Digital Twins for Distributed Energy: From Zero Export to Grid-Integrated Solar and Storage
E03 is a simulation-based engineering case study exploring how rooftop photovoltaics, battery energy storage, digital monitoring and grid-export controls can be coordinated for 226 residential users in Ayaviri, Peru.
Scope: engineering and financial scenario assessment—not a commissioned installation or an approved grid-connection study.
Explore the E03 resultsWhat a digital twin contributes to distribution networks
A digital twin links an engineering representation of the physical network with relevant operational data. It supports the study of interactions among household demand, photovoltaic generation, battery storage, advanced metering infrastructure (AMI) and network operating limits. In E03, this approach is used primarily as a simulation and decision-support prototype; continuous field synchronization has not yet been demonstrated for all users.
Six-stage engineering workflow
This application-oriented sequence complements CONSCOSA's broader R-E-C-P-G-A methodology for digital twins in infrastructure.
Connecting distribution assets, distributed resources and information
Transformers, feeders, residential customers, demand profiles and electrical operating conditions.
Solar generation, direct self-consumption, battery dispatch, surplus management and export controls.
Metering architecture, data exchange, scenario updates and operating analytics.
Functional architecture of the E03 digital twin
Conceptual architecture only. Physical PV–BESS/network power exchange and AMI/control information exchange can be bidirectional. Arrows show conceptual relationships; dashed green lines represent planned data exchange without specifying a flow direction or validated dispatch. The reference SED, communications and field interfaces require verification.
Reference equipment and constraints
| Parameter | E03 reference | Engineering qualification |
|---|---|---|
| PV per household | 1.44 kWp | Modeled as two 720 Wp modules; commercial specifications and inverter compatibility require verification. |
| BESS per household | 1.024 kWh nominal | 0.80 kW reference battery/inverter power per household; usable capacity depends on operating constraints. |
| Aggregated BESS power | 180.80 kW | Reference equipment sum, not guaranteed network support capability. |
| Smart metering | AMI concept | Field deployment and individual measured profiles have not been demonstrated. |
| Cloud communication | 15-minute interval | Communication requirement, not evidence of individual meter sampling frequency. |
The E03 reference configuration
The original E03 model combines distributed photovoltaic systems and lithium battery storage. Its investment estimate includes equipment and a provision for complementary import-related logistics and contingencies.
From a digital model to a grid-aware operating strategy
The engineering approach combines load and solar profiles, battery state-of-charge constraints, energy exchanges and configurable export ceilings. The reference deployment concept begins with Zero Export operation and evaluates a hypothetical transition to Net Billing from year three. Net Metering is also considered as a comparative compensation scenario.
Cloud communication: the project specifies a 15-minute cloud communication interval. This is a communications constraint and must not be confused with proof that all 226 homes already have individually measured quarter-hourly data. The simulation's time step and the provenance of input profiles must be documented separately.
Understanding modeled generation, demand and surplus
The reference scenario includes a 20% demand adjustment applied to historical consumption profiles. The following figures reproduce the annual E03 model balance reported in the Spanish technical publication.
E03 annual results · two complementary accounting views
A · How household demand is served
These demand-side figures sum within rounding. Aggregate grid imports are modeled as zero; this is not a verified individual-household outcome.
B · Photovoltaic generation and potential surplus
Separate model indicators, not a closed generation allocation. Battery charging, losses, curtailment and operating boundaries require reconciliation before a complete Sankey diagram is published.
Annual energy magnitudes (MWh)
Illustrative comparison of separate annual model indicators, not an additive energy-flow diagram. Values are rounded from the E03 balance.
| Annual indicator | Model result | Interpretation |
|---|---|---|
| Electricity demand | 113,736.53 kWh | Reference annual consumption, including the modeled 20% adjustment. |
| Photovoltaic generation | 701,617.19 kWh | Simulated annual PV production. |
| Direct photovoltaic consumption | 69,253.58 kWh | PV used directly by consumers. |
| BESS discharge | 44,482.95 kWh | Energy supplied by battery storage. |
| Grid imports | 0.00 kWh | Aggregate reference model output; not a verified household-level operating outcome. |
| Modeled energy surplus | 583,081.28 kWh | Potential export reference before operational injection restrictions. |
Export limits and energy curtailment
In an exploratory aggregate simulation, a hypothetical 100 kW export ceiling produces markedly different solar curtailment depending on installed PV capacity. The ceiling is a sensitivity parameter, not an Electro Puno connection authorization.
Effect of a hypothetical 100 kW export ceiling
Illustrative annual solar curtailment in the aggregate model, not an approved grid export limit. Bars are scaled to the largest displayed curtailment value.
| PV per household | BESS per household | Annual export | Solar curtailment |
|---|---|---|---|
| 0.72 kWp | None | 275.40 MWh | 7.34 MWh |
| 0.72 kWp | 1.024 kWh | 224.82 MWh | 7.34 MWh |
| 1.44 kWp | None | 363.98 MWh | 268.39 MWh |
| 1.44 kWp | 1.024 kWh | 317.79 MWh | 265.31 MWh |
These figures are preliminary model outputs. They illustrate why grid hosting capacity and curtailment must be incorporated into project sizing, rather than maximizing installed solar capacity in isolation.
Nighttime autonomy: an engineering constraint
Modeled electricity demand from 18:00 to 06:00 represents approximately 38.16% of annual demand. The E03 reference battery capacity is 1.024 kWh nominal per household, but usable energy depends on state of charge, operating limits, conversion efficiency and individual load profiles.
An aggregate energy-to-average-load calculation can provide an illustrative equivalent duration; it is not a guaranteed number of backup hours for an individual household. A bankable design requires household-level nighttime profiles, battery dispatch and reliability criteria.
Transition from Zero Export to hypothetical Net Billing
The original E03 financial model considers two initial years without recognized export revenue. From year three onward, it simulates Net Billing compensation for eligible surplus energy. This is an evaluation assumption, not an approved tariff or connection arrangement.
| Financial indicator | E03 result | Interpretation |
|---|---|---|
| Assumed export price | PEN 0.3029/kWh | Model assumption; not an authorized export tariff. |
| Avoided purchase price | PEN 0.70/kWh | Assumed retail energy cost. |
| Unrestricted reference annual export valuation | PEN 176,615.32 | Before annual degradation and the initial Zero Export period. |
| Year 1 · Zero Export | PEN 0.00 export revenue | No modeled export compensation. |
| Year 2 · Zero Export | PEN 0.00 export revenue | No modeled export compensation. |
| Year 3 · projected export | 577,265.04 kWh | Hypothetically eligible energy under the model. |
| Year 3 · projected export revenue | PEN 174,853.58 | Conditional simulated revenue. |
Reference scenario · operating and revenue timeline
Scenario assumptions, not approved compensation arrangements. Future export revenue depends on technical hosting capacity, regulation, operating restrictions and PV degradation.
Financial viability of the reference scenario
Net present value · three evaluation perspectives
All figures are expressed in Peruvian soles (PEN). These indicators reflect different assessment perspectives and must not be added or interpreted as equivalent cash flows. Results remain conditional on the E03 model assumptions.
| Additional financial parameter | Reference value | Scope |
|---|---|---|
| Evaluation horizon / discount rate | 20 years / 8% annually | Reference financial model. |
| Social NPV / multi-actor NPV | PEN 1,581,219.29 / PEN 1,563,504.30 | Distinct perspectives; not interchangeable with financial NPV. |
| Initial operating strategy | Zero Export in years 1–2 | Modeled scenario. |
| Hypothetical compensation | Net Billing from year 3 | Subject to applicable regulation and grid feasibility. |
The reference cash flow includes self-consumption savings, simulated export revenue from year three, operating and maintenance expenses, PV degradation, and scheduled battery and inverter replacements. Its NPV assumes the modeled energy surplus can be compensated without the actual network export limits used in subsequent sensitivity analyses.
Equipment and commercial feasibility of alternative scenarios
Exploratory comparisons show that the economically preferred PV–BESS configuration changes with the compensation scheme and permitted export capacity. Removing storage can improve modeled financial returns when backup and grid-support benefits are not remunerated; this does not eliminate its potential technical value.
The E03 reference CapEx is PEN 892,665.65. Alternative CapEx and net-present-value results are sensitivity estimates derived from documented budget prices and simplifying scaling assumptions—not supplier quotations or investment guarantees.
Engineering validation roadmap
- Validate input data: establish the source and representativeness of each household's demand and solar profiles.
- Confirm equipment: verify module, inverter, storage and export-controller compatibility using actual supplier specifications.
- Assess hosting capacity: conduct power-flow, voltage, thermal and reverse-power studies for the relevant distribution assets.
- Test autonomy: simulate household-level state of charge and nighttime service, including outages where backup is required.
- Reassess economics: update CapEx, replacement schedules, operational expenditure and compensation assumptions.
- Move toward deployment: connect field measurements, communications and operating controls to the digital twin.
CONSCOSA's approach is to use digital twins as decision-support systems connecting technical design, grid constraints, economic assessment and implementation planning.
Explore the Digital Twins methodology →