Renewable energy solutions: digitalisation opportunities
Connecting asset, operations, field work, customer and compliance data from solar, wind, biomass, geothermal, storage, hydrogen and other renewable energy project development, installation and operation into a single managed digital chain.
Digital maturity
moderate
Skaitmenizacijos potencialas
88/100
Biggest challenge
Project portfolio investment priorities based on incomparable assumptions
Biggest opportunity
Unified project and asset lifecycle
The greatest value is created by the ability to use lifecycle data to inform which project to develop, how to hand it over and where energy and revenue are lost in operations.
Renewable energy solutions operating model
Operations encompass the development, design, financing, construction, grid connection, commissioning and operation of solar, wind, storage, biomass and other projects. Value is driven by the ability to manage project portfolio maturity, technical and regulatory dependencies, and to accurately attribute the causes of production losses after commissioning.
Significant value is created before construction
The quality of site, grid connection, permitting and financial assumptions determines project viability.
Construction data must persist into operations
Actual equipment, tests, defects and warranties must not remain solely in project files.
Production losses must be explained by causes
Weather, grid, equipment and market impacts must be separated so that actions are economically justified.
Market and technology context
EU priorities include faster permitting, grid connections, storage and flexibility. Therefore, digital value is created across the entire lifecycle from site selection to technical and market portfolio optimisation.
Limited grid connection capacityProject value is increasingly determined by the actual probability of connection, timeframe and flexibility options.
Cost of capital and project selection qualityPortfolio data must help reject weak projects earlier and allocate capital to the most mature.
Storage and hybrid portfoliosSingle plant monitoring is being replaced by multi-technology technical and commercial optimisation.
Typical operating process
01
Site and project opportunity assessment
Resources, land, grid capacity, environmental constraints and preliminary economics are analysed.
02
Permits, connection and financial model
Managed critical dependencies, assumptions, documents, deadlines and investment decision.
03
Design and procurement
Technical solutions, equipment suppliers, contract scope and schedule are approved.
04
Construction, testing and commissioning
Actual configuration, work quality, defects, tests and warranties are recorded.
05
Operation and maintenance
Production, equipment condition, works, downtime and causes of losses are monitored.
06
Portfolio and market optimisation
Actual project performance, production forecasts, storage regimes and market revenues are compared.
Digital maturity journey
0
Projects and plants managed in separate files
Development assumptions, permits, contractor documents, construction actuals and operational data are kept in different locations.
1
Digital project and production monitoring
Project schedules and plant production are visible in systems, but portfolio maturity, actual configuration and causes of losses are verified manually.
2
Integrated project development process
Land, permits, connection, financial model, technical solutions and critical path are managed according to unified states.
3
Development, construction and operational data linked across selected portfolios Typical current situation
Land, permits, connection, financial assumption, construction handover and operational data for selected technologies or project groups are managed according to common stages, but coverage is not yet uniform across the entire portfolio.
4
Data-driven portfolio performance Siektina
Generation, weather conditions, grid constraints, failures, degradation, maintenance and market revenues are analysed in a single portfolio view.
5
Hybrid and optimised energy portfolio
Generation, storage, flexibility and market solutions are optimised according to technical constraints, risk and commercial value.
Key finding
Digitalisation of a renewable energy portfolio must connect project site, permits, grid connection, financial assumptions, construction status and actual plant performance.
The first priority is not a general asset digital twin, but a single comparable project maturity and decision chain or a single unified construction handover process.
Related digitalisation topics
Renewable energy project portfolioDigital construction and asset handoverPower plant performance and generation loss analytics
Problemos
Most common digitalisation challenges
Problems arise between project development, permits, connection, construction, asset handover and actual portfolio performance.
Project portfolio investment priorities based on incomparable assumptions
Critical
Connection probability, permit maturity, generation forecast, CAPEX, financing terms and environmental risk are held in separate models.
Consequences
Capital is allocated slowly, weak projects are difficult to stop on time, and alternatives cannot be compared using uniform criteria.
Development, permitting and connection portfolio is managed in a fragmented way
Critical
Land rights, surveys, grid capacities, permits, environmental assessments, technical specifications, deadlines and investment assumptions are kept in separate files.
Consequences
Management cannot see true project maturity, critical path and overall portfolio risk, so capital is allocated slowly.
Construction and commissioning data are not transferred to operations
Critical
Actual configuration, serial numbers, tests, defects, warranties, cable or equipment locations and contractor documents remain in project files.
Consequences
The operations team receives an incomplete asset passport, struggles to manage warranties and repeats data collection.
Causes of generation losses and portfolio performance are insufficiently distinguished
Critical
Weather conditions, grid constraints, equipment failures, degradation, soiling, shading, outages and trading decisions are analysed separately.
Consequences
It is difficult to separate technical inefficiency from market or grid impact and to accurately determine the sequence of actions.
Asset and technical data fragmented across systems
High
Power plants, modules, inverters, turbines, storage units, connection points, land plots and projects are identified differently in GIS, project, ERP, SCADA, maintenance and document systems.
Consequences
Difficult to link failure, work, cost, risk and investment need to a specific physical asset.
SCADA and project signals insufficiently converted into portfolio actions
High
Power plant alerts, production deviations, grid constraints, warranty statuses and project delays enter different work queues.
Consequences
Teams are slow to distinguish between technical, grid, contractor or market issues and do not always prioritise the highest-value case first.
Power plant maintenance relies too heavily on calendar and manufacturer portals
High
Equipment condition, load, weather conditions, failure history, warranties and actual works are not connected in a single portfolio model.
Consequences
Unnecessary inspections are carried out, whilst significant performance losses or degradation are identified too late.
Construction and operational field work coordinated separately
High
Site location, current project version, contractor tasks, materials, safety, defects, tests and proof of completion are managed with different tools.
Consequences
Delays, repeat visits, incomplete handover documentation and warranty disputes increase.
Compliance, safety and environmental data are collected at the time of reporting
Medium
Permit conditions, land and connection documents, construction inspections, contractor evidence, generation data and environmental KPIs are collected from different systems only before a report or inspection.
Consequences
Report preparation is lengthy, data origin is difficult to trace, and non-compliance is noticed too late.
Opportunities
Greatest digital opportunities
Single-technology project portfolio maturity managementVery high impactFor a single technology or project group, connect site, land rights, permits, grid connection, technical and financial assumptions, critical path and investment decision.Faster project preparation
Digital construction, commissioning and handover processVery high impactManage project, contractors, actual completion, testing, defects, documents, warranties and handover to operations.Fewer commissioning issues
Portfolio generation, curtailment and technical performance optimisationVery high impactConnect weather, generation, grid curtailment, equipment condition, market prices and maintenance actions.Higher generation and revenue
Plant condition, warranties and maintenance managementVery high impactAlign equipment signals, generation losses, failures, warranties, works, parts and economic priority.Less downtime and better asset economics
Unified project and plant data foundationVery high impactConnect sites, land, permits, grid connections, projects, equipment, SCADA, documents and financial assumptions.Reliable decisions and less data reconciliation
Construction and operations field work coordinationHigh impactConnect project version, contractor tasks, materials, safety, defects, testing and proof of completion.Lower work costs
Permit and compliance condition controlVery high impactLink permit conditions, land and grid connection documents, construction inspections, environmental KPIs, incidents and corrective actions.Lower regulatory risk
Project Portfolio Maturity and Capital PlanningVery high impactCompare permitting, connection, technical, financial and environmental risks according to uniform decision criteria.More accurate capital investment
Biggest opportunity
Unified project and asset lifecycle
The greatest opportunity is to connect project site, measurements, permits, connection capacity, technical design, contractors, financial model, construction status and operational performance in a single portfolio chain.
Faster investment decisions
Fewer project delays
Higher quality asset handover
Fewer generation losses
More accurate portfolio capital allocation
Potential business impact
Project implementation speedA clear critical path and document statuses reduce waiting time and decision alignment.
Capital allocationProjects are compared by maturity, risk, connection probability and financial value.
Construction qualityActual configuration and test evidence reduce the risk of defects and incomplete handover.
Generation revenueLoss causes are detected more quickly and linked to specific action.
Warranty utilisationEquipment history and defects enable timely substantiation of warranty claims.
Portfolio scaleUnified monitoring enables management of more projects and power plants without increasing coordination at the same pace.
Sprendimai
How to solve these problems
Solution directions linked to specific business area problems they address.
Problema
Project development, permitting and grid connection portfolio managed in fragments
→
Sprendimo kryptis
Renewable energy project portfolio platform
Manages project sites, land rights, permits, grid connection, technical and financial assumptions, critical path and investment decisions.
Problema
Portfolio investment priorities based on incomparable assumptions
→
Sprendimo kryptis
Renewable energy project portfolio platform
Manages project sites, land rights, permits, grid connection, technical and financial assumptions, critical path and investment decisions.
Problema
Construction and commissioning data not transferred to operations
→
Sprendimo kryptis
Construction, commissioning and asset handover platform
During commissioning integrates actual completion status, testing, defects, documents, warranties and operational asset passport.
Problema
Construction and operations field work coordinated separately
→
Sprendimo kryptis
Construction, commissioning and asset handover platform
During commissioning integrates actual completion status, testing, defects, documents, warranties and operational asset passport.
Problema
Asset and technical data fragmented across systems
Difficult to link failure, work, cost, risk and investment need to a specific physical asset.
→
Sprendimo kryptis
Power plant asset and maintenance system
Unifies equipment hierarchy, manufacturer signals, failure history, warranties, maintenance work and spare parts.
Problema
Power plant maintenance relies too heavily on calendar schedules and manufacturer portals
→
Sprendimo kryptis
Power plant asset and maintenance system
Unifies equipment hierarchy, manufacturer signals, failure history, warranties, maintenance work and spare parts.
Recommended digital solutions
Solutions must integrate project maturity, construction fact, asset handover and operational performance across the entire lifecycle.
Renewable energy project portfolio platform
Manages project sites, land rights, permits, grid connection, technical and financial assumptions, critical path and investment decisions.
Construction, commissioning and asset handover platform
During commissioning integrates actual completion status, testing, defects, documents, warranties and operational asset passport.
Power plant asset and maintenance system
Unifies equipment hierarchy, manufacturer signals, failure history, warranties, maintenance work and spare parts.
Production loss and portfolio performance platform
Integrates SCADA, weather, grid curtailment, failure, work and commercial data and attributes losses to specific root causes.
Permitting, safety and compliance control platform
Project maturity is assessed using subjective percentages
Permit, connection and financial model status are kept in different files
Construction documents are transferred to operations at the end of the project
It is difficult to separate grid, weather and technical generation losses
Portfolio managers do not have a single comparable view of projects
Reikia atsargumo
There are no uniform project stages and mandatory evidence
Different technologies in the first version have completely different processes
Contractor data submission is not included in project contracts
There is an expectation that AI will replace engineering or investment appraisal
Recommended first version
Single-technology project portfolio management from site and connection to investment decision, with clear maturity stages, critical path, documentary evidence and executive portfolio view.
Unified project profile
Location, land rights, permits, connection, technical assumptions, CAPEX and responsible persons.
Maturity and critical path management
Stages are substantiated by mandatory documents, dependencies and decision deadlines.
History of risks and assumptions
Records when and why production, connection, cost or revenue assumptions have changed.
Portfolio comparison
Projects are compared by maturity, expected value, deadline and critical risks.
Kam pirmiausiaProject developer · Engineering manager · Finance or investment analyst · Permitting and land specialist · Portfolio manager
What not to include in the first versionMulti-technology and multi-country rules · Full construction and operations management · Automated investment decision · Complex storage and trading optimisation
Investment priorities
Connect single-technology project portfolio maturitySelect a single technology or project group and connect location, land, permits, connection, technical and financial assumptions and decision evidence.
Single development portfolio scenarioConnect land, permits, connection, technical and financial assumptions.
Digital construction handoverCapture actual configuration, testing, defects and warranties during works.
Production loss root cause analyticsSeparate technical, grid, weather and market impact.
Storage and portfolio optimisationExpand only after establishing a reliable foundation of technical and commercial data.
Key implementation conditions
Project statuses must have clear evidence
A project must not be considered ready based solely on a subjective percentage; each stage must be supported by specific documents and decisions.
Construction data must become operational data
Serial numbers, tests, settings, defects and warranties must be captured where the work is performed.
Portfolio KPIs must distinguish between different causes of loss
Technical failure, grid curtailment, weather deviation and trading decision cannot be shown as the same production shortfall.
Manufacturer portals are not a unified asset model
Data from different inverters, turbines or storage systems must be normalised and linked to a common equipment hierarchy.
AI recommendations must have economic and technical context
An anomaly signal must show expected energy loss, criticality, warranty status and boundaries of the suggested action.
Recommended implementation sequence
01
Project portfolio maturity model
Standardise project stages, critical documents, connection, permit, land and financing statuses.
Project status model
Critical path rules
Document and responsibility matrix
Portfolio risk KPIs
02
Single development process
Select a single technology or project group and connect site, permit, connection, financial model and decision information.
Unified project profile
GIS and document integration
Decision and assumption history
Management portfolio view
03
Digital handover for construction and commissioning
Capture actual configuration, tests, defects, warranties and documents during works, not at project end.
Mobile contractor forms
Equipment register
Testing and defects process
Operational asset passport
04
Production loss and maintenance analytics
Connect SCADA, weather, grid constraint, fault, works and commercial data and classify losses by cause.
Performance baseline
Loss classification
Maintenance priorities
Warranty case management
05
Portfolio and storage optimisation
Following a reliable data foundation, expand production forecasts, storage regimes, flexibility and market decision optimisation.
Forecast quality monitoring
Storage strategies
Market and technical scenario model
Portfolio value analytics
KPIs for measuring change
Share of projects with clear evidence-based maturity status%
Measure the reliability of portfolio data and decisions.
Average time between project stagesdays
Identify delays in permits, connection and decisions.
Number of construction changes after approvalunits per project
Assess the quality of design and contractor coordination.
Share of assets with comprehensive digital passport%
Measure the quality of construction and operational handover.
Unplanned downtimehours or %
Assess asset reliability and maintenance performance.
Share of explained generation losses%
Measure how much missing generation is attributed to a specific cause.
Forecast absolute error% or MWh
Monitor the quality of generation and commercial decision forecasts.
Key risks
Project maturity is assessed using incomparable statesDifferent teams interpret the same stage inconsistently, leading to a misleading portfolio view.Kaip suvaldyti Define uniform stages, mandatory evidence and accountable approval.
The construction platform duplicates contractors' workContractors submit information in their own systems and additionally complete the client's forms.Kaip suvaldyti Establish import schedules, clear minimum data requirements and mobile collection directly at the worksite.
The performance model compares incomparable power plantsTechnology, location, degradation, grid regime and data quality differ.Kaip suvaldyti Use a technology-appropriate baseline and clearly indicate data and model limitations.
AI signals create too many non-essential tasksThe anomaly model generates alerts without economic prioritisation.Kaip suvaldyti Link signals to expected energy loss, asset criticality and approved work rules.
The first version attempts to cover the entire project and operational cycleExcessive scope delays tangible results.Kaip suvaldyti Start with one project group and a clear scenario, such as development maturity or construction handover.
Inovacijos
More advanced digital innovations
AI, drones and digital models are valuable when their signal is linked to a project, maintenance or portfolio decision and a measurable energy outcome.
Market expansion3
AI for plant condition and production loss forecasting
Highly urgent
Analyses weather, SCADA, failure, maintenance, degradation and grid constraint data.
How it is applied The signal should show the expected MWh and revenue impact and be linked to a specific maintenance action.
What value can be created
Earlier fault detection
Reduced losses and downtime
What is needed for this to work
Contextual sensor data
Failure and work history
Model quality monitoring
Human confirmation
Medium-termCommercial solutions are available
Drones and thermal imaging for plant inspections
Relevant
Image and thermal data help detect defects in modules, blades, cables or connections.
How it is applied The detected defect is linked to the precise asset object, location, warranty and work task.
What value can be created
Greater inspection coverage
Lower workforce safety risk
What is needed for this to work
Asset geographical data
Standardised image collection
Defect taxonomy
EAM integration
Short-term perspectiveCommercial solutions are available
AI and geographical models for project site assessment
How it is applied The output is used for project screening but does not replace official surveys, permits or technical assessment.
What value can be created
Faster project screening
Lower early-stage development costs
What is needed for this to work
GIS data
Network and territory information
Clear model boundaries
Short-term perspectiveCommercial solutions are available
Early stage2
Power plant and project digital twin
Highly urgent
Connects project site, technical model, actual configuration, SCADA states and planned changes.
How it is applied Starts with one group of power plants or a construction handover scenario with a clear solution objective.
What value can be created
More accurate investment and maintenance planning
Faster incident impact assessment
What is needed for this to work
Reliable asset hierarchy
GIS and real-time data
Calibrated model
Version control
Long-term perspectiveApplied in practice
Hybrid power plant and storage optimisation
Highly urgent
A model of solar, wind, storage or other resources optimises generation, storage, grid constraints and trading revenues.
How it is applied Actions are constrained by equipment warranties, safety, connection conditions and market rules.
What value can be created
Less constrained generation
Higher portfolio value
What is needed for this to work
Unified asset model
Price and generation forecasts
Storage degradation model
Medium-termApplied in practice
D.U.K.
Frequently asked questions
Where to start – project development or operations digitalisation?
It is worth starting with the process that currently has the greatest financial uncertainty and the most manual coordination. For a rapidly growing developer, this is often the project maturity and connection portfolio, whilst for an operating plant owner it is the production loss and maintenance chain.
Does a project management system not already solve this problem?
A generic project system manages tasks and deadlines, but typically does not understand the land, permits, grid, technical and financial dependencies of an energy project. A domain data model is required that grounds project status in concrete evidence.
When is it worth creating a digital twin of a plant?
When there is already a reliable equipment hierarchy, actual configuration, SCADA tags, fault history and a clear solution that the model will improve. A beautiful 3D visualisation alone will not help reduce downtime or increase production.
How to connect equipment data from different manufacturers?
A common asset model is needed that links manufacturer tags and states to a uniform equipment hierarchy, fault categories and time context. Initially, it is sufficient to normalise the most important signals for one technology or group of plants.
Where can AI help in operating the portfolio?
AI can detect anomalies, group loss causes, forecast production and help determine inspection priorities. A recommendation must be linked to expected MWh and revenue impact, asset criticality and human-confirmed action.
How to measure return on investment?
In the development side, assess shorter decision time, fewer lost projects and better capital allocation. In operations – avoided production loss, shorter downtime, lower inspection costs and timely use of warranties.
Next step
Connect project development, installation and operations signals, assets and field work across solar, wind, biomass, geothermal, storage, hydrogen and other renewable energy projects
Assess which gap in project development, construction handover or plant performance is currently reducing portfolio value the most.