This document presents a detailed analysis of a Regional Electric Distribution Network Operator (hereinafter, "the Entity"), operating within a complex mountain territory in Northern Italy. This study serves as a fundamental case study within a broader Research and Development Project on Mountain Ecosystem Innovation, providing a practical example of managing electrical infrastructure in an Alpine setting. The entire discussion has been anonymized, omitting proper names of specific locations, companies, or projects.

Context and Structure of the National Electric Grid

The energy supply system in Italy is organized into three distinct and interdependent levels: Production, Transmission, and Distribution. Energy is generated by a variety of plants (thermal, hydroelectric, wind, solar) and fed into the National Transmission Network, managed by a single Operator at an extra-regional level. This network operates at high and extra-high voltage (typically from 220 kV to 380 kV) to minimize losses during long-distance transport.

The crucial role of the Distribution Entity begins once the energy leaves the transmission network. Its primary function is to receive energy from the Primary Substations and progressively reduce the voltage. First, the energy is lowered to Medium Voltage (MV), typically between 15 and 30 kV, for transport toward urban centers and industrial areas. Subsequently, in the Secondary Substations or MV/LV Substations, the voltage is further reduced to Low Voltage (LV), generally 230-400 V, the necessary level for use by final consumers, such as homes and small businesses.

These substations are the nerve centers of the infrastructure. Beyond simple voltage transformation, they integrate vital functions of protection against faults and overcurrents, manoeuvring to allow circuits to be opened or closed during maintenance or in an emergency, and measurement to constantly monitor electrical parameters. The design and maintenance of these structures strictly comply with severe regulations defining their safety and performance requirements.

Fundamental Components of the Infrastructure

The physical apparatus of a substation consists of several interconnected elements. Transformers constitute the functional heart of the installation, distinguished between large Power Transformers (HV/MV) and smaller Distribution Transformers (MV/LV), necessary for the final voltage drop. These are complemented by manoeuvring and protection equipment, which includes circuit breakers, designed to interrupt current flow when necessary; disconnectors, which ensure the physical isolation of a section for safe work; and protection relays, which monitor circuit conditions in real-time, intervening in case of serious anomalies.

Furthermore, within the substation are measurement transformers (for current and voltage), essential for accurate monitoring of energy flows, and electrical panels that collect and manage control and monitoring systems. Safety is guaranteed by a strict earthing system, which diverts fault currents to the ground, and the entire structure is protected by an enclosure (masonry, prefabricated, or metallic).

The network itself extends across the territory with different topologies. The Medium Voltage Network is primarily designed with a meshed or ring structure, where circuits are closed or can be closed, thus conferring greater reliability of service. In case of a fault at one point, utilities can be re-energized from an alternative route. MV lines can be either overhead (more exposed to atmospheric events but economical) or underground (more expensive but resilient and with low visual impact). Conversely, the Low Voltage Network adopts a radial structure, branching out from the secondary substation to individual users. Although simpler and cheaper to build, this configuration offers lower reliability, as a fault on one branch leads to service interruption for all users downstream. Conductors are typically made of copper and aluminum, protected by high-efficiency dielectric polymeric or ceramic insulators. The entire network management is governed by imperatives of safety, reliability, efficiency, and minimizing environmental impact.

The Case Study: A Historical Operator in the Mountains

Origins and Chronological Development

The Entity under consideration boasts a centuries-old history, having been founded in the early twentieth century, specifically in 1907, with the pioneering intent of utilizing local water resources for the production and distribution of electrical energy. Its birth was a catalyst for the industrial and artisanal development of the territory, contributing significantly to the socio-economic progress of the mountain community.

Its evolution is marked by progressive investments in modernization. After the initial start-up of the first hydroelectric plant, which initially supplied modest power, the main plant underwent several upgrades: a significant power increase occurred in 1954, and a subsequent reconstruction and upscaling was completed in 2004, bringing the installed capacity to 4000 kW. A key period of transformation occurred between 2001 and 2004, with the transition of the medium voltage distribution to the standard value of 20 kV and the introduction of the first automation and remote control systems for the network. The commitment to sustainability was then reinforced starting in 2006 with the implementation of electronic meters and a massive development of a widespread photovoltaic project between 2008 and 2014, marking the integration of renewable sources.

Territorial Impact and Operational Structure

The territory served by the Operator is distinguished by its complex morphology and high altitude, with over 50% of the area located above 600 meters above sea level. This geographical configuration poses unique challenges, particularly for the resilience and maintenance of the infrastructure. The Entity is not just an energy provider but a true driver of social cohesion and economic development, ensuring access to service even in the most remote areas and supporting local businesses.

In terms of volume, the Energy Distributed annually by the network has remained relatively constant in the 2016-2021 period, averaging around 26 million kWh. The network itself is a complex system of overhead and underground MV and LV lines, with transformation substations (including pole-mounted substations) interconnected in a topology centered around three main rings. To optimize the management of this extensive network, a new GIS platform (Geographic Information System) was adopted around 2018, allowing for highly accurate mapping and updating (about 1 meter) of MV and LV network geographical data—a critical aspect for predictive maintenance and intervention planning. The MV/LV substations are numerous, over eighty, and many of them have significant power subtended from photovoltaic plants.

Electrical Behavior and Network Characteristics

The network managed by this Entity is categorized as an active network, as local generation sources, particularly the hydroelectric plant and distributed photovoltaic systems, actively inject power into the system. This characteristic significantly influences the electrical behavior of the network.

The injection of active power occurs for approximately 45% - 55% of the annual duration, typically concentrated during periods of greater sunlight and water flow, with peaks recorded between 6.2 MW and 6.9 MW. Conversely, the maximum withdrawal of active power by users is around 4 MW and mainly occurs during the winter evening hours.

Another peculiarity is the behavior of reactive power: for almost the entire year, approximately 98%, the network exhibits a predominantly capacitive character, with a maximum recorded value of about 1.5 MVAr. This phenomenon is largely due to the capacitive effect of the MV cables, which prevails over the inductance of transformers and users, especially when the active power in transit is low.

Regarding network voltage, operational data shows significant variations. The voltage measured at the main connection point exceeds 20.5 kV for 56% of the year and remains above 21 kV for about 5% of the time. Voltage fluctuations of about 4% have been observed, with maximum values reaching 21.8 kV and minimums hovering between 19.4 kV and 19.6 kV. Such variations require careful management to maintain service quality within regulatory limits.

The Evolution toward the Smart Grid and Future Prospects

The Operator is actively embracing the path toward the Smart Grid, integrating the existing infrastructure with the latest digital technologies. This includes the widespread use of smart meters for real-time monitoring of consumption and production, the implementation of network automation to rapidly isolate faults and restore service, and the advanced system integration for managing the growing distributed generation from renewable sources.

Looking ahead, the Entity must face several crucial challenges. The first concerns the continuous adaptation required to manage the increasing spread of non-programmable renewable sources, which impose bidirectional energy flows and greater management complexity. Secondly, the goal of improving overall energy efficiency by further reducing network losses remains fundamental. Finally, with increasing digitalization, the Cybersecurity of control infrastructures has become an absolute priority to protect a critical system from potential cyber threats.

In conclusion, the analysis of the Distribution Network Operator in an Alpine context provides a concrete example of the operational principles of Italian electrical networks. The challenges associated with managing an active network with considerable distributed generation, and the resulting voltage and power dynamics, offer valuable insights for developing sustainable energy solutions, confirming the Operator's role as a key player in the energy transition for its community.

Analysis of the Main Activities Performed During the Innovation Project

This section outlines the core operational and analytical activities undertaken during the Research and Development Project (hereinafter, "the Project"), an initiative designed to strategically address the escalating challenges of the modern energy transition, particularly within complex operational environments such as regional distribution networks in mountain areas. The Project's central objective was to rigorously define a validation plan and execute an in-depth analysis regarding the optimal implementation of Battery Energy Storage Systems (BESS) into the existing electrical distribution infrastructure. This comprehensive body of work, structured across several interconnected validation stages, successfully bridged the gap between theoretical modeling and applied simulation to transform existing grids into resilient and proactive energy systems.

Phase One: Foundation and Criteria Definition

The initial phase of the Project focused on establishing the foundational framework necessary for the subsequent modeling and simulation activities. This stage began with a meticulous analysis of the technology and market landscape, driven by the recognition that unprecedented volatility and the accelerating penetration of intermittent renewable sources (solar and wind) had rendered BESS deployment a strategic imperative for grid stability, energy security, and competitive pricing.

The technological review encompassed a detailed examination of various grid-scale storage technologies, including Lithium-ion (Li-ion), Sodium-Sulfur (NaS), Flow Batteries, Hydrogen-based systems, and Supercapacitors. This comparative analysis carefully evaluated each technology based on key performance attributes such as energy density, cycle life, operational temperature, efficiency, and capital expenditure (CAPEX). For instance, Li-ion was identified for its high efficiency (90-95%) and suitability for high-speed applications like frequency regulation and load shifting, while NaS and Flow Batteries were assessed for their longer duration capabilities and extensive lifecycles, albeit with higher initial CAPEX. Hydrogen-based solutions, despite their potential for very long-term (seasonal) storage, were noted for their significantly lower efficiency and higher cost per kilowatt-hour stored.

Following the technical assessment, the Project defined a comprehensive set of Key Performance Indicators (KPIs). These metrics were essential for objectively measuring the success and viability of BESS integration. The KPIs covered both Technical-Operational aspects, such as round-trip efficiency, grid support effectiveness, and charge/discharge control validation, and Economic-Financial aspects, including Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period, and the Levelized Cost of Storage (LCOS). This early stage ensured that all later simulation results could be directly translated into quantifiable measures of investment value and operational benefit.

Phase Two: Development of the PROGRESS Models and Hybrid Architecture

The Project's methodological core was the creation of the integrated PROGRESS Model Set, which provided the theoretical and structural blueprint for the BESS implementation strategy. This set was partitioned into three distinct yet interdependent categories:

First, the Technical-Functional (T-F) Models were developed to accurately represent the physical behavior of all assets—the BESS units themselves, power lines, and load profiles—and to define the operative logic of the control system. These models incorporated detailed electrical parameters (such as power flows and voltage drops) and, crucially, sophisticated optimization models for predictive charge and discharge cycles. These optimization algorithms were fundamentally based on both market price forecasts (for revenue maximization) and load/generation forecasts (for technical stability), thereby establishing the definitive control rules for the BESS units under various operating conditions.

Second, the Economic-Financial (E-F) Models acted as the vital intermediary, translating the optimized operational output from the T-F models into concrete financial value. These models rigorously calculated all investment costs (CAPEX), operating costs (OPEX), and projected revenues derived from market activities (arbitrage), ancillary service provision, and operational savings (e.g., reduced line losses or deferred infrastructure upgrades). The application of robust financial analysis, including NPV and IRR, allowed the Project to establish the true profitability threshold and calculate the LCOS, a key metric for comparing the cost of storing energy across different technologies and scenarios.

Third, the Network and Architecture Models defined the topographical and infrastructural context for BESS placement, identifying critical connection points within the distribution network, such as primary substations, hydroelectric generation centers, and MV/LV substations. The modeling in this area led to the key strategic conclusion of the Project: the endorsement of a Hybrid Architecture. This novel approach strategically combines the advantages of Centralized (Utility-scale) BESS—typically placed at a high-voltage interconnection point to maximize market access and ancillary service provision—with the benefits of Distributed BESS units, strategically installed at lower voltage levels (MV/LV substations) to address local technical needs, such as power quality improvement, enhanced local resilience, and the optimization of consumer self-consumption (acting as virtual microgrids). This Hybrid Architecture was thus established as the optimal paradigm for balancing financial profitability with technical security in a complex mountain territory.

Phase Three: Engineering and Test Environment Implementation

The subsequent activity focused on the practical realization of the Energy Management System (EMS) platform, which served as the operational engine and test environment for all subsequent simulations. This EMS platform was engineered with a state-of-the-art microservices architecture, fully containerized using Docker technology, to ensure scalability and robustness for processing real-time and historical data.

The platform’s core infrastructure involved a sophisticated data persistence layer, utilizing PostgreSQL as the relational database backbone, enhanced by the TimescaleDB extension specifically for the highly efficient management of massive volumes of time-series data. This was critical for handling high-granularity sensor readings and operational logs required for accurate simulation. The operational intelligence was driven by a sophisticated Processing Engine, which included core AI modules: the Forecaster, responsible for generating highly accurate predictions of load, generation (from renewables), and market prices; and the Planner, which utilized these forecasts within optimization algorithms to determine the optimal charge/discharge schedule (State of Charge - SoC profile) for all BESS units, centralized and distributed alike. The entire system’s operational status and simulation results were visualized and monitored using a dedicated interface, completing the loop from data ingestion to intelligent control and operational feedback.

Phase Four: Technical-Operational Simulations and Economic Analysis

With the EMS platform fully operational, the Project proceeded to the crucial stage of technical-operational simulations. These simulations were executed across two primary scenarios, validating the Project's core hypotheses:

• Scenario 1 tested the Utility-scale Centralized BESS configuration, focusing on maximizing revenue generation through energy arbitrage (buying power cheap, selling power dear) and providing essential Ancillary Services to the higher-voltage transmission network. The key technical outputs included validating the BESS's ability to maintain optimal State of Charge profiles dictated by the AI-driven Planner, demonstrating high cycle efficiency, and confirming its role in supporting overall grid stability.
• Scenario 2 analyzed the performance of Distributed BESS units, aggregated as a virtual power plant, primarily focused on maximization of local self-consumption and addressing localized grid quality issues. This scenario validated the units' capacity to manage local power quality, defer the need for costly infrastructure upgrades at specific MV/LV substations, and enhance resilience by potentially supporting microgrid operations during outages.

The final and most critical activity was the comprehensive Economic-Financial Analysis (Cost-Benefit). Utilizing the operational profiles generated by the T-F models, this analysis rigorously quantified the cash flows for both scenarios. The Project meticulously calculated and compared the financial indicators (NPV, IRR, Payback Period, and LCOS) for different BESS sizing configurations, successfully identifying the economies of scale and the minimum economically viable investment threshold for each scenario.

Strategic Conclusion and Investment Recommendations

The Project culminated in an integrated Strategic Analysis, synthesizing the technical validation and financial quantification. The results unequivocally demonstrated the financial superiority of the Utility-scale Centralized BESS scenario, confirming its potential to achieve highly attractive financial returns (high NPV and IRR) primarily through market arbitrage and network services. Conversely, the Distributed BESS units, while generating lower immediate financial returns through local self-consumption optimization, provided significantly higher strategic value in terms of technical benefits—namely, localized power quality improvement, network resilience (microgrid capability), and deferred infrastructure investment—benefits that are vital for socio-economic stability in mountain territories but often not fully monetizable under current market mechanisms.

The Project's definitive recommendation was the adoption of a Phased Implementation of the Hybrid Architecture. This strategy proposes: Phase 1: Financial Maximization—installation and commissioning of a high-capacity Centralized BESS unit to immediately consolidate the return on investment and generate maximum operating revenues. Phase 2: Strategic Extension—leveraging the flexibility and coordination capability of the EMS platform and the revenues generated by the central unit to expand the system by installing the Distributed BESS units.

In essence, the Project successfully demonstrated that addressing the energy transition challenges in complex mountain contexts requires a balanced approach where a high-yield centralized BESS ensures the financial competitiveness and funding source, while the distributed BESS units guarantee the technical security and resilience of the local infrastructure. The developed EMS platform and its integrated AI algorithms thus serve as the intelligent backbone necessary to coordinate this complex, dual-function architecture, transforming the existing grid into a resilient, proactive, and financially sustainable system. The entire body of work serves as a practical, data-driven model for other regional operators facing similar challenges.