**1. Introduction**

Lately, there has been a growing consensus among people worldwide regarding the importance of reducing emissions to mitigate the adverse effects of climate change. Several nations and companies globally are beginning to commit to net-zero emissions. Despite its vulnerability to climate change, it is also realized by Indonesia, which is Although vulnerable to climate change, this is also realized by Indonesia, which is an archipelago country country [1]. The utilization of alternative or renewable energy sources (RES) is one of the most effective ways to reduce emissions generated from fossil fuels. Solar photovoltaic (PV) is the most extensively utilized RES owing to its installation simplicity, low cost, and scalability [2]. However, problems arise because the RES generation is unpredictable and highly dependent on nature, resulting in an unstable power supply to the load [3]. Due to its high penetration, the uncertainty of PV plants expose the power grid to many challenges, such as voltage, frequency fluctuations, reverse power flow, and harmonics [4]. The successful integration of RES into the planning and operating model of an electric power system on a grid-scale increases the flexibility of the battery [5].

The battery energy storage system (BESS) helps ease the unpredictability of electrical power output in RES facilities which is mainly dependent on climatic conditions. The integration of BESS in RES power plants boost PV penetration rates [6], thereby improving the efficiency and reliability of the generating system [7]. Furthermore, BESS plays an

**Citation:** Apribowo, C.H.B.; Sarjiya, S.; Hadi, S.P.; Wijaya, F.D. Optimal Planning of Battery Energy Storage Systems by Considering Battery Degradation due to Ambient Temperature: A Review, Challenges, and New Perspective. *Batteries* **2022**, *8*, 290. https://doi.org/10.3390/ batteries8120290

Academic Editors: Luis Hernández-Callejo, Jesús Armando Aguilar Jiménez and Carlos Meza Benavides

Received: 26 October 2022 Revised: 22 November 2022 Accepted: 10 December 2022 Published: 16 December 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

essential role in distribution networks, where it is used to assist auxiliary services, load shifting and leveling, backup power, peak shaving, demand response, renewable energy integration, frequency control, voltage management, long-term, and seasonal storages [8–10]. Therefore, its optimization is essential.

BESS capacity and its ideal location are both determined by its optimization indicator. The performance of the electric power system is also significantly improved by its optimization in terms of establishing the appropriate capacity and rating. Meanwhile, inadequate capacities and ratings tend to result in greater power losses and increased costs for both the investment and operation of the power system [11]. BESS capacity needs to be optimized to ensure continuous electric power alongside robust and economical operation [12]. Its optimal placement is also extremely relevant on grid-scale networks. This is because it affects BESS costs and services by delaying investment from peak loads, improving the response to changes in electrical energy generation and demand, reducing transmission and distribution losses, as well as restrictions on RES generation [13]. One of the most significant decisions to make is planning to optimize the performance of the RES system to achieve profitable investments. The optimization of BESS capacity and placement is a significant problem due to the need for ideal energy exchange equilibrium [14] and the total cost of installation [15].

BESS technology includes the use of lithium-ion (Li-Ion), lead-acid (LA), sodiumsulfur (NaS), zinc-bromine (ZBB), nickel-cadmium (Ni-Cd), vanadium-redox (VRB), and polysulfide bromine batteries (PSB) [16,17]. These are typically used for load leveling, power quality, grid extension and support, demand management, and voltage regulation. One of the major advantages of LA is that it has relatively low investment opportunities, and expensive to operate with limited energy density. Although the Li-Ion batteries have high energy and power densities with long-lasting life cycle and excellent efficiency, it is an expensive investment [18]. This battery type is also manufactured as packs, organized in series or parallel to realize the necessary current, voltage, and power. Throughout the development of this battery, large-scale battery packs were built as power walls [19].

Li-Ion batteries' performance deteriorated over time and is referred to as calendar and cycle life [20]. This is due to two causes, first is the loss of Li-Ion triggered by the formation of a solid electrolyte contact (SEI). Second is the loss of electrode sites [21], which increases internal resistance, lowers capacitance and efficiency, and diminishes battery life [22,23]. Consequently, battery deterioration always impacts the optimal operation and longevity of Li-Ion battery energy storage, particularly the percentage of power systems [24]. It also predicts battery life, maximum charge or discharge cycles, or Ah-overall. The data is then used for cost or benefit analysis [25].

The degradation costs for a charge or discharge cycles need to be considered when analyzing real-time energy management challenges. In this case, the energy management running expenditures tend to grow because of battery life and actual unrepresented electricity prices [26]. According to Cardoso et al. [27] the overall annual power cost reductions from PV and storage systems can be reduced by 5–12% if the battery deterioration limits are considered. Ren et al. [28] stated that it significantly reduces the system's electrical performance and increases unanticipated maintenance expenditures. Battery failure is usually due to deterioration caused by increased rate of usage, and this can limit its lifespan and potentially lead to significant accidents. Likewise, battery degradation significantly reduces the system's electrical performance and increases unanticipated maintenance expenditures. Severson et al. [29] stated that the prediction of battery life facilitates new production, use, and optimization opportunities. If one can accurately anticipate the lifespan of a battery, then they can create new uses as well as optimize its performance. This leads to innovative opportunities for the manufacturing process and optimization.

The present study examines the optimization plan for the BESS system problem by considering battery degradation due to ambient temperature. It serves as a reference for investigating areas of electrification using renewable energy sources. This engineering topic covers BESS planning in relation to deterioration from a practical standpoint. However, this static problem involves battery capacity and location to attain the desired goals. These tend to be influenced by technological and economic concerns, as well as other factors such as reliability. As a result, BESS planners encounter certain challenges in gathering and inputting data, dealing with design constraints, and implementing effective energy management. The following are the key contributions of this research:

• Explain the state-of-the-art expansion planning with BESS optimization.


The present research is arranged as follows. Section 2 outlines the methods used to review the literature. Section 3 investigates BESS with respect to expansion planning. Sections 4 and 5 reviewed its application and battery technology, respectively. Section 6 focuses on the study of battery degradation. Meanwhile, Section 7 reviews the objective function, design constraint, and algorithm of BESS optimization. Section 8 discusses the issues and challenges of BESS, while Section 9 concludes the research and provides areas for future works.

#### **2. Methodology**

The systematic literature review (SLR) was summarized using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach. Data were selected from the Scopus, Science Direct, IEEE Xplore and Web of Science databases in three stages, namely identification, screening, and reporting. Figure 1, shows the identification stage, which is carried out by searching for related articles in each database, as illustrated in Table 1. The strategy adopted at the time of initial screening on the database is in accordance with the provision of the title, abstract, and keyword. This led to the realization of 1584 articles, of which 824, 352, 187, and 221 were from Scopus, Science Direct, IEEE Xplore, and Web of Science concerning the optimization of BESS and battery degradation, respectively.

**Table 1.** Search term selection.


After checking and removing duplicate reports and records marked as ineligible by automation tools, 139 papers were obtained for screening. The papers were selected in accordance with exclusion and inclusion criteria based on Table 2. Incidentally, 42 records were excluded, 12 were not retrieved, and 15 reports were omitted due to inclusion and exclusion criteria at the screening stage. Finally, the total number of comprehensive SLR articles to be reviewed are 69.

**Table 2.** Criteria for the systematic literature review.


**Figure 1.** Block diagram selection based on PRISMA flow diagram approach [30].

As a result, this SLR was carried out to respond to the following research objectives and questions.


The number of publications on this topic has increased over the past five years, as shown in Figure 2. For example, from 2018 to 2021 there were 53 articles, with 16 new publications in October 2022.

Meanwhile, 69 comprehensive articles have been selected for review. The acquired data has a Q1 journaling tool from the Scimago Journal Rank (SJR). Table 3 shows the list of publications or journals selected for review.


