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Investigation of Lightning Effects on Solar Power Plants Connected to Transmission Networks

Analysis of lightning-induced overvoltages in grid-connected solar plants, evaluating surge arrester effectiveness via EMTP simulations and spectral analysis.
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1. Introduction

The rapid integration of large-scale solar photovoltaic (PV) plants into high-voltage transmission networks introduces new vulnerabilities to grid disturbances, particularly lightning strikes. This paper investigates the propagation of lightning-induced overvoltages from transmission lines to connected solar power plants, a critical issue given the geographical overlap of high solar irradiance and high lightning activity regions. The study employs Electromagnetic Transients Program (EMTP) simulations to model the system and evaluates the effectiveness of surge arresters as a primary protective measure.

Key Insights

  • Lightning strokes on transmission lines can induce severe overvoltages at the Point of Common Coupling (PCC) of solar plants.
  • The vulnerability is heightened by the long cable runs and sensitive power electronics (inverters) within PV plants.
  • Standard protection strategies designed for traditional generation may be inadequate for distributed, inverter-based resources like solar.

2. Methodology & System Modeling

The research is based on a simulation-driven methodology using the industry-standard EMTP-RV software for accurate modeling of electromagnetic transients.

2.1 EMTP Simulation Framework

The entire system—comprising the transmission line, solar plant collection grid, transformers, and surge protection devices—was modeled in EMTP. This allows for time-domain analysis of fast-front surges with nanosecond-to-microsecond resolution.

2.2 Lightning Stroke & Solar Plant Model

The lightning stroke is modeled using the Heidler current source function, a standard for representing the channel current: $i(t) = \frac{I_0}{\eta} \frac{(t/\tau_1)^n}{1+(t/\tau_1)^n} e^{-t/\tau_2}$. Parameters $I_0$ (peak current), $\tau_1$ (front time), and $\tau_2$ (tail time) were varied. The solar plant was modeled as an aggregate equivalent circuit, including DC cables, inverters, and step-up transformers.

2.3 Surge Arrester Configuration

Metal-Oxide Varistor (MOV) surge arresters were modeled at key locations: at the transmission line tower near the strike point and at the solar plant's main AC connection point. Their non-linear V-I characteristic is given by $i = k \cdot V^{\alpha}$, where $k$ and $\alpha$ are device constants.

3. Simulation Scenarios & Parameters

3.1 Lightning Parameter Variation

Simulations covered a range of realistic lightning parameters:

  • Peak Current (Ip): 10 kA to 100 kA (representing both negative and positive flashes).
  • Front Time (tf): 1 µs to 10 µs.
  • Tail Time (tt): 20 µs to 200 µs.
This matrix allows assessment of the impact of both fast, high-current strokes and slower, longer-duration events.

3.2 Strike Distance Scenarios

Lightning strikes were simulated at varying distances (e.g., 0.5 km, 1 km, 2 km) from the solar plant's grid connection point along the transmission line. Both direct strikes to the phase conductor (shielding failure) and backflashovers due to tower strikes were considered.

4. Results & Analysis

4.1 Overvoltage Magnitude Analysis

The primary metric was the transient overvoltage magnitude at the solar plant's AC bus. Without surge arresters, overvoltages frequently exceeded 3.0 p.u. (per unit) of the system's nominal voltage for strikes within 1 km, posing a severe risk to inverter insulation. The overvoltage waveform is a superposition of the incoming surge and reflections within the plant's internal cabling network.

Chart Description (Imagined): A line chart would show overvoltage (p.u.) on the Y-axis versus lightning strike distance (km) on the X-axis. Two lines would be plotted: one (red, steeply declining) for the scenario without arresters, showing high voltages at short distances; and another (blue, flatter) for the scenario with arresters, showing significantly clamped voltages across all distances.

4.2 Fourier & Hilbert Spectrum Analysis

Beyond time-domain magnitude, the study performed spectral analysis.

  • Fourier Transform: Revealed the dominant frequency components of the overvoltage. Without arresters, energy was concentrated in high-frequency bands (100 kHz - 1 MHz), which are particularly damaging to semiconductor devices. With arresters, the spectrum shifted to lower frequencies.
  • Hilbert-Huang Transform (HHT) / Marginal Spectrum: This time-frequency analysis provided insight into how energy distribution evolved during the transient event, showing the non-stationary nature of the surge and the arrester's dynamic clamping effect.

4.3 Surge Arrester Performance

The surge arresters demonstrated high effectiveness, typically limiting overvoltages to below 1.8 p.u., a level generally within the withstand capability of modern PV inverters (typically rated for 2.0-2.5 p.u. for short durations). The energy absorption requirement for the arresters was quantified, which is critical for proper sizing.

Peak Overvoltage Reduction

> 40%

Average reduction with arresters installed

Critical Strike Distance

< 1 km

Strikes within this range cause highest risk

5. Technical Details & Mathematical Formulation

The core of the EMTP model relies on solving the telegraph equations for the transmission line, coupled with non-linear component models:

  • Transmission Line (Frequency-Dependent Model): Solved using the method of characteristics: $\frac{\partial v}{\partial x} + L' \frac{\partial i}{\partial t} + R' i = 0$ and $\frac{\partial i}{\partial x} + C' \frac{\partial v}{\partial t} + G' v = 0$.
  • Surge Arrester (MOV) Model: The piecewise non-linear characteristic is often implemented using the $\alpha$-$k$ model or the more dynamic Pinceti-Giannettoni model for energy tracking.
  • Inverter Impedance: The high-frequency impedance of the PV inverter, crucial for surge division, was modeled as a parallel RLC circuit based on typical filter designs.

6. Analysis Framework: Case Study

Scenario: A 100 MW solar plant connected to a 230 kV transmission line via a 230/33 kV step-up transformer. A lightning stroke with Ip = 50 kA, tf = 2 µs hits a tower 0.8 km away, causing a backflashover.

Framework Application:

  1. Model Setup: Build the EMTP model with detailed line constants, tower footing resistance (50 Ω), and plant internal impedance.
  2. Baseline Run (No Protection): Simulate. Record overvoltage at PCC (~3.5 p.u., 0.5 MHz dominant frequency).
  3. Mitigation Run (With Arresters): Place arresters at the struck tower and PCC. Re-simulate. Record clamped voltage (~1.7 p.u., < 100 kHz dominant frequency).
  4. Energy Calculation: Calculate energy absorbed by the PCC arrester using $W = \int v(t) \cdot i_{arrester}(t) dt$ to verify its rating is not exceeded.
  5. Sensitivity Analysis: Vary footing resistance and plant impedance to see impact on overvoltage.
This structured approach isolates variables and quantifies protection benefits.

7. Application Outlook & Future Directions

The findings have direct applications in the design and grid codes for large-scale solar facilities:

  • Enhanced Grid Codes: Transmission System Operators (TSOs) like PJM or ENTSO-E could mandate specific overvoltage protection studies and surge arrester specifications for grid-connected PV plants in high lightning-prone areas (KERA).
  • Smart Surge Protection: Future systems could integrate IoT-enabled arresters that monitor their own health and energy absorption, communicating with plant SCADA for predictive maintenance.
  • Hybrid Protection Schemes: Combining traditional MOV arresters with emerging technologies like series-connected fault current limiters (SFCL) or wide-bandgap semiconductor-based active clamps could offer superior protection with faster response.
  • Digital Twin Integration: The EMTP models developed in this research can form the basis of a digital twin for operational solar plants, allowing real-time risk assessment during thunderstorms using lightning detection network data (e.g., from Vaisala's GLD360 or Earth Networks).

8. References

  1. Grebovic, S., Aksamovic, A., Filipovic, B., & Konjicija, S. (2025). Investigation of Lightning Effects on Solar Power Plants Connected to Transmission Networks. Paper submitted to IPST2025.
  2. IEEE Std 1410-2010: IEEE Guide for Improving the Lightning Performance of Electric Power Overhead Distribution Lines.
  3. CIGRE WG C4.408. (2013). Lightning Protection of Large Wind Turbine Blades. (Provides relevant methodology for renewable energy structures).
  4. Martinez, J. A., & Walling, R. A. (2013). EMTP Modeling of Inverter-Based Resources for Power System Dynamic Studies. IEEE Transactions on Power Delivery.
  5. Vaisala. (2023). Annual Lightning Report 2022. [Online]. Available: https://www.vaisala.com
  6. Isola, G., et al. (2020). Advanced Surge Arrester Models for Fast Transient Simulations in EMTP. Electric Power Systems Research.

9. Analyst's Perspective: Core Insight & Critique

Core Insight

This paper correctly identifies a critical, yet often underestimated, fault line in the energy transition: the inherent conflict between optimal renewable siting and grid resilience. The authors pinpoint that the very regions boasting the highest solar yield (sunbelt areas) are frequently co-located with high isokeräunic levels (thunderstorm days per year). This isn't a minor coincidence; it's a fundamental siting dilemma. The research effectively shifts the narrative from viewing solar plants as passive, benign loads to recognizing them as active, vulnerable nodes that import and amplify grid-borne transients, threatening their own expensive power electronics—the inverters being the Achilles' heel.

Logical Flow

The paper's logic is robust and follows a classic engineering risk-assessment pathway: Hazard Identification → System Modeling → Consequence Simulation → Mitigation Evaluation. It starts with the plausible hazard (lightning on the transmission corridor), models its propagation through the complex RLC network of lines and plant cabling (using the industry-validated EMTP tool), quantifies the damaging consequence (overvoltage exceeding inverter BIL), and finally tests a standard mitigation tool (surge arresters). The inclusion of both Fourier and Hilbert-Huang Transform analysis adds a valuable layer, moving beyond simple peak voltage to understand the frequency-domain signature of the threat, which is more relevant for semiconductor durability.

Strengths & Flaws

Strengths: The methodological rigor is commendable. Using EMTP, the gold standard for transient studies, lends immediate credibility. Parameter variation (current, distance) provides a useful sensitivity analysis. The focus on spectral analysis is a step above many purely time-domain studies.

Critical Flaws & Missed Opportunities:

  • Economic Blind Spot: The study stops at technical efficacy. A glaring omission is a cost-benefit analysis. What is the CAPEX/OPEX of the recommended surge protection versus the risk of inverter failure (which can cost millions and incur months of downtime)? Without this, the recommendations lack actionable force for plant developers.
  • Static Modeling: The solar plant is modeled as a passive aggregate. In reality, inverters actively control voltage and frequency. Under a fast surge, their control loops can interact unpredictably with the transient, potentially worsening or mitigating the event. This dynamic inverter response is ignored, a simplification that limits real-world accuracy, as noted in dynamic studies by Martinez & Walling.
  • Single-Point-of-Failure Mindset: The solution is centralized (arrester at PCC). It neglects the potential for a distributed defense-in-depth strategy: coordinated arresters at the DC combiner boxes, inverter AC terminals, and transformer terminals, which is common practice in modern plant design to protect the entire energy conversion chain.

Actionable Insights

For utilities, developers, and OEMs:

  1. Mandate Site-Specific Transient Studies: Grid connection agreements for PV plants >20 MW in lightning-prone areas must require a detailed EMTP study like this one, not just a standard compliance checklist. This should be advocated to bodies like the IEEE PES.
  2. Develop "Renewable-Tailored" Arrester Specifications: MOV arrester standards (IEEE C62.11) are generic. Inverter manufacturers and arrester producers should collaborate to define optimized V-I characteristics and energy ratings for the unique wave shapes and duty cycles seen in PV applications.
  3. Integrate Lightning Data into Plant SCADA: Use real-time data from services like Vaisala's to implement an operational thunderstorm mode. When a cell is within 10 km, the plant could temporarily curtail or island if feasible, reducing risk exposure—a form of operational resilience inspired by grid-edge intelligence concepts.
  4. Fund Research on Active Clamping: The industry should invest in R&D for protection using SiC/GaN devices that can actively clamp voltages within microseconds, offering faster and more precise protection than passive MOVs, similar to how advanced drivers revolutionized power electronics in other fields.
In conclusion, this paper is a vital wake-up call that nails the problem definition but only partially solves it. Its real value lies in providing the foundational simulation evidence needed to drive more holistic, economically-grounded, and technologically advanced protection standards for the solar-dominated grid of tomorrow.