Energy Management Software Development

Smart meter integration via DLMS/COSEM, MQTT broker subscriptions, and utility API connections. Industrial equipment telemetry integration via ISO 15765/J1939 CAN bus data streams and Modbus TCP/RTU for legacy meters and sub-meters. BACnet/IP integration for building management systems (BMS) and HVAC equipment that report energy data through their building automation layer rather than through a dedicated energy meter. This covers the majority of commercial and industrial meter protocols in a single platform without requiring protocol-specific gateways at each site.

Sub-metering at cost centre, production line, or building level provides the granularity to identify which processes or tenants are driving consumption increases, not just the total site figure. Live dashboards display consumption by site, asset, and time period with comparison against baseline (calculated per IPMVP methodology) and budget. Alerts for consumption anomalies or threshold breaches fire within minutes of the interval data arriving rather than waiting for a daily report. Export to billing and ERP systems. A single operational view that replaces the manual process of pulling interval data from each meter portal and assembling it in a spreadsheet every month.

ML-based load forecasting models trained on your historical interval meter data, production schedules, and weather data from local meteorological APIs. Energy market data from the EIA API (US) or Epex Spot (European power markets) is incorporated where market pricing drives operational decisions such as demand response participation or battery dispatch scheduling. Forecasts run at 15-minute, hourly, and daily granularity for each site or aggregate portfolio, with confidence intervals displayed alongside the point forecast so operations teams can see not just the expected peak but the probability-weighted range.

Peak demand alerts are issued hours before forecast demand is projected to exceed your demand charge threshold, giving operations the lead time to implement load reduction. Demand response integration with OpenADR 2.0b protocol allows the system to receive automated demand response event signals from your utility or aggregator and trigger pre-configured load curtailment sequences without manual intervention. Forecast accuracy is tracked as mean absolute percentage error (MAPE) per site, and models are automatically retrained as consumption patterns shift with seasonal changes, production schedule changes, or new equipment additions.

Automated load shedding sequences triggered by demand forecasts, real-time demand signals, or OpenADR 2.0b event notifications from a utility virtual top node (VTN). The OpenADR 2.0b protocol is the industry standard for automated demand response signalling used by utilities across North America, Europe, and Australia -- building it into the platform rather than relying on manual staff response is the difference between a demand response capability and a demand response aspiration.

EV charging optimisation shifts charging schedules to off-peak windows using published tariff time-of-use periods and real-time demand conditions, without requiring manual intervention from the fleet manager. HVAC setpoint control sends BACnet/IP commands to building management systems to pre-cool or pre-heat a building ahead of a demand event, maintaining comfort within defined tolerance limits. Curtailment priority rules are configurable per site -- you define which loads can be shed, in what order, and what the minimum duration before they can be restored. The platform records every demand event -- the trigger, the loads curtailed, the demand avoided, and the cost avoidance calculated at your demand charge rate -- so demand response participation is fully auditable.

Interval data analysis for tariff comparison and procurement decision support, structured around the ANSI/ASHRAE Standard 211 energy audit protocol for commercial buildings and ISO 50001 energy baseline methodology for industrial sites. Time-of-use tariff modelling applies your actual 15-minute interval consumption data against alternative tariff structures so the analysis reflects how each tariff would actually have billed you, not an estimate based on monthly totals. Network charge analysis breaks down demand charges, capacity charges, and ancillary service components so the full cost of supply is visible, not just the energy commodity cost.

M&V (Measurement and Verification) calculations follow IPMVP (International Performance Measurement and Verification Protocol) Options A through D to quantify the energy savings from efficiency projects against an adjusted baseline. Option A isolates the variable being measured with stipulated values for the rest. Option C uses whole-facility metering with regression modelling. The M&V option is selected per project based on what is being measured and what level of certainty the project owner or financier requires. Cost avoidance calculations separate actual cost reductions from counterfactual baseline projections, which is the standard required by green financing covenants and sustainability report disclosures.

Scope 1, 2, and 3 emissions tracking calculated from energy consumption data using the GHG Protocol Corporate Standard accounting methodology. Scope 1 covers direct combustion of natural gas, diesel, and LPG at your facilities. Scope 2 covers purchased electricity, calculated using both location-based and market-based methods as required under the GHG Protocol Scope 2 Guidance. Scope 3 Category 3 (energy-related activities not in Scope 1 or 2) and Category 11 (use of sold products) are calculated where the underlying consumption data is available in the platform.

Carbon intensity is calculated using time-varying grid emission factors by region and time period -- marginal emission factors for demand response decisions, average emission factors for regulatory reporting -- sourced from national emissions registries. ISO 50001 energy management system reporting is built in as a standard report template, covering the energy review, energy performance indicators (EnPIs), energy baselines, and action plan progress required for certification audits. Automated report assembly from live metered data rather than manual export and calculation. An audit trail links every reported emissions figure back to the interval meter reads it was derived from, which is the traceability requirement for both the GHG Protocol and ISO 50001 clause 9.1.

Health monitoring for transformers, generators, renewable assets, motors, compressors, and other large energy-consuming equipment. Telemetry is ingested via Modbus TCP/RTU for industrial equipment, BACnet/IP for BMS-connected assets, and ISO 15765/J1939 CAN bus data for mobile and on-site generation equipment. This covers the communication protocols used by the vast majority of industrial monitoring points without requiring separate protocol gateways for each equipment type.

Fault detection uses consumption pattern analysis and operational parameter thresholds -- a motor drawing more current than its baseline for the same output load is flagged before it trips, not after. Asset-level energy intensity tracking compares each asset's energy per unit of output over time, identifying degrading equipment before the degradation becomes visible in the site total. A compressor that was operating at 0.12 kWh per cubic metre six months ago but is now at 0.19 kWh per cubic metre is identified as a maintenance priority before it fails. Integration with your CMMS (Computerised Maintenance Management System) raises maintenance work orders based on energy performance indicator thresholds, connecting the energy data to the maintenance workflow rather than leaving them as separate visibility tools.