A flexibility architectural design for enhancing energy management and sharing benefits in low-voltage microgrid systems using a big data platform

Low-voltage (LV) microgrids with high penetration of distributed energy resources (DERs) face growing challenges in power quality (PQ) management, real-time monitoring, and multi-stakeholder coordination. Existing big-data approaches address forecasting and optimization but lack an integrated framework combining heterogeneous DER data, semantic interoperability, severity-aware diagnostics, and equitable benefit sharing. The purpose of this study is to present DeNICE, a flexible big data architecture for LV microgrids built on five formal design principles: protocol-agnostic ingestion, registry-driven semantic harmonization, reusable service orchestration, latency-aware scaling, and stakeholder-centric transparency. A transparent rule-based PQ engine is a key methodological innovation that can achieve real-time anomaly prioritization for preventive maintenance planning. The architecture implements these principles through dual-mode ingestion, a configurable metadata registry for semantic harmonization, and an Elasticsearch-Kubernetes storage and indexing layer. A real-world deployment at the SGtech microgrid in Thailand using multi-resolution datasets (1-minute, 15-minute, hourly) confirmed system robustness. Scalability tests across 10–5000 DERs confirm near-linear ingestion ( R 2 = 0.9997), bounded indexing latency, and 40–72 ms across all loads. Operationally, MSOs reduce reverse power flow by approximately 50% using a 100-kWh battery during PV peak periods; DSOs reduce feeder overload by 33.11 kW through threshold-notification alarms; and MOs benefit from improved bulk dispatch planning. The results under a two-perspective benefit-sharing scheme (NPV = USD 20,166; BCR = 1.22; payback period of 5.0 years at full-stack value capture) are confirmed by techno-economic analysis on scalability. Cost-per-DER decreases 500-fold from 600 USD/year (10 DERs) to 1.20 USD/year (5000 DERs), approaching aggregator-grade economics for LV microgrid operations.

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Publication Details

Journal
Applied Energy
Published
2026-06-30
DOI
https://doi.org/10.1016/j.apenergy.2026.128297
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

A flexibility architectural design for enhancing energy management and sharing benefits in low-voltage microgrid systems using a big data platform

Nipon Ketjoy, Pornthip Mensin, Unchittha Prasatsap, Phongphun Kijsanayothin et al.
Applied Energy
Microgrid Control and Optimization
article

A flexibility architectural design for enhancing energy management and sharing benefits in low-voltage microgrid systems using a big data platform

Nipon Ketjoy, Pornthip Mensin, Unchittha Prasatsap, Phongphun Kijsanayothin, Malinee Kaewpanha, Yodthong Mensin
article en

Abstract

Low-voltage (LV) microgrids with high penetration of distributed energy resources (DERs) face growing challenges in power quality (PQ) management, real-time monitoring, and multi-stakeholder coordination. Existing big-data approaches address forecasting and optimization but lack an integrated framework combining heterogeneous DER data, semantic interoperability, severity-aware diagnostics, and equitable benefit sharing. The purpose of this study is to present DeNICE, a flexible big data architecture for LV microgrids built on five formal design principles: protocol-agnostic ingestion, registry-driven semantic harmonization, reusable service orchestration, latency-aware scaling, and stakeholder-centric transparency. A transparent rule-based PQ engine is a key methodological innovation that can achieve real-time anomaly prioritization for preventive maintenance planning. The architecture implements these principles through dual-mode ingestion, a configurable metadata registry for semantic harmonization, and an Elasticsearch-Kubernetes storage and indexing layer. A real-world deployment at the SGtech microgrid in Thailand using multi-resolution datasets (1-minute, 15-minute, hourly) confirmed system robustness. Scalability tests across 10–5000 DERs confirm near-linear ingestion ( R 2 = 0.9997), bounded indexing latency, and 40–72 ms across all loads. Operationally, MSOs reduce reverse power flow by approximately 50% using a 100-kWh battery during PV peak periods; DSOs reduce feeder overload by 33.11 kW through threshold-notification alarms; and MOs benefit from improved bulk dispatch planning. The results under a two-perspective benefit-sharing scheme (NPV = USD 20,166; BCR = 1.22; payback period of 5.0 years at full-stack value capture) are confirmed by techno-economic analysis on scalability. Cost-per-DER decreases 500-fold from 600 USD/year (10 DERs) to 1.20 USD/year (5000 DERs), approaching aggregator-grade economics for LV microgrid operations.

Applied EnergyVol. 422
Naresuan University (TH)
Naresuan University, Thailand Science Research and Innovation
Affordable and clean energy
Openalex Percentile: Top 8%
Microgrid Control and Optimization
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