Guojie Li

Review on frequency control of power systems with wind power penetration

The increasing penetration of wind power may influence the frequency stability of power systems. Therefore, new control schemes are necessary for wind turbines and power systems to support the frequency control. Currently, most of the published control methods can be classified into 3 levels, i.e., wind turbine level, wind farm level and power system level. The wind turbine level control enables wind turbines, particularly the variable speed wind generators, to provide dynamic response and power reserves for the primary frequency control by implementing the inertial, droop or deloading controller. The wind farm level control distributes the central control command from the system to the local wind turbines and energy storage units for the desired generation. The power system level control coordinates wind farms with conventional power plants for the secondary control to recover the frequency to the reference value faster than for the no coordination control case. This paper presents a review on the latest studies in relation to the 3-level frequency control of power systems with wind power penetration.

Design a Fuzzy Controller to Minimize the Effect of HVDC Commutation Failure on Power System

Commutation failure, which is a very frequent dynamic event in HVDC inverters, can deteriorate the availability of HVDC links and thus affect the performance of the power system. Most commutation failures are caused by voltage reduction due to ac system faults. In this paper, efforts are made to lower the effect of commutation failure on the power system, and the remedy is implemented in a fuzzy controller. In order to achieve control flexibility, the output of the fuzzy controller is made appropriate by setting a self-adjusting proportional factor. The validity and effectiveness of the fuzzy controller is verified by simulation which shows that the fuzzy controller can decrease commutation failure frequency induced by ac system faults.

A review on analysis and control of small signal stability of power systems with large scale integration of wind power

With the large scale penetration of wind power connected into power systems, it is of critical importance to investigate the influence of wind farms on the small signal stability of power systems and then develop appropriate control strategies to improve small signal stability. This paper provides an overview of recent progresses on the impact of the integration of large amounts of wind power on power system small signal stability and corresponding control strategies to enhance small signal stability. First, the concept of small signal stability and different types of wind turbine generators (WTGs) are introduced. In the second part, various viewpoints with respect to the effect of WTGs on power system small signal stability are presented. Finally, a variety of auxiliary controllers to amend small signal stability are summarized. On that basis, the issues for further study are prospected.

Energy scheduling and allocation in electric vehicle energy distribution networks

The energy storage of Electric Vehicles (EVs) can be utilized by Smart Grid through Vehicle-to-Grid (V2G) that allows EVs to feed energy stored in their batteries back to the grid as needed. Combining V2G and the mobility of vehicles, EVs can provide a natural energy transmission system called EV energy network. The main idea of this paper focus on how to schedule and allocate energy from energy sources to places where energy is needed. The features of energy route in EV energy network are analyzed and a greedy algorithm based on the hypergraph is presented. Simulations using real-world transporting data in Manhattan and the Pioneer Valley Transit Authority(PVTA). Simulations show that this method is efficient.

A Versatile Probability Model of Photovoltaic Generation Using Pair Copula Construction

Photovoltaic (PV) generation is increasingly popular in power systems. The nonlinear dependence associated with a large number of distributed PV sources adds the complexity to construct an accurate probability model and negatively affects confidence levels and reliability, thereby resulting in a more challenging operation of the systems. Most probability models have many restrictions when constructing multiple PV sources with complex dependence. This paper proposes a versatile probability model of PV generation on the basis of pair copula construction. In order to tackle the computational burden required to construct pair copula in high-dimensional cases, a systematic simplification technique is utilized that can significantly reduce the computational effort while preserving satisfactory precision. The proposed method can simplify the modeling procedure and provide a flexible and optimal probability model for the PV generation with complex dependence. The proposed model is tested using a set of historical data from colocated PV sites. It is then applied to the probabilistic load flow (PLF) study of the IEEE 118-bus system. The results demonstrate the effectiveness and accuracy of the proposed model.

Effect of Erroneous Position Measurements in Vector-Controlled Doubly Fed Induction Generator

Vector control of the doubly fed induction generators (DFIGs) depends on accurate information from a stator voltage phase lock loop (PLL) and a rotor position encoder for the reference frame transformations required by theory. The effect of erroneous information due to noise picked up by commonly used hardware PLLs and incremental position encoders was analyzed in this paper. The analysis shows that erroneous information can give rise to destructively large currents due to: 1) the DFIG system wrongfully perceiving very large P and Q references; and 2) system instability. It is shown that instability does not arise from inside the inner current feedback loop, but from the outer feedback loop that regulates the complex power. Simulation and experimental test results validate the analysis. The experimental results are taken from a 1.5-MW DFIG intended for a wind turbine. A simple scheme to protect against the erroneous information has been tested successfully in a brief trial period.

Versatile distribution of wind power output for a given forecast value

The wind power output distribution for a given forecast value is often described by a theoretical distribution, such as Gaussian, Beta and Cauchy. However, the theoretical distributions could hardly simulate the actual wind power uncertainty for all situations. Moreover, the cumulative distribution function (CDF) or quantile function is more concerned by system operators than the probability density function (PDF). Nonetheless, the CDF of a theoretical distribution usually could not be expressed in a closed form and is commonly derived from the numerical integral of PDF. The estimation error of PDF may hence be cumulatively enlarged through the numerical integral process. Given this background, this paper presents a versatile distribution model that can simulate any shape of the actual distributions of wind power forecast errors. The CDF of the versatile distribution could be written as a closed form so it can be directly applied on fitting the actual CDF. The mathematical feature of the versatile distribution can also facilitate the dispatching decision-making and benefit power system analysis. The results demonstrate the feasibility and effectiveness of the proposed distribution model.

A novel nonlinear control for stability improvement in HVDC light system

HVDC light is more and more concerned recently to improve power system stability due to controllability of its IGBT valve. In this paper, a model of HVDC light system is established and analyzed. And a nonlinear control to enhance HVDC Light system stability is proposed. The digital simulation results show that the proposed nonlinear control is effective to damp system oscillations and enhance system stability. Furthermore, digital simulation studies are conducted using the well-established PSCAD/EMTDC software package to show the effectiveness of the proposed nonlinear controller in damping oscillations when plow flow reversed.

Robustness analysis on electric vehicle energy distribution networks

Electric Vehicles (EVs) can be used as a medium between the battery energy stored in EVs and the power grid through Vehicle-to-Grid (V2G). Combined with the characteristic that vehicles are mobile, EVs can provide a natural energy transmission system called EV energy network. This paper analyzes the features of energy routes in the EV energy network and studies the impact of traffic congestion on the EV energy distribution networks. Based on the characteristics of traffic congestion in the urban, sporadic congestion algorithm and recurring congestion algorithm are presented to simulate in a model of the EV energy network. Additionally, energy degree (ED) and energy source available rate (ESAR) are defined to reflect the current state of the EV energy network. The real-world transporting data in Manhattan and Pioneer Valley Transit Authority (PVTA) is utilized to analyze the robustness of the proposed EV energy network.

Applying probabilistic collocation method to power flow analysis in networks with wind farms

In power systems with a high wind power penetration, probabilistic load flow analysis is a fundamental problem for system planning and operation due to the uncertainty and fast fluctuation of wind speed. This paper proposes probabilistic collocation method (PCM) for load flow analysis with a penetration of wind farms. The orthogonal polynomials are utilized to generate the approximation of the random variable of interest as the function of uncertainty parameters. The proposed method is a computational efficient solution to provide quite an accurate approximation for the given probability distribution of system response. Therefore the method can significantly reduce the computational time compared to the traditional brute force Monte Carlo approach. Illustration examples are given on the IEEE 39 bus system to show the effectiveness of the proposed method.