Lightning Strike Prediction Model for Power Grid Active Protection
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Solution Overview
Problem
Traditional lightning protection measures for transmission lines are passive and focus on design and installation, failing to predict and prevent lightning strikes effectively, especially in complex power grid networks, leading to significant losses when a transmission line with high strike probability is not anticipated before a storm.
Innovation Solution
A lightning prewarning-based method using a Bayesian network to predict strike probability, reconstructing node admittance matrices, and establishing a power flow transfer optimization model to regulate power flow before a strike, minimizing losses by active intervention when the strike risk is high.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional static lightning protection measures are used, then lightning resistance capability is improved, but the protection remains passive and cannot predict strikes in advance
Solution Approach 1:
The patent applies preliminary action by establishing a lightning strike probability prewarning model that predicts lightning risks before they occur. The model uses meteorological data and Bayesian networks to issue prewarnings, allowing the power system to take preventive measures in advance rather than relying solely on passive protection during actual strikes.
Solution Approach 2:
The patent implements feedback by continuously monitoring meteorological elements and updating the lightning strike probability in real-time. The prewarning model receives feedback from meteorological data and adjusts probability assessments, enabling dynamic adaptation to changing weather conditions and improving prediction accuracy.
2Loss of energy
If power flow regulation is performed before lightning strike, then load loss is reduced, but regulation cost increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting power flow parameters based on lightning strike probability prewarnings. When high probability is predicted, the system changes operational parameters such as power flow distribution and generator output to reduce exposure to potential lightning damage, balancing energy loss reduction with regulation costs.
Solution Approach 2:
The patent implements dynamics by making the power flow regulation strategy adaptive rather than static. The system dynamically adjusts regulation measures based on real-time lightning probability assessments, enabling flexible response to varying risk levels and optimizing the balance between load loss reduction and regulation cost.
3Loss of energy
If the transmission line is disconnected to prevent lightning damage, then strike loss is reduced, but power supply reliability deteriorates
Solution Approach 1:
The patent applies preliminary action by providing advance prewarnings of lightning strikes, allowing the system to prepare protective measures before disconnection becomes necessary. This early warning enables planned responses that maintain power supply reliability while preventing strike damage, rather than relying on abrupt disconnections.
Solution Approach 2:
The patent implements beforehand cushioning by establishing contingency plans and protective measures in advance of predicted lightning strikes. The system prepares regulatory strategies and alternative power flow paths before disconnection is needed, cushioning the impact on power supply reliability while still protecting against strike damage.
Data Source
AI summary
A lightning prewarning-based method for active protection against a lightning strike on an important transmission channel includes collecting meteorological element data, and establishing a transmission line-specific lightning strike probability prewarning model; using a maximum probability of a lightning strike prewarning level as a lightning strike prewarning level; performing equivalence calculation on a large-scale regional power system, using a minimum sum of a power loss risk cost and a regulation cost as an optimized objective function, and establishing a power flow transfer optimization model; and comparing a sum of a regulation cost and load power loss risk cost caused after the tie line is disconnected if regulation is performed before a lightning strike, and a load power loss risk cost caused if regulation is not performed, and when the regulation cost is not greater than the load power loss risk cost, performing regulation before the lightning strike.