and quality indicators. Our software is based not only on data provided by the manufacturer, e.g. repair times but also on predictive algorithms. Downtime is disadvantageous in two dimensions. The first is the dissatisfaction of end-users, and the second is the cost of repairing the failure and the lack of revenue during its removal.
When the network is operational
Only then can we address the issue of efficiency, i.e. whether it is operating optimally. Smart RDM provides analysis, reports and visualisation of processes both holistically and in detail. We can examine the performance of a section of the network, a single heat substation, or go down to the level of a specific valve. The level of accuracy depends only on the users and their needs.
A CEO can check the whole operation of a company, whereas an engineer will only be interested in the specific area he is responsible for. What is more, those responsible for settings on specific substations can simulate the behaviour of the equipment at given parameters thanks to the so-called Digital Twin. A digital copy of a given system component allows verification and preparation of optimal settings before they are applied to the physical equipment. Here again, economic parameters come into play, which can be maintained at an optimal level thanks to a specialised network behaviour analysis.
How can this be predicted?
The production and consumption of heat is the last element of the system that we will briefly describe in this article, but not the last one that Smart RDM analyses. Proper planning of production is crucial due to the high costs of the production process. To plan production well, consumption must be adequately forecasted.
This is where the prediction module comes in. It uses a statistical algorithm based on historical data, calculated under the ordinance of the Polish Minister of Climate of 23 April 2020 on detailed rules of shaping and calculating tariffs and settlements for heat supply, supplemented with a forecasting model using machine learning algorithms.
Planning cannot be carried out correctly without considering production capacity, generation unit configuration based on efficiency characteristics and availability with the inclusion of start-up/shutdown times and costs within a 72h horizon. We have included all these elements in the Smart RDM platform, giving our customers a complete solution that becomes the reporting, diagnostic and monitoring centre for the district heating company.
We provide much more as part of the solution - for more information, please read our customer stories and visit the Smart RDM website.