Naresh Acharya

Fast contingency screening and ranking for small signal stability assessment

Utilities today are in need of tools and techniques that will enable them to predict the dynamic stability and reliability of the grid in the real-time. The problem is challenging because of the large number of contingencies that are to be simulated. In this paper a fast method for power system contingency screening and ranking for small signal stability assessment is presented which essentially reduces the number of contingencies for detailed evaluation. The proposed method avoids repeated computation of eigenvalues for all possible post-contingency scenarios. Instead, the eigenvalues corresponding to critical modes for post-outage conditions are estimated based on first-order eigenvalue-sensitivity using just the nominal condition eigenvalues and post outage system state matrices. Since a critical outage condition can produce a large change in the eigenvalues, the first order prediction might not have acceptable accuracy. To overcome this issue, a second-order correction is applied which needs the computation of the eigenvectors corresponding to the eigenvalues of interest. A significant reduction in computation time for evaluation of post contingency eigenvalues using the proposed method is demonstrated. A case study on a 16-machine NETS-NYPS system shows promising results.

Optimal day-ahead scheduling for microgrid participation in frequency regulation markets

As microgrid installations are steadily growing in the United States and around the world, widespread adoption of commercial microgrids would rely upon the economic benefit to the owners and operators. With the introduction of new market mechanisms and growing penetration of non-traditional generation assets, there is an increasing need and interest in allowing distributed assets to participate in traditional grid services such as frequency regulation. This paper considers the problem of determining the optimal balance of energy and ancillary services for individual microgrid generation assets to participate in such markets. An optimization framework that maximizes the predicted performance of the microgrid over a day-ahead time horizon while accounting for individual asset constraints is proposed. Simulation results on a realistic test system with practical considerations are presented.

Parallelization of time domain dynamic simulation: Existing tools and new techniques

Summary form only given. Enhancing predictability with “faster than real-time” dynamic simulation will enable the dynamic stability margin, proactive real-time control and will improve grid resiliency to fast time-scale phenomena. The existing tools used for dynamic simulation are optimized for single core of a PC. Therefore, they do not take advantage of multiple computational cores and do not meet the real-time need of the industry. The recent advancement in High Performance Computing (HPC) techniques and parallel numerical libraries presents an opportunity to improve the computational speed of dynamic simulation engines. In this context, this paper presents two approaches for parallelization. In the first approach the time domain simulation engine of GE Concorda PSLF has been parallelized using OpenMP under the existing architecture. Improvements in speed have been observed in cases that are large enough to slow down simulation time, such as the US Eastern Interconnect. Further speed gains are dependent on the acceleration of network solution, which is being researched. In the second approach an implicit integration technique with simultaneous solution of multiple time-steps is presented. An initial implementation of this technique on a small test system shows promising results.