@article{li_du_lu_2018, title={Design of a New Primary Frequency Control Market for Hosting Frequency Response Reserve Offers From Both Generators and Loads}, volume={9}, ISSN={["1949-3061"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000443200700086&KeyUID=WOS:000443200700086}, DOI={10.1109/TSG.2017.2674518}, abstractNote={This paper presents the design of a new primary frequency control (PFC) market for hosting frequency response reserve (FRR) offers from both generators and loads. Traditionally, FRR is provided by synchronous generators. Advanced control and monitoring technologies have enabled loads to provide fast and discrete PFC, which is complementary to the slow and continuous governor response provided by synchronous generators. In this paper, the performance of the PFC provided by the load is benchmarked by the equivalent amount of PFC provided by the synchronous generators at each typical system inertia condition using the actual dynamic network models and operation data of the Electric Reliability Council of Texas (ERCOT) system. Then, a new real-time PFC market mechanism is proposed to accept and value the PFC offers from both generators and loads. A few case studies are presented to illustrate the new market mechanism and demonstrate its effectiveness for mitigating price spikes. The results of this paper are applicable to other low-inertia power grids similar to the ERCOT system for procuring ancillary services that are essential to host high penetration of renewable resources.}, number={5}, journal={IEEE TRANSACTIONS ON SMART GRID}, author={Li, Weifeng and Du, Pengwei and Lu, Ning}, year={2018}, month={Sep}, pages={4883–4892} }
 @article{jiang_mu_jia_lu_yuan_yan_li_2016, title={A Novel Dominant Mode Estimation Method for Analyzing Inter-Area Oscillation in China Southern Power Grid}, volume={7}, ISSN={["1949-3061"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000391722100038&KeyUID=WOS:000391722100038}, DOI={10.1109/tsg.2016.2533621}, abstractNote={This paper proposes a new approach to estimate dominant mode for monitoring inter-area oscillation in the China Southern power grid (CSG) by the use of phasor measurement units (PMUs) under both ringdown and ambient conditions. The state space model is identified by the data driven stochastic subspace identification (Data-SSI) algorithm. The canonical variate algorithm is used first to construct the weighted projection matrix of the Data-SSI. Then, the criterion for model order selection is developed to estimate the model order, and the linear model of power system is built with Data-SSI. The dominant oscillation modes are calculated by eigenvalue analysis. To accurately identify the dominant modes, repetitive results are calculated with model order variation, and then clustering analysis and stepwise refinement are applied to discriminating the dominant modes from trivial ones to improve the estimation accuracy. Field-measurement data collected by PMUs in CSG is used to validate the proposed algorithm. The comparison between existing mode estimation techniques and the proposed approach demonstrates its accuracy and robustness under both ringdown and ambient conditions.}, number={5}, journal={IEEE TRANSACTIONS ON SMART GRID}, author={Jiang, Tao and Mu, Yunfei and Jia, Hongjie and Lu, Ning and Yuan, Haoyu and Yan, Jiahong and Li, Weifeng}, year={2016}, month={Sep}, pages={2549–2560} }
 @article{du_li_ke_lu_ciniglio_colburn_anderson_2015, title={Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources}, volume={6}, ISSN={["1949-3029"]}, url={http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000361680800010&KeyUID=WOS:000361680800010}, DOI={10.1109/tste.2015.2425354}, abstractNote={This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.}, number={4}, journal={IEEE TRANSACTIONS ON SUSTAINABLE ENERGY}, author={Du, Pengwei and Li, Weifeng and Ke, Xinda and Lu, Ning and Ciniglio, Orlando A. and Colburn, Mitchel and Anderson, Phillip M.}, year={2015}, month={Oct}, pages={1263–1271} }