Coordinated Risk Mitigation Strategy For Integrated Energy Systems Under Cyber-Attacks

Abstract

The dramatic increase of cyber-attacks on energy systems can cause huge losses, which has drawn extensive attention due to the fast integration of information communication technologies (ICTs). This issue is becoming worse with the integration of electricity and gas systems (IEGS), facilitated by gas generation and new coupling technologies.This paper investigates the risk and mitigation strategies for IEGS under false data injection attacks (FDIA) in a hierarchical two-stage framework. The FDIA on both electricity and gas systems are modelled through injecting falsified data by adversaries. To mitigate the adverse impacts, a novel two-stage distributionally robust optimization (DRO) is proposed: i) day-ahead operation to determine initial operation scheme and ii) real-time corrective operation with the realization of FDIA and renewable generation uncertainties. A semidefinite programming is formulated for the original problem and it is then solved by a convex optimizationbased algorithm. A typical IEGS is used for demonstration, which shows that the proposed model is effective in mitigating the risks caused by potential FDIA and renewable uncertainties, by optimal coordinating energy infrastructures and load shedding. This work provides system operators with a powerful tool to operate the IEGS with enhanced security against malicious cyber-attacks while accommodating increasing renewable energy. The method can also be easily extended to operating IEGS against other natural attacks.

Economic-Effective Multi-Energy Management Considering Voltage Regulation Networked With Energy Hubs

“…, and , , . And the balancing conditions are given in (27) and (28) for active and reactive power, respectively. , and , are the active and reactive power demand.…”

“…And SO generally assumes the explicit uncertainty distribution based on a large number of scenario representations, which is computationally challenging. As an alternative of RO and SO, the novel distributionally robust optimization (DRO) can address the aforementioned problems based on the ambiguity-averse models considering partial distributional information [27][28][29][30].…”

Reactive Power Optimization in Integrated Electricity and Gas Systems

“…In (14), the substation voltage can be determined by OLTC tap position and the step size of each tap position. Constraint (15) regulates the total operation number of OLTC tap since too many operations will accelerate the wear process of the transformer [21][22][23]. In (16), the reactive power of PV is described by the forecasted active PV power output and the power factor as defined in (17).…”

“…Therefore, it is of necessity to handle the uncertainty through a relative less conservative optimization technique without requiring large datasets. As a promising optimization method to handle uncertainties, distributionally robust optimization (DRO) inherits the advantages of both RO and SO, overcoming the explicit assumptions on probability distributions of SO and over-conservatism of RO [14][15][16][17].…”

A Smart and Safe Electricity Consumption Model for Integrated Energy System Based on Electric Big Data

“…The behavior feature sets were utilized without data analysis or optimization. The effectiveness of these sets remains to be verified, against the target user samples [9][10][11][12][13][14][15].…”