Optimal Energy Storage System-Based Virtual Inertia Placement: A Frequency Stability Point of View

Abstract

In this paper, the problem of optimal placement of 5 virtual inertia is considered as a techno-economic problem from a 6 frequency stability point of view. First, a data driven-based equiv-7 alent model of battery energy storage systems, as seen from the 8 electrical system, is proposed. This experimentally validated model 9 takes advantage of the energy storage system special attributes to 10 contribute to inertial response enhancement, via the virtual inertia 11 concept. Then, a new framework is proposed, which considers the 12 battery storage system features, including annual costs, lifetime and 13 state of charge, into the optimal placement formulation to enhance 14 frequency response with a minimum storage capacity. Two well-15 known dynamical frequency criteria, the frequency nadir and the 16 rate of change of frequency, are utilized in the optimization formu-17 lation to determine minimum energy storage systems. Moreover, a 18 power angle-based stability index is also used to assess the effect 19 of virtual inertia on transient stability. Sensitivity and uncertainty 20 analyses are further conducted to assess the applicability of the 21 method. The efficiency of the proposed framework is demonstrated 22 on a linearized model of a three-area power system as well as two 23 nonlinear systems. Simulation results suggest that the proposed 24 method gives improved results in terms of stability measures and 25 less ESS capacity, when compared with other methods proposed in 26 the literature. Q1 27 Index Terms-Optimal placement, frequency nadir, virtual 28 inertia, energy storage systems, inertial response, rate of change 29 of frequency, transient stability, uncertainty analysis, sensitivity 30

Manipulation of Static and Dynamic Data Center Power Responses to Support Grid Operations

“…It is important to ensure the state of charge (SoC) of the UPS to remain within the upper and lower bands to prolong the battery life time as well as to guarantee the operational safety of the system. These limits are predefined for which the SoCi ∈ [SoCi,min, SoCi,max] and they are limited to 20% and 80% of the UPS storage capacity, respectively [38].…”

Economic operational analytics for energy storage placement at different grid locations and contingency scenarios with stochastic wind profiles

“…Similarly, the probabilistic constraints were also formulated in [27], considering the forecast errors to solve the two-stage stochastic programming through MPC along with the chance constraints. Voltage [28] and time-domain [29] system performance has been utilized for the placement and sizing of ESS. In [28], ESS has been optimally allocated, considering the optimized voltage deviation, flicker, power loss, and line loading.…”

“…Voltage sensitivity is utilized to determine the location of ESS. Power system oscillations damping were considered for the ESS placement in [29]. Here, ESS is modelled using a second-order model used for describing synchronous generator operation and dynamics.…”

A Comprehensive Survey on the Impact of Renewable Energy Sources in Power System Operation and Control

“…Generally, in power-systems, inertia play a significant role in the maintenance of reliability and stability of system by stabilizing the variations in frequency [14]. The conventional synchronous generation sources were displaced by the renewable energy sources that have no intrinsic inertia [15].…”