High penetration of renewable energy sources will cause crucial challenges for future energy systems. This study presents a three-level model for adaptive robust expansion co-planning of electricity and natural gas infrastructures in multienergy-hub networks, which is robust against uncertainties of maximum production of wind generation and gas-fired power plants as well as estimated load levels. The proposed min-max-min model is formulated as a mixed integer linear programming problem. The first level minimises the investment cost of electricity and natural gas infrastructures, the worst possible case is determined through the second level, and the third level minimises the overall operation cost under that condition. To solve this model, the final minimisation problem is replaced by its Karush-Kuhn-Tucker conditions and a two-level problem is determined. Finally, by using the column and constraint generation algorithm the original problem is decomposed to master and subproblems and the optimal solution is derived iteratively. The proposed robust expansion co-planning model is tested on modified Garver's 6-hub, modified IEEE RTS 24-hub, and modified IEEE 118-hub test systems and numerical results show its effectiveness to cope with uncertainties with regard to control conservativeness of the plan.
The growing interconnection between information networks and power grids enables a more efficient and economical operation, but also introduces significant challenges in modern cyber-physical power systems, such as malicious cyber-attacks. Several cyber-attacks have been reported in the recent decade, affecting hundreds of thousands of people. These attacks can lead to large power system blackouts, and optimization models are essential tools for optimal decision-making in reliable and secure operation of cyber-physical power systems. In this paper, optimization models in cyber-physical power systems are extensively reviewed and classified based on their applications, including cyber-security and optimal operation. One major application of optimization is in cyber-security evaluation of smart grids. This paper investigates the models to implement cyber-attacks against state estimation, coordinated cyber-physical attacks aiming to cover each other, and financially-motivated attacks in electricity markets; optimal defense strategies and interactions between the attacker and the defender are also introduced. Furthermore, optimization models used in the operation and dispatching of cyber-physical power and energy systems, optimal routing of information networks, and privacy-preserving models are presented. Finally, as solving optimization models is a crucial step in optimal decision-making, solvers in the literature are also introduced.
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