Smart Energy Solutions

An energy management system that cuts use and emissions and supports greener operations

Solution Overview

The smart energy solution uses IoT, big data, and artificial intelligence to monitor, analyze, and optimize energy. Live readings, analysis models, and automated control help enterprises and cities get more from each unit of energy and spend less on it.

30% less energy

Smarter use of the energy already on site

25% lower cost

Less waste and a lighter operating bill

45% higher efficiency

Scheduling and load balancing done by the system

Smart energy system architecture

Core Functions

Energy management across monitoring, savings, generation, and the grid

Energy Monitoring

Watch electricity, gas, water, and other energy use as it happens, break the data down from several angles, and send an alert when a reading looks wrong.

  • Live energy monitoring
  • One view across energy types
  • Intelligent alerts
  • Energy-efficiency reports

Intelligent Energy Saving

AI adjusts equipment settings so the site runs at a better energy-efficiency ratio.

  • Intelligent scheduling
  • Load forecasting
  • Automatic equipment control
  • Energy-efficiency review and tuning

New Energy Management

Monitor solar and wind generation, run the storage system, and improve how new energy is connected to the grid.

  • New-energy generation monitoring
  • Energy storage management
  • Grid connection and dispatch
  • Generation efficiency analysis

Smart Grid Management

Watch how the grid is running, balance supply and demand, diagnose faults and restore service automatically, and keep the grid secure.

  • Grid status monitoring
  • Supply and demand balancing
  • Automatic fault diagnosis
  • Power quality management

Use Cases

Parks, buildings, cities, and residential communities

Industrial Parks

Park-wide energy management and dispatch

About This Scenario

The industrial-park energy platform gives the management committee and tenant companies one energy service. It brings together electricity, gas, heat, and water so supply, delivery, and use can be watched end to end. Big-data analysis of how the park uses energy produces diagnostics and saving advice for each company. Demand response shifts load off grid peaks so the park's overall power bill falls. Distributed solar and storage are dispatched together, more new energy is used on site, and the park can move toward lower-carbon industry.

Pain Points

Energy use differs widely: Companies in the park use energy in different mixes and at different levels, so one management and assessment standard is hard to apply
High electricity cost: When everyone draws power at once, peak load, demand charges, and the unit price all rise
New energy goes unused: Distributed solar in the park is uneven, and without storage or dispatch, surplus generation is curtailed
Data stays in silos: Each company's energy data sits apart, so the management committee cannot see park-wide consumption

Technical Advantages

One view of every company

Energy data from every company is collected, shown on one screen, and compared side by side

Demand response

Stagger company load, cut the park's peak demand, and save 30% on demand charges

New-energy dispatch

Forecast solar output, schedule storage charge and discharge, and raise on-site use of new energy to 85%

Energy-efficiency benchmarking

Set park benchmarks, publish rankings on a regular cycle, and give companies a reason to save

Commercial Buildings

Intelligent control that cuts energy use in building plant

About This Scenario

For offices, shopping centers, and similar buildings, the system watches and controls HVAC, lighting, elevators, and water services from one place. AI uses the weather forecast, indoor and outdoor temperature and humidity, and how many people are in the space to set the air conditioning so comfort holds and energy use falls. Lighting follows the schedule, daylight, and occupancy sensors, and comes on only when it is needed. Elevator group control cuts empty trips and waiting. Predictive maintenance flags faults before they stop equipment. Sub-metering bills each tenant on their own use, which gives them a reason to save.

Pain Points

Air conditioning dominates the bill: HVAC is more than 50% of building energy use. The saving is real, and the settings are hard to get right by hand.
Lighting stays on: Public areas stay lit all year, including rooms with nobody in them.
Plant runs flat out: Equipment sits at full load for long stretches, efficiency is poor, and maintenance costs stay high.
Tenants have no reason to save: Power is split by floor area, so using less does not change the bill.

Technical Advantages

Smarter air conditioning

AI sets pre-cooling, pre-heating, and variable-speed control, and cuts HVAC energy by more than 30%

Lighting that follows occupancy

Occupancy and light sensors dim the fixtures to what the space needs, and lighting power falls by 40%

Predictive maintenance

The system watches equipment condition, AI estimates when a fault will hit, and earlier maintenance cuts losses by 60%

A meter for each tenant

Each tenant has their own meter and live usage, so saving energy shows up on their bill

Smart City

City energy management and lower use in municipal facilities

About This Scenario

The city energy platform pulls together supply and use for electricity, gas, heat, and water so city managers can decide from a full picture. Street lights, traffic signals, and bus stops are controlled for lower energy use. Street lights change brightness with sunrise and sunset, weather, and traffic and footfall, and they drop to a lower output late at night. EV charging is scheduled so drivers charge in the valley and the grid load flattens. City energy data forecasts demand, tightens the supply plan, and supports greener urban operations.

Pain Points

Street lights run hard all night: They stay at high output even when the street is empty after midnight
Chargers sit in the wrong places: Queues form at peak and stalls sit idle in the valley
Energy data is split: Each utility keeps its own figures, so the city cannot see supply and demand together
Emergency supply is late: In extreme weather and other shocks, energy reserves are not moved in time and city operations suffer

Technical Advantages

Street-light control

Brightness follows weather, time, and traffic. Each lamp can be set on its own, and energy use falls by 50%

EV charger scheduling

Price signals move charging off peak, load forecasts guide where chargers go, and utilization rises by 30%

City energy view

Several energy streams sit on one picture of how energy moves through the city, so decisions rest on the data

Emergency supply plan

Forecast demand in extreme weather, move reserves ahead of the event, and keep the city running

Smart Community

Energy management for the estate and for how residents use power

About This Scenario

The community energy system serves both the property manager and residents. It watches and trims use in shared lighting, elevators, pumps, and chargers so operating cost falls. Distributed solar and storage can be connected: residents use what they generate, export the surplus, or join power trading. A home energy terminal shows live usage, bills, and saving tips. The community microgrid uses new energy where it is produced, raises self-sufficiency, and gives the estate a lower-carbon model to point to.

Pain Points

Shared facilities cost too much: Public plant uses a lot of energy, fees are hard to collect, and the property company is under pressure
Rooftop solar pays back slowly: Output is uneven, the export tariff is low, and the payback stretches out
Households cannot see their use: Residents do not know what drives the bill, or what to change
EV charging is scarce: There are too few chargers, queues are long, and the price is high

Technical Advantages

Shared-facility savings

Lights, elevators, and pumps are controlled automatically, property energy use falls by 30%, and operating pressure eases

Solar and storage together

Forecast solar output, schedule charge and discharge, and lift self-consumption to 70%

Energy service for residents

The mobile app shows live use, and AI sends saving tips that cut the household bill

Orderly charging

Valley-period charging, a lower tariff, and points rewards cut charging cost by 40%

Technical Architecture

The energy IoT stack, from sensors to the management platform

Application layer

Energy management platform Mobile monitoring app Data visualization Reporting and analysis

Platform layer

Energy data platform AI optimization engine Load forecasting model Automated control

Network layer

Industrial Ethernet Power-line communication 4G/5G wireless LoRa low-power network

Sensing layer

Smart meters Environmental sensors Power quality monitors Equipment status sensors

Success Cases

A smart energy deployment already running in the field

Smart Energy at a Large Industrial Park

A smart energy system for a 500-hectare industrial park, covering 150 companies and 2,000 monitoring points.

32%
Lower overall energy use
28%
Energy cost saved
15%
Share of new energy
98%
Supply reliability

How energy use changed after the project

Related Resources

How smart energy is built, and where it is used

Smart energy knowledge base

Architecture, use cases, and how a smart energy project is put in place

Technical Support

Technical advice and support while the project is being delivered

Start a Smarter Energy Operation

The team will shape a smart energy design around your site