Managing decisions for smart grid using interdependency modeling

Abstract

Critical infrastructures are vital complex systems for our lives. Electrical grids, gas pipelines, telecommunication networks and transportation roads are examples of those critical infrastructures. Furthermore, critical infrastructures are tightly interconnected one to another, and their interdependencies are more evident during adverse events, such as faults, natural disasters or cyber attacks. Making smart decisions is a hard task for operators. This paper wants to suggest a complete procedure for helping critical infrastructure operators in managing assets during adverse events. CISIApro simulator is an agentbased simulator able to evaluate the risk associated with the consequences of adverse events. The agent ability to produce resources is summarized into the concept of operative level. The output of CISIApro, related to the power infrastructure, is used as input of the unit commitment algorithm as an example of decision making algorithm. In this paper, the unit commitment includes network topology security constraints and a risk-based objective function. This process is validated by means of a reference scenario made of four interconnected infrastructures, within a regional area. Results are presented in order to understand how unit commitment can suggest different solutions based on different risk assessment

From Detecting Cyber-Attacks to Mitigating Risk Within a Hybrid Environment

“…This article also analyses how increasing situation aware- ness improves the response capabilities and the decision process. As demonstrated in [26], including data on the propagation of an adverse event and their consequences on equipment and services improves the resilience and the response time of the considered infrastructures through suitable mitigation algorithms. The output of CISIApro can be included in an optimization algorithm for improving the decision process considering also events that are not within the infrastructure.…”

“…The main advantage of this simulator is the great flexibility of the modeling approach: CISIApro is able to consider several interdependent infrastructures, electrical grid, gas networks, water distribution, telecommunications and rail road systems, as in [26], [43]. The operational mode can be both centralized and distributed.…”

“…In addition, thanks to specific software adapters, the output of CISIApro can be exposed as a service to feed other processes, such as Decision Support Systems (DSS) or other Risk-assessment tools. For an example of this architecture, please refer to [26], [43].…”

Enhancing Decision Support with Interdependency Modeling

“…Bu and Yu [1] have solved this problem using a game-theoretic decision making scheme for electricity retailers in the smart grid using real-time demand-side management. The methodology described in this chapter implements a security-constrained unit commitment algorithm along with a novel risk based objective function [9] to manage demand and response in power grids.…”

“…The unit commitment problem [9] involves the determination of the startup and shutdown schedules of generating units to meet the forecasted demand in a future short-term period (usually between 24 and 168 hours). The objective is to minimize the total production costs while satisfying a number of operating constraints.…”