District heating

Heating network optimization

Purecontrol anticipates heat demand and coordinates all network sources (biomass, UVE, gas, heat pumps, heat recovery) in real time.

The solution enables more efficient, stable, and economical operation, while reducing the carbon footprint of the heating network.

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Dynamic orchestration of heat sources

Our technology predicts demand and continuously optimizes the management of network sources:

Prediction of changes in heat demand based on weather, seasonality, and consumption profiles
Anticipation of production from different network sources (renewable energy, biomass, fossil fuels, heat pumps, etc.)
Automatic arbitration to reduce costs, stabilize the network, and limit the carbon footprint

Objective:
Meet heat demand, reduce losses and overheating, and minimize gas use

Hypervision of the heating network

Purecontrol offers comprehensive hypervision of the network: sources, distribution, efficiency, heat loss.

The platform displays the anticipated control strategy over several hours, including trade-offs between sources, demand forecasting, and identification of critical periods.

Improved network efficiency and anticipation of deviations.
Pilotage des sources de chaleur du réseau pour minimiser les pertes thermiques.

Production adjusted to network demand

Purecontrol predicts changes in heat demand by integrating weather, seasonality, calendar, and consumption profiles. This anticipation allows production to be adjusted in real time, avoiding overheating, heat loss, or unnecessary strain on equipment.
Cette anticipation permet d’adapter précisément la production en temps réel et d’éviter les surchauffes, les pertes thermiques ou les sollicitations inutiles des équipements.

Less energy waste and better network stability.

Optimal orchestration of heat sources

The solution automatically arbitrates between biomass, renewable energy, gas, or waste heat based on cost, availability, operational constraints, and carbon footprint. The network is powered by the most efficient combination at any given moment.

Cost reduction, decreased use of fossil fuels

Intelligent heat network management

Purecontrol creates a digital twin that models the behavior of the network and its sources. The solution predicts heat demand based on weather, consumption profiles, seasonality, and schedules. At the same time, it anticipates the availability and performance of sources (UVE, PAC, biomass, gas, etc.).
Production instructions are automatically adjusted every minute via PLCs to ensure an optimal balance between actual demand, costs, technical constraints, and carbon targets.
The goal is to improve network stability and reduce energy losses.pour garantir un équilibre optimal entre demande réelle, coûts d'exploitation, contraintes techniques et objectifs carbone.
Objectif : améliorer la stabilité du réseau et réduire les pertes énergétiques..
Suivi consigne charge du four orchestration reseau pilotage Purecontrol

Management of the network's heat sources (biomass, UVE, fossil fuels) based on demand, operational and environmental constraints to minimize heat loss.

From hypervision to control-command

Simplify day-to-day operations with real-time monitoring and control

Digital twin
PureConnect
PureAnalytics Energy
PurePilot
Integration of external factors
Vue prédictive
Dynamic modeling of the heating network and its sources (UVE, biomass, heat pumps, gas, heat recovery).
Hypervision platform offering real-time monitoring, customizable graphs, tailored KPIs, and alerts for multi-site supervision.
Power breakdown, real-time equipment performance monitoring without sub-meters, and automatic detection of energy performance deviations or anomalies.
Real-time control of automated systems. PurePilot applies optimized instructions from the digital twin to adjust the contribution of each source according to demand, costs, and carbon targets.
Takes into account key parameters: weather, seasonality, calendar, HP/HC rates, carbon intensity of electricity, and technical constraints specific to each source.
Predicts changes in heat demand over several time horizons (short and medium term) to adapt production, smooth out variations, and limit the use of the most carbon-intensive sources.
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Optimizing waste-to-energy plants: 3 levers for improving energy and environmental performance

Waste-to-energy plant operators have to juggle sometimes conflicting requirements: ensuring stable combustion despite heterogeneous fuel, meeting the needs of the heating network, while remaining compliant with environmental regulations. All this with limited human resources, facilities already optimized by conventional automation systems, and increasing pressure on operating costs.

Discover three concrete levers for improving their overall performance.

Read the article