This study proposes a cooperative secondary voltage and frequency control strategy to reduce the number of controller updates by using an event-triggered approach. The proposed approach is applied to the secondary control that will offset primary control deviations in islanded microgrids with limited computation resources. The controller updating mechanism considered here is event-triggered which judges whether a certain measurement error has reached the event-triggered condition (ETC) associated with the norm of a function with a standard state. We consider two secondary control options to form an ETC, which include a centralized strategy in which an auxiliary controller would collect all agents’ states, and a distributed control strategy which only require the neighboring agents information. The corresponding stability and convergence analyses are presented and simulation results for an islanded microgrid test system consisting of four distributed generators (DGs) are provided. The simulation results validate the effectiveness of the proposed control strategies and show that the proposed strategies based on an event-triggered approach can dramatically reduce controller updates.

Reliable power grids are also vulnerable to extreme events, which are with a low probability but highly risk events, such as a typhoon. Power system, as an important infrastructure, should have the ability to withstand the adverse effect of such extreme events. This paper proposes a quantitative resilience assessment framework for power transmission systems operated under typhoon weather, which considers both the spatial and temporal impacts of typhoon. The proposed framework allows systematic estimation of resilience considering weather intensity, fault location of components, restoration resources, and emergency response plans. The typhoon wind field model for disaster risk assessment is applied to evaluate the intensity and the duration of impacts. The finite element modeling of components is developed to model the outage probability of components. A new resilience index considering the duration of extreme events (RICD) is proposed, which not only considers the performance of system but also considers characteristics of disruption. The proposed method is demonstrated by four case studies using the modified IEEE 6-bus test system. The numerical results reveal that the proposed method is able to quantify the influence of extreme event on power system resilience, and it shows that RICD is more feasible than two traditional indices in terms of normalization and comparability.

Daily peak load forecasting is an essential tool for decision making in power system operation and planning. However, the daily peak load is a nonlinear, nonstationary and volatile time series, which makes it difficult to be forecasted accurately. This paper, for the first time, proposes a bespoke gated recurrent neural network combining dynamic time warping (DTW) for accurate daily peak load forecasting. The shape-based DTW distance is used to match the most similar load curve, which can capture trends in load changes. By analyzing the relationship between the load curve and the cycle of human social activities, the some-hot encoding scheme is firstly applied on the discrete variables to expand the features to further characterize their impact on load curves. Then a 3-layer gated recurrent neural network is developed to forecast daily peak load. The proposed algorithm is implemented on the Theano deep learning platform and tested on the load dataset of the European Network on Intelligent Technologies (EUNITE). The simulation results show that the proposed algorithm achieves satisfactory results compared with other algorithms using the same dataset in this study

In this paper, a new topology of two-stage cascaded switched-diode (CSD) multilevel inverter is proposed for medium-voltage renewable energy integration. First, it aims to reduce the number of switches along with its gate drivers. Thus, the installation space and cost of a multilevel inverter are reduced. The spike removal switch added in the first stage of the inverter provides a flowing path for the reverse load current, and as a result, high voltage spikes occurring at the base of the stepped output voltage based upon conventional CSD multilevel inverter topologies are removed. Moreover, to resolve the problems related to dc source fluctuations of multilevel inverter used for renewable energy integration, the clock phase-shifting (CPS) one-cycle control (OCC) is developed to control the two-stage CSD multilevel inverter. By shifting the clock pulse phase of every cascaded unit, the staircase-like output voltage waveforms are obtained and a strong suppression ability against fluctuations in dc sources is achieved. Simulation and experimental results are discussed to verify the feasibility and performances of the two-stage CSD multilevel inverter controlled by the CPS OCC method.