Techno-economic hardening strategies to enhance distribution system resilience against earthquake

• Published in: Reliability engineering & system safety 2021-09, Vol.213, p.107682, Article 107682
• Main Authors: Venkateswaran V, Balaji, Saini, Devender Kumar, Sharma, Madhu
• Format: Article
• Language: English
• Subjects: Algorithms; Clustering; Distribution System Hardening; Earthquakes; Energy storage; Energy Storage Units (ESUs); Fragility; Geological hazards; Hardening; Mixed integer; Monte Carlo simulation; Natural disasters; Power System Planning; Reliability engineering; Resilience; Seismic activity; Seismic hazard; Seismic zones; Storage units; Survivability; Underground cables; Underground storage
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2021.107682

•Proposed framework combines grid-side & demand-side measures to enhance resilience.•Monte-Carlo based probabilistic earthquake hazard model is developed.•Three-dimensional hardening methodology is proposed to enhance system resilience.•Case study is conducted on practical distribution system of Dehradun, India. The electrical distribution grid is unremittingly vulnerable to natural disasters. Many researchers propose strategies mainly based on grid-side solutions to improve critical load's survivability during the targeted emergency period. However, the main agenda of resilience enhancement is to improve the overall system resilience. Therefore, this paper proposes a proactive framework that combines the grid-side and demand-side solutions to enhance the overall system resilience. Here, the grid-side approach presents optimal hardening of the distribution grid by using resilient energy storage units (ESUs), underground cables (UCs), and the demand-side by using home battery inverters (HBIs) & its communication infrastructure. For resilient hardening against earthquakes, it is essential to identify it's all possible occurrences. Therefore, a Monte-Carlo-based probabilistic earthquake hazard model is developed through which the vulnerability is characterized using the peak ground acceleration (PGA) model and fragility curves. For optimized hardening investments, the vulnerable zones of the system are identified via clustering algorithms. With the formulated mixed-integer nonlinear problem, the optimal ESUs and UCs are identified for each cluster. The proposed methodology is tested on a real-world 156-bus distribution system of Dehradun district, India, under seismic zone IV.