Achieving a minimum power fluctuation rate in wind and photovoltaic output power using discrete Kalman filter based on weighted average approach

In this study, a discrete Kalman filter-based approach is presented for minimising the output power fluctuations of wind and photovoltaic systems. The control strategy is based on the change in power fluctuation which is determined by the weighted average of the highest and lowest values of the power fluctuation for each interval of time. A genetic algorithm optimisation approach is utilised to determine the optimal value of weighted average such that the power fluctuation rate is minimum. This study also gives the optimum battery power and its state of charge to achieve smoothing determined by the optimal weighted average. On the basis of this optimum battery power, the specification and configuration of the battery energy storage system are also determined

A fuzzy logic control approach for smoothing of wind and photovoltaic generation output fluctuations

Increasing levels of the wind and photovoltaic systems require innovative ways to manage the fluctuations caused due to the intermittent generation profile. This paper proposes a fuzzy logic based control approach to smooth the power output of the collocated wind and photovoltaic generation system. A first order filter is modified with a fuzzy logic controller which regulates the battery power, the state of charge and pitch angle for smoothing of the output power. The controller adjusts the time constant of the filter based on the state of charge of battery and pitch angle of wind generation system by considering the battery power. The effectiveness of the proposed approach is analyzed by considering the different values of the state of charge

Electrodeposited cobalt-based electrocatalysts for efficient oxygen evolution reaction and supercapacitors

Although transition metal oxides/hydroxides have gone through many modifications including heteroatoms doping to improve their performance towards electrocatalytic water splitting and supercapacitors, their superior performance is yet to come. Herein, cobalt hydroxide was calcined, sulfurized, and phosphorized, which was prepared via a facile electrodeposition process on nickel foam at −1.0 V. Based on the experimental results, the cobalt sulfide showed a lower overpotential of 282 mV to achieve a current density of 10 mA/cm2 for oxygen evolution process. Moreover, the prepared optimized cobalt sulfide sample displayed the highest specific capacitance of 3.7 F/cm2 along with the largest energy density (0.144 Wh/cm2) as well as high power density (8.28 W/cm2). The prepared optimized cobalt sulfide sample showed a very stable electrochemical performance suggesting that the facile electrodeposition process can produce efficient electrocatalysts for the oxygen evolution process

Kalman filter approach for dispatching and attenuating the power fluctuation of wind and photovoltaic power generating systems

The battery energy storage system (BESS) is a popularly used source to smooth the power fluctuation caused by variation of wind speed and solar irradiance. The forecasted data of wind and solar irradiance may contain bias error and does not provide the true power available from wind and photovoltaic generating systems. This study proposes a method based on discrete Kalman filter (DKF) to eliminate the bias error present in the forecasted data so that true power of wind and photovoltaic systems could be predicted. A DKF-based state-space approach is utilised to predict the true power obtained through wind and photovoltaic generating systems. The proposed approach also attenuates the power fluctuation of wind and PVGSs considering the desired power dispatched to the load as well as evaluates the BESS power needed for this purpose