Energy storage sizing by copula modelling joint distribution for wind farm to be black‐start source

Abstract

To achieve fast power system restoration with high penetration of wind power, using wind farm (WF) as black-start (BS) source is a promising choice. An energy storage system (ESS) sizing method with the minimum investment cost is proposed to enable WF to be a reliable BS source. The proposed method covers three aspects: (i) providing WF self-starting power, (ii) dealing with frequency deviation when starting up ancillary machines and (iii) smoothing WF output power while starting up generator unit. During BS progress, ESS power sizing and capacity sizing are both considered as random variables and their marginal distributions are estimated by kernel density estimation to avoid the distribution model mismatch. The correlation between these two random variables is discussed, which shows that these two variables are not independent. To model the dependence structure between ESS power sizing and capacity sizing, copula theory is applied to build the joint probability distribution. A tail dependence analysis and goodness-of-fit test included copula selection procedure is conducted to choose the most suitable copula function. A case study with real WF data demonstrates that a better-fitted copula has lower ESS sizing cost.

A review of key functionalities of battery energy storage system in renewable energy integrated power systems

“…BESS in wind 167 and PV 168 farms can be exploited to start up these units as a BS source because BESS is capable of providing the necessary excitation voltage that other non‐BS units require 169 . This will enhance the BS ability of the grid and widen the prospective application of PV/wind generation.…”

“…This will enhance the BS ability of the grid and widen the prospective application of PV/wind generation. However, proper sizing 167,168 and allocation of start‐up sequence of BESS and other generating units 170 are imperative for enhancing the resiliency of the grid.…”

Design and Implementation of a Hybrid Real-Time State of Charge Estimation Scheme for Battery Energy Storage Systems

“…The initial SOC value required by the Coulomb counting method is obtained using the OCV method and a linear approximation equation is Processes 2020, 8, 2 5 of 22 established from the battery manufacturer's OCV-SOC data. The formula for calculating real-time battery SOC using Coulomb counting algorithm is shown in (1).…”

“…In recent years, BESSs have been widely used in renewable energy (RE)-based power generation (REBPG) applications and microgrids to smooth the intermittent power generation, buffer the power generation-demand differences, and improve the frequency stability of power systems. BESSs are also very useful in optimal electrical energy management and grid voltage stabilization [1]. In order to achieve proper compensation functions, real-time SOC information of BESS is required to determine its operational limits and prevent overcharging/overdischarging to ensure a desirable battery life.…”

Selecting an Effective ESS Installation Location From the Perspective of Reactive Power

“…However, that study focuses more on the transient phenomena, neglecting the changes in the active/reactive power requirements according to the location. Previously, Liu and Liu [2]- [6] have explored the improvement in the power quality of a wind farm using an ESS and determined its capacity for a black start. However, Liu and Liu installed the ESS on a wind farm and discussed the ESS as a secondary facility to convert the wind farm into a self-starting generator.…”