Model Predictive Control-Based Coordinated Control Algorithm with a Hybrid Energy Storage System to Smooth Wind Power Fluctuations

Abstract

Stochastically fluctuating wind power has an escalating impact on the stability of power grid operations. To smooth out short- and long-term fluctuations, this paper presents a coordinated control algorithm using model predictive control (MPC) to manage a hybrid energy storage system (HESS) consisting of ultra-capacitor (UC) and lithium-ion battery (LB) banks. In the HESS-computing period, the algorithm minimizes HESS operating costs in the subsequent prediction horizon by optimizing the time constant of a flexible first-delay filter (FDF) to obtain the UC power output. In the LB-computing period, the algorithm keeps the optimal time constant of the FDF from the previous period to directly obtain the power output of the UC bank to minimize the power output of the LB bank in the next prediction horizon. A relaxation technique is deployed when the problem is unsolvable. Thus, the fluctuation mitigation requirements are fulfilled with a large probability even in extreme conditions. A state-of-charge (SOC) feedback control strategy is proposed to regulate the SOC of the HESS within its proper range. Case studies and quantitative comparisons demonstrate that the proposed MPC-based algorithm uses a lower power rating and storage capacity than other conventional algorithms to satisfy one-minute and 30-min fluctuation mitigation requirements (FMR).

A novel output power determination and power distribution of hybrid energy storage system for wind turbine power smoothing

“…The extent of smoothing is different for countries. If the standard of countries such as China and Japan is taken into account, the output power deviations in every 1-min (short-term restriction) and 30-min (long-term restriction) should be less than specific values [3,37].…”

Control Strategy for Energy-Storage Systems to Smooth Wind Power Fluctuation Based on Interval and Fuzzy Control

“…The existing studies have mainly focused on promoting wind power consumption through the electricity market [27][28] [29]. A previous study [30] proposed an optimal dispatching mode of wind storage combined with "peak shaving" by comprehensively considering market TOU price and reduction of wind curtailment.…”

An Adaptive Energy Optimization Method of Hybrid Battery-Supercapacitor Storage System for Uncertain Demand

“…Another study, Ref. [16], proposed energy management based on power and voltage limitation methods to suppress DGs power fluctuation. However, methods based on limit measures lack adaptive dynamic adjustability.…”