Optimization of Renewable Energy Allocation to Reduce Network Vulnerability Risk Under Intentional Transmission Attacks

Abstract

Intentional physical attacks on a wide-ranging transmission network may result in load shedding or outages in the electrical grid. This vulnerability can be mitigated through modern transmission expansion planning that takes into account grid risk and renewable energy penetration. This research introduces a novel approach to optimally reduce the network’s vulnerability to intentional transmission attacks by combining game-theoretic sequential attacker-defender model analysis with power flows and probabilistic risk analysis. This innovative method allocates defender resources based on location and size optimization under a budget constraint. The defender or network planner utilizes renewable energy technologies, such as photovoltaics and batteries, as non-wire expansion alternatives based on their power system reliability and environmental friendliness. This research was implemented on three modified IEEE bus test systems: the 14-bus, 39-bus, and 118-bus test systems. In Case 1, an investment in photovoltaics outperforms Case 2, where the defender integrates photovoltaics with batteries. In the 14-bus scenario of Case 1, the network vulnerability risk is reduced from 112.3 MW to 58.78 MW; in the 39-bus scenario, it decreases from 298.78 MW to 79.9 MW, and in the 118-bus scenario, it drops from 48.3 MW to 29.81 MW. The study demonstrates that the optimal allocation of defender resources can reduce the risk in exponential cost models. Integrating renewable energy at the grid scale will be crucial for the future expansion of power grids.

Keywords

• Game theory sequential attacker defender
• network vulnerability risk
• non-wire expansion planning
• power flows
• probabilistic risk analysis
• renewable energy