Gengfeng Li

Reliability Evaluation of Active Distribution Systems Including Microgrids

This paper proposes a new method for reliability evaluation of active distribution systems with multiple microgrids based on a Monte Carlo simulation. Multi-state models are developed on the basis of Generalized Capacity Outage Tables (GCOTs) to better represent various types of distributed generators in reliability evaluation. Then, the virtual power plant (VPP) is introduced to model microgrids with intermittent sources. Furthermore, the reliability behavior of VPP is efficiently characterized by an equivalent GCOT. The nonsequential Monte Carlo method is then adopted to evaluate the reliability of active distribution systems considering different operation modes under single or multiple contingencies. Some techniques - such as two-step state sampling, zone partitioning and minimal path search - are proposed to facilitate the state evaluation process and improve the Monte Carlo simulation speed. The effectiveness and efficiency of the proposed method are validated through extensive numerical tests on an IEEE test system and a real-life active distribution network.

Risk Analysis for Distribution Systems in the Northeast U.S. Under Wind Storms

Summary form only given. With the growing trend of extreme weather events in the Northeast U.S., a region of dense vegetation, evaluating hazard effects of wind storms on power distribution systems becomes increasingly important for disaster preparedness and fast responses in utilities. In this paper, probabilistic wind storm models for the study region have been built by mining 160-year storm events recorded in the National Oceanic and Atmospheric Administrations Atlantic basin hurricane database (HURDAT). Further, wind storms are classified into six categories according to NOAA criteria and IEEE standard to facilitate the evaluation of distribution system responses under different levels of hazards. The impacts of wind storms in all categories are accurately evaluated through a Sequential Monte Carlo method enhanced by a temporal wind storm sampling strategy. Extensive studies for the selected typical distribution system indicate that our models and methods effectively reveal the hazardous effects of wind storms in the study region, leading to useful insights towards building better system hardening schemes.

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.

Reliability evaluation of distribution systems including micro-grids considering demand response and energy storage

The integration of micro-grids has changed the radial configuration of distribution systems. Flexible operation modes of micro-grids, the incorporation of demand response and energy storage devices have render traditional distribution system reliability evaluation method obsolete. Based on a sequential probabilistic model of wind generators, a piecewise price model for distribution systems considering renewable energy penetration level is proposed in this paper. Then, a reliability model of the load incorporating demand response is developed based on the piecewise price model. Furthermore, a charging/discharging management model of energy storage devices considering micro-grid operation modes is determined. Sequential Monte-Carlo simulation and minimal path method are adopted to evaluate reliability of distribution systems including micro-grids. The validity of above models and methodology is examined through numerical tests on modified RBTS.

Modeling of DFIG based wind generator and transient characteristics analysis

As a renewable, clean energy, wind energy has attract more and more attention. It has become a common understanding of the world to vigorously develop wind energy. In order to guarantee the safety and reliability for wind power integration operation, it is of great significance to establish an appropriate wind power generator system model and analyze its electromagnetic transient characteristics. This paper analyzes the control strategy of doubly-fed induction generator (DFIG) based wind generator. Vector decoupling control technology has been adopted to establish the mathematical model of DFIG based wind generator. Furthermore, an electromagnetic dynamic simulation model of DFIG based wind generator is established based on the platform of PSCAD/EMTDC. A short circuit fault is simulated to study the dynamic response of DFIG based wind generator. Finally, transient characteristic of DFIG is analyzed by this paper.

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.

Analysis of wind power integration capacity in wind-hydro-thermal hybrid power system

An improved analysis approach for wind power integration capacity (WPIC) is proposed. In this paper, WPIC is composed of two parts, one provided by hydro power and the other provided by thermal power. After proper consideration of wind power randomness, WPIC provided by hydro power is determined by the regulation ability of reservoir in hydro power plants. Then, a concept of equivalent thermal power units output duration curve is proposed to accurately evaluate WPIC provided by thermal power in a probabilistic perspective. Numerical tests are conducted on Gansu power grid in 2015. Monthly WPIC under different scenarios are determined, which validates the effectiveness of this approach.

Eliminating Redundant Line Flow Constraints in Composite System Reliability Evaluation

Reliability evaluation of composite systems involves extensive calculations. Current solutions to this computational burden have mainly focused on extracting failure states from the state space. Instead, the evaluation of failure states is accelerated by methods presented in this paper. The scale of optimizations required for generation redispatching and/or load shedding in failure states is reduced by eliminating redundant line flow constraints. First, a sufficient and necessary condition for a line flow constraint to be redundant is established in the form of a linear programming problem, based on the concept of steady-state security region (SSR). Then, two redundancy elimination methods are proposed-a conservative one based on a heuristic, and a radical one based on an analytical condition. Numerical tests are conducted on IEEE-RTS79 and a real-life system. More than half of the line flow constraints are eliminated by the conservative method and nearly 90% by the radical method. The proposed methods can be used in conjunction with most of the existing acceleration techniques to further improve efficiency.

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.