Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids
Introduction
Nowadays, a microgrid system is being considered as one of the solutions to the energy concern around the world and it is gaining more attention recently [1]. It can be viewed as a group of distributed generation sources (DGs) connected to the loads in which the DGs can be fed to loads alone or be fed to a utility grid [2], [3]. In recent years, a Battery Energy Storage System (BESS) can be used in various aspects of the power systems. As the output characteristics of these DGs are quite different from the conventional energy sources, the system should be able to handle unexpected fluctuations and maintain system reliability. When an islanding operation occurs in a microgrid where a DG or a group of DGs continue to supply the microgrid system which is separated from the utility grid, the system needs to have the master generator which can provide voltage and frequency support. Generally, a synchronous generator can fulfill this demand. When there is no synchronous generator, converters interfaced batteries can act as the master control. Therefore, battery storage devices serve as an important aspect in microgrid operations [4].
BESS is implemented in various aspects of power systems as one key factor for sustainable energy in many countries particularly in Europe, America and Japan. Advantages of BESS include an improvement of system frequency, especially when BESS is used for system frequency control. For small disturbances, BESS is discharging when the system frequency is lower than 50 or 60 Hz. On the other hand, BESS is charging when the system frequency is higher than 50 or 60 Hz. For large disturbances, BESS can enhance the performance of the system frequency control by integrating BESS with an under frequency load shedding scheme, an under or over frequency generation trip. With these different functions, BESS can offer a good solution. Thus, it is concluded that BESS is a rapid and flexible element for power systems [5], [6], [7], [8].
Previous optimization procedure [4] was implemented for a large interconnected power system case using a small BESS rated power (i.e., 2 MW) compared to the total volume of the spinning reserve provided by the conventional generations (i.e., 3000 MW). Therefore, the impact of BESS on system frequency behavior was widely negligible. Considering now the case of a microgrid system (e.g., a small power system), the BESS rated power cannot be negligible anymore, and thus the grid frequency is now sensitive to BESS output power variations. So, the installation of large/inappropriate size or random size of BESS can cause frequency problems, increase system losses and add an extra cost to the microgrid system. For these reasons, an optimal sizing of BESS is an essential method for a microgrid [5]. However, the optimization method can be achieved by many ways such as balanced generation and load demand method, linear programming method, enumerative method, iterative algorithm, genetic algorithm, particle swarm optimization. According to [9], [10], [11], [12], the advantages of particle swarm optimization (PSO) include simplicity, ease of use, high convergence rate and minimal storage requirement. Especially, it is less dependent on the set of the initial points compared to other methods which implies that convergence algorithm is robust. In [13], an optimal sizing of BESS by using PSO-based reliability is already proposed for an islanded microgrid. However, two basic problems need to be addressed in a microgrid operation: voltage control and frequency control. When in islanding mode, frequency control becomes the main concern for a microgrid operation [14]. Thus, this paper selected and proposed the optimal sizing of BESS by using PSO method-based frequency control of the microgrid to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters).
Modern BESS technologies, which are analyzed and compared the performance and total cost in this study, are the polysulfide–bromine BESS and the vanadium redox BESS (i.e., redox-flow batteries). It is a relatively new commercially available battery and differs from conventional BESS in such a way that the amount of energy it can store is independent on its power rating [15]. Moreover, redox-flow batteries can be designed for both high power and large energy storage. Due to its new commercialization, recent studies on redox-flow BESS in a microgrid are limited [16], [17]. In this study, the specified costs of two BESS technologies are separated and analyzed in order to compare performances of different technologies for 15 years installation in the typical microgrid.
The main purpose of this paper is to determine an optimal size of BESS at minimal total BESS cost by using the proposed PSO-based frequency control of the microgrid to prevent the microgrid from instability and system collapse after the loss of the utility grid. The proposed optimal size of BESS based-PSO is compared with the optimal size of BESS based analytic method (i.e., balanced generation and load demand) and the conventional size of BESS. It is clearly shown that the proposed optimal size of BESS based-PSO method gives the best performance in achieving the optimum size of BESS at minimum total cost of BESS for the microgrid. Then, the impacts of BESS specified costs with different storage technologies are investigated and compared for 15 years installation in the typical microgrid. The rest of this paper is organized as follows; Section ‘Introduction’ describes the background of the research and previous work; Section ‘System configuration’ gives a brief description of the study microgrid; Section ‘Cost consideration of modern BESS technologies’ demonstrates the proposed optimal sizing of BESS by using the PSO method and the analytic method based on frequency control of the microgrid; Section ‘The proposed optimal sizing of BESS based frequency control’ shows the results and analysis; Section ‘Results and discussion’ concludes what has been done in this work.
Section snippets
Microgrid system
The typical microgrid can be operated either in a grid-connected mode or stand-alone mode. Under a normal operation, the microgrid is connected to the utility grid. Fig. 1 shows the microgrid system, which contains a 1.2 MW mini-hydro generator, 2 MW hydro generator and 3 MW photovoltaic sources and BESS, is connected to the microgrid system at bus 1. The system contains the group of feeders which could be a part of the distribution system. The critical loads 1 and 4 require a local generation and
Cost consideration of modern BESS technologies
The considered cost for adding BESS to a microgrid system includes the cost of required inverter and BESS technology. A review of BESS retail prices showed that BESS price is a function of the power and capacity rating. In order to establish an economical analysis of BESS installation, this paper considers the BESS capital cost, operating and maintenance cost. The parameters of these costs depend on energy purchase costs and chosen BESS technology [26].
Objective function
In this paper, the purpose of the objective function in (17) is to evaluate an optimal size of BESS to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters) and the purpose of the objective function in (18) is to minimize the total cost of BESS for 15 years installation in the microgrid. The objective function f1 and f2 have the same weight. To minimize a BESS size and total cost of BESS, the final objective functions are
Results and discussion
In a normal state, all power generated from the microgrid are used to supply loads. If the BESS state of charge is greater than the depth of discharge, the shortage power is supplied by BESS. If BESS could not supply the shortage power, the shortage power is supplied by the utility grid. In an emergency state (e.g., islanding), if the generation cannot meet the load demand in a short period of time during a large disturbance (e.g., three-phase fault) or islanding, the system frequency will drop
Conclusion
This paper proposes the new method to evaluate an optimal size of BESS at minimal total BESS cost by using the proposed PSO method-based frequency control of the microgrid to control and prevent the microgrid from instability and system collapse after the loss of the utility grid. Based on the results, it is seen that BESS offers rapid active power compensation which improves significantly the dynamic stability of the stand-alone microgrid. Moreover, the results indicate that the optimal sizing
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