Buffered-microgrid Structure for Future Power Networks; a Seamless Microgrid Control

This paper proposes a new structure and control scheme for future microgrid-based power system, which is designed to achieve a seamless operation in both islanded and grid-connected modes, while the load is appropriately shared by all units (i.e. renewable sources, energy storage systems and the grid). The proposed method, which involves physical separation of the microgrid from the grid by using AC/DC/AC converters, ensures safe, secure and seamless operation of both modes. Such a “buffered” structure enables reduction in the transmission losses by reducing the exchanged energy with the grid through using a dead-zone in the control of the buffering AC/DC/AC converter. An inverse-droop control technique has been implemented to control the voltage magnitude and frequency, using current control in the dq-frame. PSCAD/EMTDC software has been used to validate the proposed method through simulating different scenarios. The solution provides a simple, smooth, and communication-free decentralized control for multi-sources microgrids. Moreover, the proposed buffered structure separates the dynamics of the microgrid and the grid, which enables a faster microgrid voltage and frequency control and protects the grid and the microgrid from faults on the other side

False Data Injection Attacks Against Synchronization Systems in Microgrids

Synchronization systems play a vital role in the day-to-day operation of power systems and their restoration after cascading failures. Hence, their resilience to cyberattacks is imperative. In this paper, we demonstrate that a well-planned false data injection attack against the synchronization system of a generator is capable of causing tripping subsequently leading to instability and blackout. We present an analytical framework behind the design and implementation of the proposed cyberattack. Moreover, we derive and discuss the conditions for which a cyberattack interfering with a synchronizing signal can be successful. Effective physical mitigation strategies are then proposed to improve the cyber-resilience of synchronization systems. The proposed cyberattack model and mitigation strategies are verified for a microgrid test system using an OPAL-RT real-time simulator

Co-Optimization of Gas-Electricity Integrated Energy Systems Under Uncertainties

In the United States, natural gas-fired generators have gained increasing popularity in recent years due to low fuel cost and emission, as well as the needed large gas reserves. Consequently, it is worthwhile to consider the high interdependency between the gas and electricity networks. In this dissertation, several co-optimization models for the optimal operation and planning of gas-electricity integrated energy systems (IES) are proposed and investigated considering uncertainties from wind power and load demands. For the coordinated operation of gas-electricity IES: 1) an interval optimization based coordinated operating strategy for the gas-electricity IES is proposed to improve the overall system energy efficiency and optimize the energy flow. The gas and electricity infrastructures are modeled in detail and their operation constraints are fully considered. Then, a demand response program is incorporated into the optimization model, and its effects on the IES operation are investigated. Interval optimization is applied to address wind power uncertainty in IES. 2) a stochastic optimal operating strategy for gas-electricity IES is proposed considering N-1 contingencies in both gas and electricity networks. Since gas pipeline contingencies limit the fuel deliverability to gas-fired units, N-1 contingencies in both gas and electricity networks are considered to ensure that the system operation is able to sustain any possible power transmission or gas pipeline failure. Moreover, wind power uncertainty is addressed by stochastic programming. 3) a robust scheduling model is proposed for gas-electricity IES with uncertain wind power considering both gas and electricity N-1 contingencies. The proposed method is robust against wind power uncertainty to ensure that the system can sustain possible N-1 contingency event of gas pipeline or power transmission. Case studies demonstrate the effectiveness of the proposed models. For the co-optimization planning of gas-electricity IES: a two-stage robust optimization model is proposed for expansion co-planning of gas-electricity IES. The proposed model is solved by the column and constraint generation (C&CG) algorithm. The locations and capacities of new gas-fired generators, power transmission lines, and gas pipelines are optimally determined, which is robust against the uncertainties from electric and gas load growth as well as wind power