Beyond financial and environmental aspects, DGs have technical limitations. Typically, these systems have slower response times, frequently exceeding 10 s, leading to delays in power availability during electrical supply interruptions. Additionally, the scalability of DGs is limited, making it challenging to adapt to varying energy demands over time.
Beyond economic and environmental benefits, battery storage systems offer greater flexibility and adaptability, which can be adjusted to each company’s specific energy demand. In the open energy market, this adaptability is vital.
Environmentally, replacing DG with BESS contributes to reducing greenhouse gas emissions and other atmospheric pollutants. By eliminating the burning of fossil fuels, such as diesel, BESS mitigates the negative environmental impacts associated with DG. This is especially pertinent in the pursuit of cleaner, more sustainable energy sources, in line with international commitments to carbon emission reductions and a transition toward a greener energy matrix.
Studies address several thematic areas related to the use of BESS, such as isolated grid supply, grid-connected applications, distribution system management, and transmission line support.
This paper contributes significantly to the existing literature by offering an innovative comparative analysis between BESS and diesel generators based on real data from an operating microgrid. The novelty of the study lies in the simulation of the use of DG instead of BESS to serve the same load at high-energy prices. This reveals a tangible and concrete understanding of the financial and environmental consequences of this choice.
It will be noted throughout the article that these results clearly demonstrate the advantages of BESS in relation to DG and the conventional electrical grid. In environmental terms, the BESS does not emit CO2, while the DG emits tons of CO2 per year. In financial terms, the total cost of BESS over 20 years is assessed as lower than that of DG and the power grid.
The article thus substantiates the significance of BESS in terms of environmental sustainability and financial viability. Furthermore, it enhances the academic and practical context by furnishing precise data and analyses that highlight BESS as an energy-saving and financially advantageous option for the operation of microgrids during periods of elevated energy charges.
2. Materials and Methods
The methodology used clearly defines the materials and methods of the study, such as the economic evaluation of both technologies and the quantification of their respective CO2 emissions and other pollutants.
The paper bases its findings on a specific case study: the operational performance of a facility in Brazil equipped with a 250 kW/560 kWh BESS and a 75 kVA DG. This offers practical insight into the implications of our analysis, providing a tangible perspective on the findings. Therefore, data collection is a critical part of the approach, collecting real operational data and supplementing it with information from previous research, manufacturer publications, and government reports.
Regarding environmental evaluation, the analyses focus primarily on greenhouse gas emissions. CO2 emissions and other pollutants from both technologies are quantified, allowing for a direct comparison of their environmental impacts.
After these separate analyzes, the data is put into a direct comparison between BESS and DG, weighing the environmental benefits and associated costs. In this context, the challenges and limitations of transitioning from DG to BESS are also briefly explored, including considerations of infrastructure and regulation.
2.1. Financial Analysis Methods
where PMWh is the constant remuneration to the electricity provider over the plant’s lifespan; MWh denotes the amount of electricity produced annually, and r is the real discount rate, representing the cost of capital. The terms Capitalt, replacementb, O&Mt, Fuelt, Carbont, and Dt signify the capital, battery replacement, operation and maintenance, fuel, carbon, and decommissioning costs in a given year t, respectively.
Similarly, as with renewable energies, BESS emerged with the need for a metric to compare its associated costs, LCOS. LCOS refers to the cost per unit of energy (such as kWh) that is stored and then discharged from an energy storage system.
Here, Capitalt, replacementb, and O&Mt represent capital, replacement, and operating and maintenance costs in year t, respectively. Meanwhile,
denotes the total energy released from the storage system during its useful life, adjusted for system efficiency, and r is the real discount rate.
The LCOS calculation does not weigh the energy’s value or its release timing. Since the energy’s value can fluctuate daily or annually, storage technologies that dispatch energy during demand peaks might have higher economic value despite a higher LCOS. In this light, three specific metrics have been developed to compute energy storage costs, chiefly differentiating based on charging costs: RADP (required average discharge price), RAPS (required average price spread), and RAOP (required average operating profit).
Required Average Discharge Price (RADP): This metric is the average discharge price needed for an energy storage solution to break even. Essentially, it is the price at which the stored energy should be sold to cover all associated costs; mathematically :
Required Average Price Spread (RAPS): considers the price difference between energy’s purchase (charging) and sale (discharging). A significant price gap is typically necessary between the energy bought during low-demand times and the energy sold during peak demand. This metric represents the average price difference for the storage solution to reach break-even; expressed as :
is the average charging price, found from the distribution between the total charging cost and the total energy charged.
Required Average Operating Profit (RAOP): This metric determines the average operating profit required for an energy storage system to be deemed viable. It is the difference between the revenue from the discharging of energy and the costs of charging and maintaining the storage solution. In particular, unlike RAPS which focuses on price differences, RAOP includes other operational costs. Defined as :
2.2. Environmental Analysis Method
is the total CO2 emission from DG (in tons),
is the amount of fuel consumed (in liters), and
is the specific emission factor for the fuel (in tons of CO2 per liter). While the BESS is represented as follows:
is the total CO2 emission associated with the charging of the batteries (in tons),
is the energy produced to charge batteries (in kWh), and
is the electric grid’s emission factor (in tons of CO2 per kWh).
are the total pollutant emissions from the DG (in tons) and
is the specific emission factor for pollutants (in tons of pollutants per liter). For the BESS, it is given that:
are the total pollutant emissions associated with battery charging (in tons), and
is the electric grid’s pollutant emission factor of the electric grid (in tons of pollutants per kWh).
is the difference in CO2 emissions between DG and BESS, and
is the difference in pollutant emissions between DG and BESS.
3. Case Study
The microgrid in the case study is part of the Living Lab Project, located in Belo Jardim, Pernambuco, Brazil. The Edson Mororó Moura Technology Institute solution portfolio places a particular emphasis on the development and testing of battery energy storage systems and microgrids. Additionally, it contributes to energy efficiency within the institution by utilizing BESS (Battery Energy Storage System) during peak hours, backup, power factor correction, and the establishment of an islanded microgrid. The microgrid is connected to the grid and isolated. In this context, the database is made up of operational data from the system connected to the grid, focusing on the operation of supply times when demand or consumption is exceeded.
Based on the operation of this system, two-day operation data was collected and used as a reference for the simulation of the case study. The data are specific to the time of the highest load demand and high-energy costs, between 5:30 p.m. and 8:30 p.m. The reduced database is because it is a private microgrid for product development and the use of its data is restricted.
From approximately 260 minutes of operation data, referring to the second day of operation, the DG set contributes 20 kW to meet the demand, and during its operation, the BESS reduces its power to the minimum value of 100 kW. This demonstrates how much the BESS alleviates facilities that generally make use of the DG set daily for cost reduction or backup promotion.
In the comparison between DG and BESS, the context of the application is paramount and depends on various factors. With regard to energy efficiency, the set of diesel generators is composed of two essential elements: the engine and the alternator. Thus, the efficiency of the diesel generator sets is depicted as the combined efficiency of these two subcomponents. Typically, the joint efficiency of the diesel generators fluctuates between 30–55%, whereas the standalone efficiency of the diesel engine and the alternator varies between 35–60% and 85–95%, respectively, with notable energy losses in the form of heat. In contrast, BESS generally exhibits very high charge and discharge efficiencies, frequently exceeding 80%, with the ability to store and release electricity with minimal losses. Regarding carbon emissions, diesel generators emit substantial amounts of CO2, NOx, and other pollutants, while a BESS itself does not release pollutants directly. However, the source of electricity used to charge the batteries may have correlated emissions if the electricity is derived from fossil-fuel-powered plants.
In contrast, the BESS exhibits an active power of 250 kW and a substantial energy capacity of 560 kWh. Despite its significantly higher capital cost of USD 370,459.5, it compensates for the annual increase in energy prices and inflation rates of 5% and 6.05%, respectively. It is important to note that of the capital cost, 30% goes toward replacing batteries around the tenth year of their useful life.
At first, the analysis of these data without appropriate technical and financial treatment could lead to erroneous considerations. Therefore, this technical–financial analysis allows stakeholders to carefully evaluate the options of the DG and BESS, considering both technical capacities and financial impacts.
4. Discussion of Results
The comprehensive analysis of the energy systems analyzed, the diesel generator, the battery energy storage system, and the electrical grid revealed decisive insights into their performance, allowing for a detailed evaluation of their relative efficacy. The evaluation focused on various parameters, encompassing both operational capacities and associated costs. The parameters analyzed included RADP, RAOP, and RAPS. It is essential to note that systems are assessed for load service during times when the electrical grid has the highest kWh cost.
The initial observation of operational costs (OPEX) and total costs highlights a clear advantage of BESS over DG regarding OPEX, which costs approximately USD 340,790.67 less. Although the total cost of BESS and DG is quite similar, BESS stands out for its marginally lower cost, although the electrical grid presents a significantly higher expense. Regarding energy, both the DG and BESS and the electrical grid show equivalent values of generated, discharged, and consumed energy, respectively. The LCOE (levelized cost of energy) and LCOS present a sharper comparison. BESS has a marginally lower LCOS (USD 0.38) than the LCOE of DG (USD 0.39), indicating a higher cost efficiency in energy generation. The LCOE of the electrical grid (USD 0.67) is significantly higher, making it the least cost-efficient option for energy generation.
RAOP is another critical metric that shows the average operational profit generated to cover all operational and capital costs throughout its lifecycle. In this perspective, the simulated DG has the lowest value of USD 0.10/kWh, closely followed by BESS with USD 0.11/kWh, with both exceeding the electrical grid (USD 0.10/kWh). This indicates that although DG requires a lower average operating price, BESS is not far behind, providing a competitive operational performance.
A similar analysis is performed for RAPS, with results indicating a higher average price of USD 0.22/kWh for the DG when compared to the BESS with a price of USD 0.18/kWh, but lower than the grid (USD 0.38/kWh). Specifically, BESS requires a smaller spread to achieve the break-even point, which refers to the point at which the total (fixed and variable) operating expenses of an energy system, whether DG or BESS, reach their maximum. This means that, at the breakeven point, the system is neither generating profit nor incurring a loss. Therefore, the evaluated indicator shows that BESS needs a smaller difference between the purchase and sale prices of energy to cover its operational and capital costs, while the electric grid presents the largest value difference.
In financial terms, the BESS stands out as the best option to meet the load demand during the period of the highest grid cost, compared to the possibility of using the DG and the grid itself. However, the purely financial perspective leaves gaps regarding the environmental impacts that these technologies can provide. When comparing the diesel generator group and the battery energy storage system, significant differences are observed in terms of emissions and environmental impacts.
In contrast to the DG, the BESS presents itself as a greener and more sustainable option. It does not emit CO2 during its operation, contributing to a substantial reduction in greenhouse gas emissions. This environmental benefit is converted into financial gains with carbon credits, totaling USD 350.9 per year, which can be considered an additional return when opting for this technology.
In terms of financial analysis, it is verified that BESS also stands out in terms of total cost, OPEX, and LCOS. Although the DG presents a slightly superior RADP, the BESS excels in RAOP, indicating a higher average operational profit.
Thus, balancing environmental and financial considerations, the BESS stands as the most favorable option for the case. It not only minimizes the environmental impact by significantly reducing greenhouse gas emissions and other pollutants, but also shows financial performance.
This article explores the comparison between the use of diesel generators and BESS, focusing on their application in Brazil. Diesel generators have been identified to be widely used on the Brazilian market to meet increasing demand, especially in the industry. However, this solution has limitations, such as high fuel costs, negative environmental impacts, and a lack of operational flexibility.
The current climate scenario highlights the imperative need for sustainable energy choices. In this context, BESS emerges as a prominent alternative in stark contrast to the traditional options, especially in terms of CO2 emissions. This article presents an analysis using data from a real microgrid in operation and then simulating the use of DG in place of BESS to meet the same load during the high-cost energy period that occurs every day. From the results obtained, it is found that DG is responsible for emitting a substantial 67.32 tons of CO2 equivalent annually, a striking contrast to BESS, which does not contribute to CO2 emissions, resulting in a carbon credit of USD 350.9.
The environmental impact of DG is exacerbated by the emission of other pollutants, such as CO2, PM, and NOx, totaling 30.56 kg/year, 1.39 kg/year, and 145.94 kg/year, respectively. These further contribute to environmental degradation, presenting significant challenges in terms of air quality and public health. The DG carbon credit, valued at USD 5.91, is significantly less than that of BESS, further highlighting the environmental advantages of the latter.
Beyond environmental considerations, financial analysis reveals critical insights. The total cost over a 20-year life cycle is lower for BESS (USD 1,551,486.50) compared to DG (USD 1,562,643.80), which is substantially lower than that of the Electric Grid (USD 2,722,137.23). In the case of the grid, only the cost of energy is observed, and its growth is considered over 20 years. These data, combined with an LCOS of USD 0.38 (lower than the LCOE of DG and the grid), position BESS as an economically viable option, ensuring energy efficiency at a lower cost.
Among the metrics analyzed, RADP, an indication of the necessary discharge price for equilibrium, is comparatively lower for BESS (USD 0.38/kWh), implying that it requires a lower average discharge price to cover all associated costs. This is complemented by a higher RAOP (USD 0.11/kWh), suggesting a higher average operational profit for BESS compared to DG and the Electric Grid. The RAPS for BESS is also the lowest, indicating that BESS requires a smaller price spread to reach the breakeven point.
Based on the results obtained in this study, it is recommended that policymakers and other stakeholders in the energy sector consider the potential of BESS as a viable and sustainable alternative to diesel generators. Implementing policies and incentives that favor the use of energy storage technologies, such as BESS, could accelerate the transition to cleaner and more sustainable energy sources. It is important to highlight the need for clear and comprehensive regulation that guarantees the safety, reliability, and accessibility of these technologies for all users of the electrical system.
In conclusion, the article unequivocally demonstrates that BESS not only meets contemporary environmental imperatives by minimizing CO2 emissions and other pollutants, but also stands out as an energetically efficient and economically viable option. Commitment to sustainability, combined with tangible economic benefits, emphasizes BESS as a superior strategic investment choice, promoting not only environmental health, but also ensuring an optimized financial return over time. For future work, it is recommended to use a longer period of data analysis for more accurate validation of the results.