Hourly Dispatching Wind-Solar Hybrid Power System with Battery-Supercapacitor Hybrid Energy Storage

This dissertation demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a specific dispatching horizon for an entire day utilizing a hybrid energy storage system (HESS) configured by batteries and supercapacitors. Here, wind speed and solar irradiance are predicted one hour ahead of time using a multilayer perceptron Artificial Neural Network (ANN), which exhibits satisfactory performance with good convergence mapping between input and target output data. Furthermore, multiple state of charge (SOC) controllers as a function of energy storage system (ESS) SOC are developed to accurately estimate the grid reference power (PGrid,ref) for each dispatching period. A low pass filter (LPF) is employed to decouple the power between a battery and a supercapacitor (SC), and the cost optimization of the HESS is computed based on the time constant of the LPF through extensive simulations. Besides, the optimum value of depth of discharge for ESS considering both cycling and calendar expenses has been investigated to optimize the life cycle cost of the ESS, which is vital for minimizing the cost of a dispatchable wind-solar power scheme. Finally, the proposed ESS control algorithm is verified by conducting control hardware-in-the loop (CHIL) experiments in a real-time digital simulator (RTDS) platform

Design of a cost effective battery-supercapacitor hybrid energy storage system for hourly dispatching solar PV power

This study aims to develop a low cost energy storage system for hourly dispatching solar photovoltaic (PV) power for 1MW grid connected PV array. To fulfill this objective, the optimum (most economical) scaling of a battery and supercapacitor (SC) hybrid storage is developed based on the time constant of a low pass filter (LPF) that is used to allocate the power between a battery and SC. Based on the battery state of charge (SOC), rule based algorithms are developed to estimate the perfect grid reference power for each one-hour dispatching period. Another rule-based algorithm is implemented to keep the battery SOC within a certain limit that helps to increase the battery lifetime. An economic comparison of different kinds of battery and SC combination in hybrid energy storage system (HESS) is presented in this research. This study also considers the relationship between the actual PV cell temperature and the ambient temperature and presents their effects on energy storage price calculations. This study uses actual solar data of four different days recorded at Oak Ridge National Laboratory (ORNL) in MATLAB/Simulink environment simulations to get the better picture about annual energy storage cost for hourly dispatching solar power. According to the results, the HESS combination of li-ion battery and SC, outperforms a battery only or lead acid and SC combination in HESS operation regardless of temperature framework

Evaluation of reference generation algorithms for dispatching solar PV power

This paper aims to develop a low-cost energy storage system by evaluating reference generation algorithms for dispatching solar power for 1 MW photovoltaic (PV) arrays. Based on battery state of charge (SOC), rule-based algorithms are developed to adjust the grid reference power for each one-hour dispatching period. In this paper, several rule-based algorithms are used to control the SOC of the battery that plays a significant role to design cost-effective energy storage system. The price comparison is made between two kinds of energy storage system (i) Battery only (ii) Battery+ Supercapacitor (SC), where a low pass filter is used to allocate power between battery and SC. The most economical energy storage system is developed through extensive simulations in MATLAB/Simulink environment. The results show that the hybrid energy storage system (HESS), combination of battery and SC, outperforms a battery-only operation.Conference PaperPublishe