Contingency-constrained economic dispatch with safe reinforcement learning

Future power systems will rely heavily on micro grids with a high share of decentralised renewable energy sources and energy storage systems. The high complexity and uncertainty in this context might make conventional power dispatch strategies infeasible. Reinforcement-learning based (RL) controllers can address this challenge, however, cannot themselves provide safety guarantees, preventing their deployment in practice. To overcome this limitation, we propose a formally validated RL controller for economic dispatch. We extend conventional constraints by a time-dependent constraint encoding the islanding contingency. The contingency constraint is computed using set-based backwards reachability analysis and actions of the RL agent are verified through a safety layer. Unsafe actions are projected into the safe action space while leveraging constrained zonotope set representations for computational efficiency. The developed approach is demonstrated on a residential use case using real-world measurements

Distributed Contingency Analysis over Wide Area Network among Dispatch Centers

Traditionally, a regional dispatch center uses the equivalent method to deal with external grids, which fails to reflect the interactions among regions. This paper proposes a distributed N-1 contingency analysis (DCA) solution, where dispatch centers join a coordinated computation using their private data and computing resources. A distributed screening method is presented to determine the Critical Contingency Set (DCCS) in DCA. Then, the distributed power flow is formulated as a set of boundary equations, which is solved by a Jacobi-Free Newton-GMRES (JFNG) method. During solving the distributed power flow, only boundary conditions are exchanged. Acceleration techniques are also introduced, including reusing preconditioners and optimal resource scheduling during parallel processing of multiple contingencies. The proposed method is implemented on a real EMS platform, where tests using the Southwest Regional Grid of China are carried out to validate its feasibility.Comment: 5 pages, 6 figures, 2017 IEEE PES General Meetin

Wide-area monitoring and control of future smart grids

Application of wide-area monitoring and control for future smart grids with substantial wind penetration and advanced network control options through FACTS and HVDC (both point-to-point and multi-terminal) is the subject matter of this thesis. For wide-area monitoring, a novel technique is proposed to characterize the system dynamic response in near real-time in terms of not only damping and frequency but also mode-shape, the latter being critical for corrective control action. Real-time simulation in Opal-RT is carried out to illustrate the effectiveness and practical feasibility of the proposed approach. Potential problem with wide-area closed-loop continuous control using FACTS devices due to continuously time-varying latency is addressed through the proposed modification of the traditional phasor POD concept introduced by ABB. Adverse impact of limited bandwidth availability due to networked communication is established and a solution using an observer at the PMU location has been demonstrated. Impact of wind penetration on the system dynamic performance has been analyzed along with effectiveness of damping control through proper coordination of wind farms and HVDC links. For multi-terminal HVDC (MTDC) grids the critical issue of autonomous power sharing among the converter stations following a contingency (e.g. converter outage) is addressed. Use of a power-voltage droop in the DC link voltage control loops using remote voltage feedback is shown to yield proper distribution of power mismatch according to the converter ratings while use of local voltages turns out to be unsatisfactory. A novel scheme for adapting the droop coefficients to share the burden according to the available headroom of each converter station is also studied. The effectiveness of the proposed approaches is illustrated through detailed frequency domain analysis and extensive time-domain simulation results on different test systems

Geometry-based Estimation of Stability Region for A Class of Structure Preserving Power Grids

The increasing development of the electric power grid, the largest engineered system ever, to an even more complicated and larger system requires a new generation of stability assessment methods that are computationally tractable and feasible in real-time. In this paper we first extend the recently introduced Lyapunov Functions Family (LFF) transient stability assessment approach, that has potential to reduce the computational cost on large scale power grids, to structure-preserving power grids. Then, we introduce a new geometry-based method to construct the stability region estimate of power systems. Our conceptual demonstration shows that this new method can certify stability of a broader set of initial conditions compared to the minimization-based LFF method and the energy methods (closest UEP and controlling UEP methods)

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

Robustness of the European power grids under intentional attack

The power grid defines one of the most important technological networks of our times and sustains our complex society. It has evolved for more than a century into an extremely huge and seemingly robust and well understood system. But it becomes extremely fragile as well, when unexpected, usually minimal, failures turn into unknown dynamical behaviours leading, for example, to sudden and massive blackouts. Here we explore the fragility of the European power grid under the effect of selective node removal. A mean field analysis of fragility against attacks is presented together with the observed patterns. Deviations from the theoretical conditions for network percolation (and fragmentation) under attacks are analysed and correlated with non topological reliability measures.Comment: 7 pages, 4 figure