Yanling Lin

Battling the Extreme: A Study on the Power System Resilience

The electricity infrastructure is a critical lifeline system and of utmost importance to our daily lives. Power system resilience characterizes the ability to resist, adapt to, and timely recover from disruptions. The resilient power system is intended to cope with low probability, high risk extreme events including extreme natural disasters and man-made attacks. With an increasing awareness of such threats, the resilience of power systems has become a top priority for many countries. Facing the pressing urgency for resilience studies, the objective of this paper is to investigate the resilience of power systems. It summarizes practices taken by governments, utilities, and researchers to increase power system resilience. Based on a thorough review on the existing metrics system and evaluation methodologies, we present the concept, metrics, and a quantitative framework for power system resilience evaluation. Then, system hardening strategies and smart grid technologies as means to increase system resilience are discussed, with an emphasis on the new technologies such as topology reconfiguration, microgrids, and distribution automation; to illustrate how to increase system resilience against extreme events, we propose a load restoration framework based on smart distribution technology. The proposed method is applied on two test systems to validify its effectiveness. In the end, challenges to the power system resilience are discussed, including extreme event modeling, practical barriers, interdependence with other critical infrastructures, etc.

A New Model for Resilient Distribution Systems by Microgrids Formation

Forming multiple micorgrids with distributed generators offers a resilient solution to restore critical loads from natural disasters in distribution systems. However, more dummy binary and continuous variables are needed with the increase of the number of microgrids, which will therefore increase the complexity of this model. To address this issue, this letter presents a new model to reformulate the micorgrid formulation problem in resilient distribution networks. Compared with the traditional model, the number of both binary and continuous variables is greatly reduced, such that the computational performance is significantly improved. Numerical results on IEEE test systems verify the effectiveness of the proposed model.

Smart Grid in China: a promising solution to China’s energy and environmental issues

Smart Grid presages an advanced power grid that revolutionizes the century-old traditional power grid and the way mankind uses energy. In China, the pressure on the current grid exerted by growing demand, environmental issues and the unbalanced energy use structure makes the transition to a ‘smarter’ and ‘cleaner’ grid inevitable. This paper firstly contrasts the concepts and research priorities of Smart Grid of China and other developed countries; then turns to the situation of Chinese energy and power use. China has the largest generating capacity, 79% of which is coal-fired plants. And China is also the largest carbon emitter in the world. Despite the challenges, China is also the most promising market for Smart Grid. The components of Smart Grid, especially the development of renewable energy, electric vehicles and smart substation are reinforced in the Chinese 12th Five-Year Plan (2011–2015). The paper examines also efforts by government, power utilities and research institutes. The paper concludes that developing Smart Grid will be beneficial both to China and the world.

Researches on the reliability evaluation of integrated energy system based on Energy Hub

In this paper, the concept of Energy Hub was introduced to capture the coupling between multiple energy forms such as electricity, gas, heat and cooling in an Integrated Energy Systems (IESs). The reliability model for Energy Hubs was established based on a Smart Agent Communication (SAC) algorithm. In the model, the energy conversion efficiency, failure rate and repair time for various energy supply systems were considered, and thus the effects of coupling among different energy types on the IES reliability were taken into account. According to the SAC algorithm, an Energy Hub was defined as a smart agent which can communicate with other smart agent. Combined with the Monte Carlo simulation, a reliability evaluation approach is presented based on the SAC algorithm and Energy Hub model. In the presented approach, fault localization, fault isolation, system reconfiguration and fault recovery can be implemented autonomously, which effectively improves the system status assessment efficiency during the reliability evaluation of IESs. Finally, the proposed models and approaches are applied on the multi-paradigm modeling and simulation platform-AnyLogic, and the effectiveness of the model is validated by extensive cases studies.

A new method to evaluate maximum capacity of photovoltaic integration considering network topology reconfiguration

As photovoltaic (PV) integration increases in distribution systems, an effective way of assessing the maximum allowable PV integration capacity is urgently needed. In this paper, a new method is proposed to evaluate the maximum PV integration capacity with AC power flow limits, and the effect of topology reconfiguration on PV integration is also considered. In addition, the single commodity flow constraint is put forward to guarantee topology radiality. Usually, this problem requires mix integer non-convex optimization, which is a great challenge to solve. To address this problem, second order cones are employed to relax the non-convex constraints so that the model can be efficiently solved. Furthermore, the IEEE 33-bus test system with four PV integration cases for maximum integration capacity is studied. The test result shows the effectiveness of reconfiguration in increasing maximum PV integration capacity.