Case study 02 - Sustainable coastal destination
Building the Future of Sustainable Coastal Hospitality
Explore how resorts, villas, renewables, storage, mobility and destination operations can contribute to one governed energy model.
Business context
One destination, many connected energy systems.
Hotels, villas, public spaces, district cooling, renewable generation, storage and mobility infrastructure all influence destination performance. The operating model must coordinate these systems without losing local control.
- Connected evidence across the estate
- Comfort and service constraints remain explicit
- Every scenario retains its assumptions
Creating one operational view across a destination
Leadership needed a credible way to connect operational performance, investment priorities and sustainability outcomes without compromising service.
Business challenge
Energy cost, carbon and service requirements were managed through fragmented systems and delayed reporting.
Decision requirement
Teams needed to compare interventions, understand assumptions and rank opportunities before committing operational or capital resources.
Business transformation
A shared decision model connects engineering, finance, operations and sustainability around the same evidence.
Property ownersEngineering teamsFinance leadersSustainability teamsOperations
What the Digital Twin must understand
Destination-scale demand
Connect operational behaviour, asset condition and demand context before recommending change.
Visitor experience
Connect operational behaviour, asset condition and demand context before recommending change.
Renewable variability
Connect operational behaviour, asset condition and demand context before recommending change.
Operational complexity
Connect operational behaviour, asset condition and demand context before recommending change.
Resilience
Connect operational behaviour, asset condition and demand context before recommending change.
Measurable commitments
Connect operational behaviour, asset condition and demand context before recommending change.
What changed operationally
Moving from fragmented reporting to a connected operating model changes how teams identify, test and verify improvements.
Reactive and fragmented
- Monthly utility review
- Disconnected BMS and meter data
- Manual baselines
- Limited scenario comparison
- Delayed maintenance response
- Portfolio performance difficult to compare
ENERGE TWINGoverned decision layer
Connected and predictive
- Live operational evidence
- Normalised performance baselines
- Automated variance detection
- Scenario testing before change
- Ranked investment opportunities
- Continuous outcome verification
BMS, PMS and enterprise systems become one operational picture
ENERGE TWIN complements the existing estate rather than forcing wholesale replacement.
Connect the controls already operating the estate
BMS, meters, HVAC controls, renewable systems and IoT signals retain their operational roles.
Relate energy demand to how the property is used
Occupancy, bookings, weather, tariffs and maintenance context explain demand.
Unify evidence needed for confident decisions
Measured, derived and modelled data remain distinguishable and auditable.
Integrate without creating uncontrolled operational risk
Approved interfaces and governed workflows protect continuity and accountability.
A continuous operational intelligence layer
Existing systems contribute to one governed model for analysis, simulation and decision support.
Utility data
Smart meters
BMS
Weather
Solar
Storage
ENERGE TWIN
Analytics
Decision support
Operational capabilities that work together
The model combines monitoring, simulation, optimisation, carbon and maintenance intelligence within one governed operating context.
Destination energy monitoring
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Demand simulations
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Storage orchestration
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Renewable integration
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Carbon intelligence
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Asset health prediction
Translate live evidence into prioritised actions while retaining operational constraints and confidence.
Representative simulation
Compare operating choices before implementation.
Values are illustrative model outputs, not guaranteed customer results.
Operating scenarioDestination energy ecosystemConnected asset view
Simulation comparisonBaseline18.6 GWhCurrent operating model Modelled15.2 GWhOptimised scenario
See the outcome before making the change
- Energy
- -15.2%
- Cost
- Indicative
- Comfort
- Protected
- Confidence
- High
Operational evidence translated into measurable value.
Illustrative modelled ranges. Actual outcomes depend on asset profile, climate, tariffs, schedules, data quality and implementation.
Operational experience
Operational improvement visitors never have to notice
Arrival
Service conditions remain protected while energy performance improves.
Rooms
Service conditions remain protected while energy performance improves.
Leisure
Service conditions remain protected while energy performance improves.
Comfort
Service conditions remain protected while energy performance improves.
Connected path to net zero
Net-zero operationsEfficiencyRenewablesStorageVerification
From discovery to continuous improvement
Discover
Build evidence, test decisions and verify progress.
Connect
Build evidence, test decisions and verify progress.
Model
Build evidence, test decisions and verify progress.
Analyse
Build evidence, test decisions and verify progress.
Simulate
Build evidence, test decisions and verify progress.
Optimise
Build evidence, test decisions and verify progress.
What made the operating case credible
Every result communicates where the evidence came from and how it should be interpreted.
Meters, BMS and verified records
Weather, schedules and occupancy context
Scenario assumptions remain visible
Outcomes compared with the governed baseline
Operational safeguards
- Comfort and service requirements remain explicit
- Approved scenarios retain accountable owners
- Measured outcomes update the baseline
Technical basis
- Model
- Operational Digital Twin
- Evidence
- Measured, derived and modelled
- Control
- Governed implementation
Intelligence that supports the next decision
Real-time monitoring
Surface drift and anomalies while action can still protect performance.
Scenario simulation
Compare operational choices, assumptions and likely outcomes.
Sustainable performance
Connect efficiency, renewables, carbon and service requirements.