Dynamic modeling and sizing optimization of stand-alone photovoltaic power systems using hybrid energy storage technology
Introduction
As a kind of clean and renewable resource, photovoltaic (PV) energy has gained significant attention in recent years due to the high energy cost and adverse environmental impacts of conventional fossil fuels. One of the major challenges for the PV energy system remains matching the intermittent energy supply with the dynamic power demand. This problem can be solved by exchanging power with the electrical grid. However, for the stand-alone PV system [1], [2], certain energy storage devices must be added into the system so as to provide power-on-demand. These devices must store PV energy in excess of electricity demand and subsequently meet electricity demand in excess of PV energy. The conventional lead–acid battery is the most common energy storage device at the present time. Fuel cells (FCs) in combination with an electrolyzer, a compressor, and hydrogen tanks are considered as a new energy storage mode, which is characterized by the generation, storage, and conversion of hydrogen energy. Furthermore, a hybrid energy storage system combining a battery system and a hydrogen system provides us with another storage option for the PV system.
Some studies on the PV power system with energy storage have been reported in the literature. Dakkak et al. [3] developed a centralized energy management strategy for a PV system with plural individual subsystems and one battery bank. Nelson et al. [4] assessed a stand-alone wind/PV power system using the single energy storage method (battery or hydrogen). Based on the downhill simplex method, the cost of a PV system using hydrogen storage method was optimized by Santarelli et al. [5]. Vosen and Keller [6] analyzed the cost and efficiency of PV power systems with different combinations of energy storage devices. A hybrid energy storage system coupled to PV generation was evaluated in Ref. [7].
However, most of them do not take into account the effects of energy storage capacity on the whole system. The system cost and efficiency are usually dealt with separately. No studies have been reported that compare system cost and efficiency.
Three energy storage technologies, namely photovoltaic/battery (PV/Battery) system, photovoltaic/fuel cell (PV/FC) system, and photovoltaic/fuel cell/battery (PV/FC/Battery) system as shown in Fig. 1, are studied in this work. The PV/Battery system consists of a PV generator, DC/DC, batteries, and an inverter. The PV/FC system comprises a PV generator, DC/DC, an electrolyzer, a compressor, fuel cells, and an inverter. The PV/FC/Battery system is the combination of the battery system and the hydrogen system. Fig. 2 shows the hourly average load data during a day [8]. The peak demand is 2.3 kW. These load data are assumed to remain constant in each hourly interval. Thus, the system under study here is best thought of as a collection of homes, which are large enough to smooth out sub-hourly variations that may occur in any one home. The radiation and temperature data of Shanghai are derived from Refs. [9], [10], [11]. The monthly radiation and average temperature data are shown in Fig. 3.
The paper is organized as follows: Section 2 develops the key component models, which facilitate the evaluation of power systems. In Section 3, three cost metrics and three efficiency metrics are defined as comprehensive evaluation standards. At the same time, a method of ascertaining minimal system configuration is designed for the purpose of the impartial comparison. Finally, based on the sizing optimization of the three PV systems, correlations between system cost and efficiency are revealed in Section 4.
Section snippets
Photovoltaic module
The solar cell is the basic unit of photovoltaic modules which convert the sun's rays or photons directly into electrical energy. A solar cell is generally represented by a circuit diagram [12], [13] as shown in Fig. 4.
As a function of voltage, the current of a cell is defined bywhere Iph is the photon current, Isat is the diode reverse saturation current, Vt is the thermal voltage, Rs and Rp are the series and parallel resistances, respectively, and I
Methods of system evaluation and optimization
Fig. 1 shows the structures of the PV/Battery, PV/FC, and PV/FC/Battery hybrid power systems. The efficiencies, costs, lifetimes and operation and management (O&M) costs of the key components are listed in Table 1. PV data are from the product instruction of a PV module (Shell SP140-PC). Fuel cell data are from the California Energy Commission [24] and Refs [26], [27]. The electrolyzer, compressor, hydrogen tank, battery and inverter data from the US National Renewable Energy Laboratory [25]
Results and discussion
The results for the three energy storage technologies are summarized in Table 2. The capacity of the batteries or hydrogen tanks is calculated based on the load demands during a day (45.632 kWh d−1).
Conclusions
Three stand-alone photovoltaic power systems using different energy storage technologies are modeled and optimized in this paper. The proposed component models facilitate the estimation of the storage capacity and calculation of the system efficiency. Three cost metrics and three efficiency metrics provide comprehensive standards of system evaluation. The method of ascertaining the minimal system configuration lays the foundation for the impartial comparison among the three power systems.
For
Acknowledgements
This work is supported by the National Natural Science Foundation (NNSF) of China (Grant 20576071).
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