Malhar Padhee

Malhar Padhee, Anamitra Pal, Chetan Mishra et al.

Battery energy storage systems (BESSs) can play a key role in mitigating the intermittency and uncertainty associated with adding large amounts of renewable energy to the bulk power system (BPS). Two BESS technologies that have gained prominence in this regard are Lithium-ion (LI) BESS and Vanadium redox flow (VRF) BESS. This paper proposes a fixed-flexible BESS allocation scheme that exploits the complementary characteristics of LI and VRF BESSs to attain optimal techno-economic benefits in a wind-integrated BPS. Studies carried out on relatively large transmission networks demonstrate that benefits such as reduction in system operation cost, wind spillage, voltage fluctuations, and discounted payback period, can be realized by using the proposed scheme.

Malhar Padhee, Anamitra Pal, Katelynn A. Vance

This paper presents a methodology for building daily profiles of wind generation and load for different seasons to assess their impacts on voltage violations. The measurement-based wind models showed very high accuracy when validated against several years of actual wind power data. System load modeling was carried out by analyzing the seasonal trends that occur in residential, commercial, and industrial loads. When the proposed approach was implemented on the IEEE 118-bus system, it could identify violations in bus voltage profiles that the season-independent model could not capture. The results of the proposed approach are expected to provide better visualization of the problems that seasonal variations in wind power and load might cause to the electric power grid.

Joydeep Banerjee, Anamitra Pal, Kaustav Basu et al.

Smart grid systems are composed of power and communication network components. The components in either network exhibit complex dependencies on components in its own as well as the other network to drive their functionality. Existing, models fail to capture these complex dependencies. In this paper, we restrict to the dependencies in the power network and propose the Multi-scale Implicative Interdependency Relation (MIIR) model that address the existing limitations. A formal description of the model along with its working dynamics and a brief validation with respect to the 2011 Southwest blackout are provided. Utilizing the MIIR model, the $K$ Contingency List problem is proposed. For a given time instant, the problem solves for a set of $K$ entities in a power network which when failed at that time instant would cause the maximum number of entities to fail eventually. Owing to the problem being NP-complete we devised a Mixed Integer Program (MIP) to obtain the optimal solution and a polynomial time sub-optimal heuristic. The efficacy of the heuristic with respect to the MIP is compared by using different bus system data. In general, the heuristic is shown to provide near optimal solution at a much faster time than the MIP.