*8.4. Degradation of Battery Due to Ambient Temperature*

Due to calendar and cycle aging, the amount of time a battery has been in use impacts how old it appears. Even though its life is determined by calendar aging, the BESS datasheet includes two limits cycle and float life. The likely computation of the BESS life value being accurate is low since battery life is dependent on cycle or float life. This is unlikely to affect the computation process. The term float life refers to the length of time that a BES is guaranteed to operate at its maximum capacity. When designing a BES system, the impacts of battery aging need to be considered with respect to the overall cost. High operating temperature, SOC, DOD, and charge or discharge current rate are all nonlinear factors that influence battery degeneration. The aging of the battery has an impact on the BESS performance and the cost of the electric power system. The major parameters of its deterioration capacity are voltage, current, charge or discharge cycle, and battery life. Generally, two things contribute to battery degeneration. First, there is loss of lithium ions as a result of SEI production. Second, it is caused by the loss of electrode particles. This is because the battery experiences an increase in its internal resistance. It causes a decrease in the battery's capacity as well as its efficiency, which eventually results in a shorter lifespan.

The battery performance and life cycle of Li-Ion batteries are susceptible to high temperatures, which tend to accelerate degradation significantly. This triggers the rapid growth of SEI on the surface of electron particles, leading to a loss in battery capacity. It is since the rapid growth of SEI on the surface of electron particles causes a decrease in battery capacity. In addition to this, the temperature of the surrounding environment has a significant bearing on the rate at which capacity is lost. The temperature of the battery cell and the high ambient contribute to the rapid growth of SEI on the surface of electron particles. Its development also contributes to a decrease in the capacity of the battery. According to the literature [100], when the ambient temperature exceeds 35 ◦C, changes in electrolyte composition increase. This is due to a significant temperature rise, accelerating active lithium consumption rate. Therefore, ambient temperature considerations can be challenging in influencing BESS battery degradation.

#### *8.5. Retired Batteries for BESS*

Hazardous chemical waste on BESS construction cells significantly affects the environment. Damaged batteries can be recycled and reused. Approximately 95% of the main material in LA batteries are recyclable and reusable [15,158]. In the past ten years, approximately five million EVs and 400 GWh of lithium-ion batteries have been sold all over the world [159]. The development of the EV market will eventually result in a large flow of retired batteries. Meanwhile, Li-Ion recycling is likely feasible, battery reuse and recycling are complementary processes that only slow down the cycle of excess resources. lion recycling has proven to be uneconomical [160]. The repurposing of retired batteries from EVs as BESS is a new challenge. To reduce battery disposal problems due to EOL [161] in electric power systems, BESS can be built to provide related services from EOL batteries. This is because these batteries tend to qualify for less-demanding grid services [162]. Retired BESS can increase the RES penetration of the electric power system for reverse spinning [163] with relatively cheaper installation costs.

#### *8.6. Flexibility of Variable Renewable Energy Sources*

Because of nature intermittency, RES such as solar PV and wind energy are inextricably connected to uncertainty. Higher renewable penetration rates substantially influence microgrid or grid system operation, data transfer, and handling, including remote sensing, decision-making, and system control. Therefore, this RES requires storage facilities such as BESS to store and supply electricity as needed. Most studies generate RES variability data using probabilistic methods such as Monte Carlo simulations, analytical and approximation models. However, these methods are insufficient for expressing random variables. These processes are also computationally challenging and need large amounts of historical data, extended run times, and precise mathematical premises. As a result, precise modeling and analytical treatment of this uncertainty while considering the geographic situation are crucial to making the best operational and financial decisions during microgrid or grid applications.

#### **9. Conclusions**

This study reviews the state-of-art BESS optimization methods considering battery degradation in connection to its diverse technologies. A comprehensive analysis of the development of the current BESS modeling approach with the objective function, battery degradation characteristics, and design constraints was employed. BESS is related to expansion planning, often called SEP. Its primary goal is to ensure that central planners, such as vertically integrated power companies and policymakers from governments or groups of countries responsible for minimizing costs rather than maximizing the benefits to private investors. Additionally, the use of BESS on the grid or microgrid is adopted to improve power quality, voltage and frequency control, peak shaving, load smoothing, and energy arbitrage.

LA, Li-Ion, NaS, and VRB are grid applications most common battery technologies. The energy density, efficiency, longevity, and cost of batteries linked to a storage network are all classed. Battery degradation reduces power efficiency in BESS. As a result, its deterioration needs to be considered during BESS optimization. The degradation of batteries owing to ambient temperature is currently understudied. Lithium-ion batteries' performance and life cycle are extremely temperature sensitive. In addition, high temperatures greatly accelerate battery degradation. The ambient temperature has a significant influence on the capacity fading rate, especially when it surpasses 35 ◦C, the composition of the electrolyte changes because of the large increase in temperature.

Generally, the objective function of optimizing BESS is to reduce the total cost of planning. The objective function and design constraints of BESS are highly dependent on the purpose for which BESS is used. BESS objective function is used to reduce LCC and battery degradation costs to minimize the total cost of system planning. The only components that make up this LCC are the costs of operation and maintenance, as well as the initial investment in the BESS. Based on the study of the optimal BESS, ambient temperature affects battery degradation. The development of its model due to ambient temperature can be a new perspective in optimizing BESS. The battery degradation algorithm affects the speed and convergence of BESS optimization. The determination of the model algorithm and battery degradation factors needs to be appropriately considered.

The challenges that need to be faced and the scope of future research in optimizing BESS by considering battery degradation of ambient temperature are the economic analysis, utilizing proper battery storage technology, and developing optimal charge or discharge model. Others include developing model degradation due to ambient temperature of BESS, considering retired batteries for BESS, and using the RES variable due to the uncertainty of natural conditions.

**Author Contributions:** Conceptualization, C.H.B.A., S.S., S.P.H. and F.D.W.; methodology, C.H.B.A. and S.S.; software, C.H.B.A.; validation, S.S., S.P.H. and F.D.W.; formal analysis, C.H.B.A.; investigation, C.H.B.A.; resources, C.H.B.A. and S.S.; data curation, C.H.B.A., S.S., S.P.H. and F.D.W.; writing—original draft preparation, C.H.B.A., S.S., S.P.H. and F.D.W.; writing—review and editing, C.H.B.A., S.S., S.P.H. and F.D.W.; visualization, C.H.B.A.; supervision, S.S., F.D.W. and S.P.H.; project administration, C.H.B.A.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Directorate General of Higher Education (DIKTI), Ministry of Education, Culture, Research and Technology, Research Grant: Penelitian Disertasi Doktor (PDD) with contract number 1929/UN1/DITLIT/Dit-Lit/PT.01.03/2022.

**Institutional Review Board Statement:** Not appliable.

**Informed Consent Statement:** Not appliable.

**Data Availability Statement:** Not appliable.

**Acknowledgments:** The authors are grateful to the Center for Education Financial Services (PUS-LAPDIK), Ministry of Education, Culture, Research, and Technology and Indonesia Endowment Fund for Education (LPDP), Ministry of Finance of Republic of Indonesia: Beasiswa Pendidikan Indonesia (BPI) for supporting the funding of doctoral studies scholarship through contract number 1358/J5.2.3./BPI.06/10/2021.

**Conflicts of Interest:** The authors state that there is no conflict of interest. The research initiatives used as support had no part in the planning, collecting, analyzing, and interpreting data, as well as in compositing the paper and publishing the results.

#### **Abbreviations**

The following are some of the abbreviations that can be found in this manuscript:


