Economic feasibility of energy strategies in retail: a comparative analysis of the Free Electricity Market, Zero-Export photovoltaic systems, and BESS in supermarkets in Santa Catarina, Brazil

Viabilidade econômica de estratégias energéticas no varejo: uma análise comparativa entre Mercado Livre de Energia, fotovoltaica Zero Grid e BESS em supermercados de Santa Catarina, Brasil

Abstract

Abstract  Electricity costs challenge the competitiveness of the supermarket retail sector. This study analyzed the technical and economic feasibility of three strategies in supermarkets in Santa Catarina, Brazil: the Free Electricity Market (FEM), battery energy storage systems (BESS) for peak shaving, and zero-grid photovoltaics. Based on real data from 2024 and a 15-year financial model (LCOE and payback), the analysis took into account Brazilian Law No. 15,235/2025. The results indicated that the FEM with incentivized energy offers the most immediate return, reducing costs by 25% to 28%. Photovoltaic generation proved to be a robust investment, with a payback period of 4.5 to 5.5 years. In contrast, BESS was found to be economically unfeasible under current conditions due to high CAPEX, with a payback period exceeding 8 years. It is concluded that contract management and solar generation are the investment priorities, while energy storage depends on future cost reduction.

Keywords:
Free Electricity Market; Photovoltaic generation; BESS; Energy efficiency

Resumo

Resumo  O custo da energia elétrica desafia a competitividade do setor supermercadista. Este estudo analisou a viabilidade técnica e econômica de três estratégias em supermercados de Santa Catarina, Brasil: o Mercado Livre de Energia (MLE), sistemas de armazenamento por baterias (BESS) para peak shaving e fotovoltaica Zero Grid. Com base em dados reais de 2024 e em modelagem financeira de 15 anos (LCOE e payback), a análise considerou a Lei nº 15.235/2025. Os resultados indicaram que o MLE com energia incentivada oferece o retorno mais imediato, reduzindo custos entre 25% e 28%. A geração fotovoltaica mostrou-se um investimento robusto, com payback de 4,5 a 5,5 anos. Em contrapartida, o BESS revelou-se economicamente inviável nas condições atuais devido ao elevado CAPEX, com payback superior a 8 anos. Conclui-se que a gestão contratual e a geração solar são as prioridades de investimento, enquanto o armazenamento depende de futura redução de custos.

Palavras-chave:
Mercado Livre de Energia; Geração fotovoltaica; BESS; Eficiência energética

1 Introduction

The continuous growth in electricity demand, coupled with environmental concerns and the need for cost optimization, has driven companies to seek more efficient energy management strategies (Geller et al., 2004). The push for energy efficiency goes beyond reducing operating costs, as it is embedded in a broader context of technological transition and compliance with environmental goals. As highlighted by Volan et al. (2023), the establishment of ambitious legislation and goals is an essential factor for replacing fossil fuel-based technologies with cleaner and more efficient alternatives.

Against this backdrop, the liberalization of energy markets has emerged as a global trend to enhance competitiveness. Countries such as Japan and the United States have already consolidated models in which consumers negotiate directly with suppliers (ECOM, 2023). In Brazil, although the expansion of the Free Electricity Market (FEM) has been gradual since 1998, recent developments point to an acceleration. In 2024, driven by the pursuit of competitive tariffs and contractual flexibility, migrations to the Free Contracting Environment (Ambiente de Contratação Livre – ACL) reached record highs, in parallel with rising electricity consumption across all regions of the country (CCEE, 2024).

The supermarket retail sector is particularly sensitive to these dynamics. Characterized as electricity-intensive consumers, supermarkets rely on uninterrupted refrigeration and air conditioning to preserve products (ABRAS, 2023a; Kolokotroni et al., 2019). Studies indicate that refrigeration may account for up to 60% of a store's energy consumption (Kolokotroni et al., 2019), and, in Brazil, electricity represents, on average, 10% to 15% of the sector's operating expenses (ABRAS, 2023b). This dependence makes the profitability of these companies vulnerable to tariff fluctuations and high peak-hour costs.

In light of these challenges, modernizing energy management becomes imperative. Migration to FEM stands out as a primary strategy, enabling customized contracts. At the same time, the adoption of distributed photovoltaic generation — which has the potential to be a promising alternative for meeting demand cost-effectively in several regions of the country (Nascimento et al., 2025) — and battery energy storage systems (BESS) align with the transition toward decentralized models, described by Rifkin (2016) as pillars of the new energy economy. Technically, the use of BESS for peak shaving offers the potential to shift loads and minimize the most burdensome tariff charges (EPE, 2020).

Recent studies have explored these technologies from different perspectives: Menezes et al. (2024) applied mathematical optimization models for cost reduction in industrial settings, while Almeida & Altoé (2022) validated the feasibility of photovoltaic generation specifically in the retail sector. However, the literature still lacks analyses that integrate migration to Free Electricity Market with the use of storage systems under a peak-shaving strategy and zero-grid generation based on real operational data. Most studies focus on isolated solutions or theoretical simulations, leaving a gap regarding how these three energy management approaches interact financially within the same real load profile.

Accordingly, the contribution of this study consists of the technical and economic feasibility analysis of FEM, BESS, and distributed photovoltaic generation, based on the real load profile of a supermarket chain in Santa Catarina, Brazil. The study thus aims to quantify the potential for cost reduction during peak hours, while also providing support for strategic decision-making in energy management within the sector.

2 Theoretical background

2.1 Composition of electricity tariffs

The tariff structure of electricity distribution utilities in Brazil is regulated by ANEEL (the Brazilian Electricity Regulatory Agency) and is designed to reflect regulatory costs, ensuring tariff affordability and the economic and financial balance of concessions (ANEEL, 2023a).

The final tariff comprises two main components: the Distribution System Usage Tariff (Tarifa de Uso do Sistema de Distribuição – TUSD), which covers infrastructure ("wire") costs, and the Energy Tariff (Tarifa de Energia – TE), which refers to the cost of the energy itself. Both are influenced by the concepts of Portion A (non-manageable costs, such as energy purchases from Itaipu and sector charges) and Portion B (manageable costs, such as the distributor's own operation, maintenance, and investments). Efficient management of Portion B directly affects annual tariff adjustments (ENERGES, 2023).

For billing purposes, consumers are divided into two groups:

• Group A (High Voltage): this group includes industrial facilities and large commercial establishments (such as supermarkets). Billing follows a two-part (binomial) structure, comprising the cost of contracted demand (kW) — a fixed amount paid for grid availability — and metered consumption (kWh).

• Group B (Low Voltage): this group includes households and small businesses. Billing is predominantly single-part (monomial), based solely on the volume of energy consumed (kWh), although the White Tariff (Tarifa Branca) option has introduced time-of-use variation for this group.

Supermarkets, generally classified under Group A, are subject to the time-of-use tariff system, which segments the day into peak (higher tariffs) and off-peak (lower tariffs) periods. This differentiation aims to discourage consumption during periods of highest system load (ANEEL, 2020). Depending on their load structure, Group A consumers must choose between the Green modality (a single demand tariff with time-differentiated consumption tariffs) or the Blue modality (time-differentiated tariffs for both demand and consumption). Selecting the appropriate modality can yield significant reductions in operating costs.

In addition, the Tariff Flag system, in effect since 2015, signals the actual cost of energy generation on a monthly basis. The flags (Green, Yellow, and Red — Levels 1 and 2) pass on to consumers the additional costs arising from the dispatch of thermal power plants. For the supermarket sector, frequent activation of the red flag can increase energy costs by up to 12%, undermining competitiveness (ANEEL, 2024).

Given this scenario, efficient management within the regulated market (even before migration to the free market) involves contract optimization. Under ANEEL Resolution No. 1,000/2021, consumers may revise their contracted demand to avoid penalties for exceeding contracted limits or paying for idle demand (ANEEL, 2023a).

2.1.1 Composition of electricity bills

The composition of electricity bills reflects the sum of TUSD and TE costs, plus sector charges and taxes (PIS, COFINS, and ICMS). Under current regulations, utilities must itemize these amounts transparently, allowing consumers to understand the effective cost of each component (ANEEL, 2023a).

For Group A4 consumers served by CELESC (Centrais Elétricas de Santa Catarina, the local power utility in Santa Catarina), which operate at medium voltage (2.3 kV to 25 kV), regulation allows a choice between two main time-of-use tariff modalities: Blue and Green. The appropriate choice between them depends fundamentally on the load profile and load factor of the consumer unit.

The Blue Time-of-Use Tariff is characterized by the application of differentiated tariffs for power demand (kW) according to the time of use (peak and off-peak). In other words, the consumer pays a specific rate for contracted demand during peak hours and a different rate for the remainder of the day. Energy consumption (kWh) is also subject to time differentiation. This modality is mandatory for high-voltage consumers (subgroups A1, A2, and A3) and optional for A4, and is generally recommended for units with a high load factor during peak hours (ANEEL, 2023a).

The Green Time-of-Use Tariff differs by applying a single tariff to power demand (kW), regardless of the time of use. However, energy consumption tariffs (kWh) are sharply differentiated, with the peak-hour (kWh) rate being significantly higher than that of the Blue tariff. This modality tends to be advantageous for consumers who can modulate their load, drastically reducing consumption during peak hours to avoid the penalty of high energy costs in that period (ANEEL, 2023a).

2.2 The Free Electricity Market in Brazil

The Free Electricity Market (FEM) in Brazil dates back to the 1990s, a period in which the limitations of the state-led model and the need for investment made structural reforms in the electricity sector imperative (Garisto, 2015). The 2001 rationing crisis acted as a catalyst for profound transformations, culminating in the 2004 regulatory reform (Brasil, 2004), which established the current model of the Brazilian electricity sector. This regulatory framework segregated the market into two distinct environments: the Regulated Contracting Environment (Ambiente de Contratação Regulada – ACR) and the Free Contracting Environment (Ambiente de Contratação Livre – ACL) (Brasil, 2004).

In the Free Contracting Environment, consumers negotiate directly with suppliers, defining prices, contract terms, and generation sources (CCEE, 2024). Unlike the regulated market, where tariffs are fixed and subject to the Tariff Flag System, the free market offers budget predictability and exemption from these additional charges. Among its advantages are customized demand management and access to renewable sources, which can reduce energy costs by 15% to 30% (ABRACEEL, 2024).

The expansion of this market has been progressive. MME Ordinance No. 50/2022 represented a significant step forward by allowing, as of January 2024, all Group A (high-voltage) consumers to migrate to the free market, regardless of their contracted demand (Brasil, 2022b). More recently, the regulatory landscape was updated by Law No. 15,235 of 2025 (originating from Provisional Measure No. 1,300/2025), establishing new guidelines for market opening and sector modernization; seeking to correct tariff distortions; and preparing the system for broader and more sustainable liberalization.

Currently, FEM accounts for approximately 38% of national energy consumption, with projections by the Electric Energy Trading Chamber (Câmara de Comercialização de Energia Elétrica – CCEE) indicating the projected attraction of more than 24,000 new consumers by the end of 2025 (CCEE, 2024). However, despite robust growth, the market faces structural challenges, such as short-term price volatility (PLD, the Brazilian spot price) and bottlenecks in transmission infrastructure (Santos & Bassoi, 2021). The full consolidation of the model therefore depends on continuous regulatory evolution to ensure the integration of intermittent renewable sources and the legal certainty required for new investments (ABRADEE, 2023; Santos et al., 2023).

Historically, the expansion of renewable sources in Brazil was strongly driven by tariff subsidies established by Law No. 9,427/1996 and its subsequent amendments, such as Law No. 12,783/2013 (Brasil, 1996, 2013). These incentives consist of discounts applied to the TUSD and the Transmission System Usage Tariff (TUST), ranging from 50% to 80% or 100%, depending on the source (solar, wind, biomass, small hydropower plants) and the project's authorization date. The mechanism was designed to increase the competitiveness of these sources vis-à-vis large-scale conventional generation (Brasil, 2013; Brasil, 2022a).

In the Free Market, "incentivized energy" offers discounts on the grid (transport) usage tariff, reducing the final cost. However, Law No. 14,120/2021 eliminated this benefit for new projects after March 2022. As a result, "legacy energy" contracts (older plants that retain the discount) have become scarce and highly sought-after assets in the market (Brasil, 2021; Almeida, 2021). For electricity-intensive consumers, such as supermarket chains in Santa Catarina, contracting incentivized energy (with a 50% discount on TUSD/TUST) remains a robust cost-reduction strategy. Since the TUSD can represent a substantial share of the bill (often exceeding 40% of total costs at low and medium voltage), halving this amount generates a direct financial impact, particularly advantageous for mitigating the fixed costs of contracted demand and peak-hour consumption (Reis, 2023; Schmitt, 2022)

The viability of this strategy depends on the tax burden. Although the discount reduces the tariff calculation base, the ICMS (the Brazilian state value-added tax on goods and services) may be levied on the full amount under certain state legislations, mitigating the benefit (Rovaris et al., 2022). Thus, the economic analysis must weigh the high cost of incentivized energy, due to its scarcity, against the actual net savings achieved on the TUSD after taxation.

2.3 Energy consumption models for supermarkets

Energy consumption in food retail exhibits unique characteristics, marked by the intensity and continuity of demand. Brazilian studies (Panesi, 2008; Hibarino, 2018) and international studies (AERG, 2013) converge in identifying food refrigeration as the main driver of a supermarket's energy consumption, followed by lighting and air conditioning. This uninterrupted operation, vital for preserving perishables, places the sector eighth in the electricity consumption ranking of the Electric Energy Trading Chamber (CCEE), just behind large basic industries such as metallurgy and chemicals.

The financial impact of this consumption profile is severe. According to Bruno (2015), electricity has become the second-largest operating expense of supermarket chains, surpassed only by payroll and, in some cases, surpassing rental costs. Recent data corroborate this trend: a survey by Sincovaga (2024) revealed that, for 25% of the establishments interviewed, energy accounts for more than 20% of total operating costs. Furthermore, energy inflation is a constant reality; around 30% of companies in the sector have reported increases of more than 20% in their electricity bills since 2021 (ABRAS, 2024a).

This scenario is exacerbated by the sector's physical growth. Reports by the Brazilian Supermarket Association (Associação Brasileira de Supermercados – ABRAS) indicate that the number of stores increased by 31% in 2023, resulting in an 11% rise in aggregate energy consumption over the same period (ABRAS, 2024b). Faced with cost pressures and tariff volatility, business owners have adopted both palliative and structural measures. The most common actions include lighting optimization with LED technology (30%), strategic shutdown of freezers (22%), and luminance reduction (44%). However, only 13% had invested in self-generation (photovoltaics) and 7% in refrigeration retrofits, as of the latest survey (ABRAS, 2024a).

The specialized literature, such as the Advanced Energy Retrofit Guide (AERG, 2013), suggests that isolated efficiency measures are insufficient. The economic sustainability of supermarkets increasingly depends on integrated solutions involving automation, equipment modernization, and, crucially, the strategic management of energy procurement. It is in this context that migration to the Free Electricity Market and the adoption of distributed generation emerge not only as cost reducers but also as hedging tools against price volatility and exclusive dependence on local distribution utilities (ABRACEEL, 2024; Brasil, 2024).

In addition to the ACL discussed earlier — in which companies can sign energy contracts aimed at greater cost predictability and competitiveness, taking advantage of the discounts applicable to the TUSD and TUST through the contracting of incentivized energy — there are other strategies for reducing electricity bills. These range from investments in more energy-efficient equipment to the adoption of self-generation systems. Moreover, the implementation of energy storage systems can help balance consumption by reducing demand during peak hours, when energy costs are significantly higher.

In the context of this study, on-site photovoltaic generation and the implementation of battery storage systems are specifically addressed, analyzing how these solutions can directly contribute to reducing companies' electricity bills.

2.3.1 Photovoltaic generation

Photovoltaic technology converts solar radiation into electricity through semiconductor cells. The modules generate direct current (DC) power, with voltage and current variations that depend on irradiance and temperature (Esteves, 2018; Pereira & Oliveira, 2011).

For use in supermarkets and connection to the electricity grid, inverters are employed. These devices convert direct current into alternating current (AC), synchronizing it with the local grid. Beyond conversion, inverters ensure power quality and minimize distortions, complying with current technical standards (Rashid, 2014). Depending on the connection and energy management strategy, photovoltaic systems are classified into different topologies:

• Grid-Connected (On-Grid) Systems: Operate in parallel with the utility grid. The energy generated is simultaneously consumed by local loads, and any surplus is injected into the grid, generating energy credits (under the Brazilian net metering scheme, Sistema de Compensação de Energia Elétrica). This configuration does not require batteries and is the most common option for cost reduction via net metering, provided the inverters are certified with anti-islanding protection (ANEEL, 2023b); NREL, 2020).

• Zero-Export (Zero-Grid) Systems: This is an on-grid configuration with a specific technical constraint: the inverter regulates generation so that it never exceeds the unit's instantaneous consumption. The goal is to avoid injecting energy into the utility grid (New Day Solar, 2024). This modality is strategic for Group A consumers seeking to avoid charges on injected energy (the "Fio B" wire charge) or facing technical connection restrictions imposed by the distribution utility (Technik, 2023).

• Hybrid and Storage Systems: Combine the characteristics of grid-connected systems with the autonomy of battery banks (BESS). A hybrid inverter manages the energy flow between the modules, batteries, loads, and the grid (NREL, 2021). For supermarkets, this is the most sophisticated topology, as it enables not only backup in the event of outages (off-grid function) but also peak-shaving strategies (using the battery to reduce demand during peak hours) and price arbitrage (Oudalov et al., 2007).

2.3.2 Energy storage and batteries in the Brazilian Electricity Sector

Unlike off-grid systems, in which storage is mandatory due to the variability of the solar resource, in grid-connected systems the adoption of batteries (Battery Energy Storage Systems – BESS) focuses on reliability (backup) and cost reduction through demand management (Esteves, 2018). The use of batteries increases the system's technical stability and economic attractiveness by smoothing fluctuations in photovoltaic generation (Volan et al., 2021, 2022).

Among the various storage methods, electrochemical batteries predominate in commercial applications due to their modularity and energy density (IEA, 2023). Lithium-ion technology currently leads the market, particularly Lithium Iron Phosphate (LFP) batteries, which offer longer service life and greater thermal safety (RONTEK, 2019). The economic viability of this technology has been driven by the sharp decline in investment costs, which have fallen by approximately 90% since 2010 (IEA, 2023).

Within the Brazilian regulatory framework, the landscape is in transition. Historically, ANEEL Normative Resolutions No. 482/2012 and No. 687/2015 did not specifically address storage (Brasil, 2012, 2015). However, throughout 2024 and 2025, the topic gained traction with the holding of Capacity Reserve Auctions and the opening of public consultations (ANEEL Public Consultation No. 007) to define rules for ancillary services and revenue stacking (ANEEL, 2024; Mayer Brown, 2024).

Even under the current regulatory framework, Group A (medium-voltage) consumers can already technically exploit three main strategies with BESS:

• Peak Shaving: Using the battery to supply the load during peak hours, avoiding grid consumption when tariffs are highest (Oudalov et al., 2007).

• Energy Arbitrage: Charging the system during low-tariff periods (overnight) and discharging during high-tariff periods.

• Dispatch Control: Storing surplus photovoltaic generation to avoid grid injection at times of credit devaluation or technical restrictions (Lopes et al., 2022).

In light of the above, this section has shown that the combination of photovoltaic generation, migration to the Free Market, and storage systems constitutes a three-pronged strategy for cost reduction. In the following sections, the study applies these concepts to assess the economic feasibility of these solutions in supermarkets in Santa Catarina.

3 Methodology

The choice of the state of Santa Catarina as the territorial scope is justified by the availability of high-resolution primary data from a regional retail chain, which enables more accurate simulations than the use of sector averages. Furthermore, the supermarket sector in Santa Catarina is economically significant and operates under a tariff structure that serves as a benchmark for market migration and storage technology feasibility studies in medium-sized chains.

Accordingly, this research adopted a quantitative and exploratory approach, based on primary data collection and financial modeling. The study was conducted in the second half of 2024, using corporate databases and updated market parameters for the simulation of energy scenarios.

Consumption data were extracted from the energy management system of a retail chain, covering three supermarkets located in the Greater Florianópolis area, Santa Catarina (anonymously identified as Supermarkets A, B, and C). The dataset comprised the consumption (kWh) and demand (kW) history, recorded at 15-minute intervals over five years. For the purposes of a conservative simulation, the 2024 load profile — the year with the highest demand values in the historical series — was adopted as the reference, with a 3% safety margin.

To assess the economic feasibility of energy interventions in the retail sector, the analysis was structured into four comparative scenarios. These scenarios range from the current supply situation (captive market) to the integration of self-generation or storage technologies, providing an incremental view of the financial benefits. A summary of the technical assumptions and objectives of each proposal is presented in Table 1.

Table 1
Summary of the Energy Management Scenarios Analyzed.

Scenario	Technical Description	Main Economic Objective
Captive market	Supply via the local distribution utility (ACR), under the Blue or Green tariff modality.	Baseline for cost comparison.
Free electricity market	Energy procurement in the Free Market (50% incentivized energy).	Reduction of MWh costs and exemption from tariff flags.
Photovoltaic panels	Implementation of a solar system in the zero-grid configuration.	Reduction of purchased energy volume and tax mitigation.
BESS	Use of batteries to supply the load during peak hours.	Reduction of billed demand and of consumption during high-tariff periods.

The units are connected at medium voltage (Subgroup A4) within the concession area of CELESC (Centrais Elétricas de Santa Catarina). Table 2 details the tariffs approved by ANEEL Ratification Resolution No. 3,385/2024, used as the baseline for calculating costs in the ACR.

Table 2
Subgroup A4 Tariffs – CELESC (2024-2025).

Modality	Tariff Period	TUSD Demand (BRL/kW)	TUSD Distribution (BRL/MWh)	TE (BRL/MWh)
Blue	Peak (P)	36.65	106.86	456.91
Blue	Off-Peak (OF)	17.71	106.86	286.41
Green	Peak (P)	17.71	998.00	456.91
Green	Off-Peak (OF)	17.71	106.86	286.47

• Source: Adapted from ANEEL (2024).

For the ACL migration scenario, current energy costs and sector charges were considered, as shown in Table 3. The tax analysis took into account the legislation of the state of Santa Catarina, where the ICMS is levied on the total value of the transaction, mitigating part of the tax benefit of the TUSD discount (incentivized energy).

Table 3
Energy Costs in the Free Electricity Market (BRL/MWh) and Associated Charges.

Type	Value
Conventional energy	155.00 BRL/MWh
50% incentivized energy	195.00 BRL/MWh
100% incentivized energy	341.00 BRL/MWh
Administrative fee	BRL 8,703.00
System Service Charges (ESS)	5.31 BRL/MWh
COVID Account	2.30 BRL/MWh
Water Scarcity Account	3.46 BRL/MWh

The economic feasibility of the solutions (ACL migration, PV generation, and BESS) was assessed over a 15-year horizon using the Levelized Cost of Energy (LCOE). This choice is justified by the nature of the supermarket sector, where high inventory turnover and pressure on operating margins make the payback period and the LCOE the most critical indicators for managerial decision-making and direct comparison with utility tariffs. The LCOE was calculated according to Equation (1):

$\begin{array}{c}LCOE=\frac{{{\displaystyle \sum }}_{t=1}^T\frac{C_t}{{\left(1+r\right)}^t}}{{{\displaystyle \sum }}_{t=1}^T\frac{E_t}{{\left(1+r\right)}^t}}\end{array}$ (1)

where:

$C_t$ represents the total costs in year t, including CAPEX and OPEX;

$E_t$ is the energy generated in year t;

r is the discount rate;

T is the analysis time horizon.

The tariff subsidy analysis considered the additional costs applied in the captive market, based on the applicable tariffs and taxes, such as ICMS, PIS, and COFINS. The equation used for this calculation is presented in Equation (2).

$\begin{array}{c}TotalCost=\frac{\left(Demand\times \mathrm{0,5}\times TUSD\left(demand\right)\right)+\left(Consumption\times \mathrm{0,5}\times TUST\left(distribution\right)+TE\right)}{\left(1-ICMS\right)\times \left(1-PIS-COFINS\right)}\#\end{array}$ (2)

The financial analyses were performed over a 15-year horizon, under the following assumptions:

• Minimum acceptable rate of return (MARR): 11.25%, based on the SELIC rate (the Brazilian base interest rate) of November 2024.

• Inflation: 4.03%, according to the 2025 forecast of the Brazilian National Monetary Council.

• Taxes: ICMS of 17%, PIS of 1.2795%, and COFINS of 5.9074% levied on energy, and full PIS/COFINS (9.25%) levied on other costs.

• CAPEX BESS: The price reported by BloombergNEF (BNEF) was adopted, which recorded a record low of USD 139/kWh in 2021 (BNEF, 2021). Converted to Brazilian reais, the BESS price is BRL 1,551.44/kWh, considering an exchange rate of BRL 5.79 per USD and import costs (BRL 482.89/kWh in import duties plus BRL 263.74/kWh in ICMS).

• CAPEX PV: The price per watt-peak reported by GREENER (2024) was adopted: BRL 3.00 per watt-peak for systems above 500 kWp and BRL 3.10 for systems between 75 kWp and 150 kWp.

• OPEX: Annual OPEX was set at 1% of CAPEX for the BESS and 2% of CAPEX for the PV systems.

• Import costs: An exchange rate of BRL 5.79 per USD was considered, with charges calculated using the Brazilian Federal Revenue Service's official calculator.

• Efficiency and degradation: For the BESS, a round-trip efficiency of 87.5% and capacity degradation over a service life of 6,000 cycles were considered (GREENER, 2021).

• Depth of Discharge (DoD): 92.5% of total battery capacity.

• Solution modularity: 5 kWh increments, ensuring that BESS sizing is consistent with market-available products.

This study has limitations that should be considered when interpreting the results. The feasibility of photovoltaic generation and BESS is tied to CELESC tariffs (Santa Catarina), local solar irradiation levels and may vary in other regions. Furthermore, the financial indicators (NPV and LCOE) are sensitive to fluctuations in the exchange rate and in the 2024 SELIC rate. Finally, the model assumes technological degradation rates based on the technical literature, which may differ from the actual operational performance of batteries and panels.

4 Results and discussion

4.1 Presentation of the collected data

To enable the economic simulations, the consumption and demand profiles of the three units were extracted for the 2024 base year. Table 4 summarizes the adopted values, where "Consumption" refers to the average monthly recorded value and "Demand" corresponds to the maximum power peak recorded in the year, plus a 3% safety margin to ensure robust equipment sizing (inverters and transformers).

Table 4
Adjusted Maximum Demand and Consumption Values for 2024.

Supermarket	Peak Consumption (MWh)	Off-Peak Consumption (MWh)	Peak Demand (kW)	Off-Peak Demand (kW)
Super_A	28.80	262.91	772.50	927.00
Super_B	34.63	306.51	824.00	978.00
Super_C	6.30	62.84	154.50	180.25

It is worth noting that, in the CELESC concession area, peak hours run from 6:30 p.m. to 9:30 p.m., totaling 3 hours per day of elevated tariffs, which directly affects the battery discharge strategy.

4.1.1 Temporal analysis of consumption and demand

The data analysis reveals two distinct operating profiles among the units studied. On one hand, there are the large establishments (Supermarkets A and B): both units show total monthly consumption in the range of 300 to 350 MWh and power demands close to 1 MW (1,000 kW). The ratio between peak consumption and total consumption is around 10%, which is characteristic of commercial operations that maintain intensive refrigeration 24 hours a day but reduce part of the lighting and air conditioning during the night. The similarity between the profiles of Supermarkets A and B (a scale difference of approximately 15%) suggests that solutions feasible for one tend to be replicable for the other.

On the other hand, there is Supermarket C, a medium-sized establishment with total consumption of approximately 70 MWh/month and demand below 200 kW; this unit operates on a significantly smaller scale (around 20% of the size of the others). Its peak consumption share (9.1%) is slightly lower, indicating a more stable load profile or a commercial operation that closes earlier.

This stratification is crucial for the discussion of the results: while Supermarkets A and B have sufficient scale to dilute high infrastructure investments (such as large battery banks), Supermarket C serves as a "stress test" to verify the feasibility of these technologies in smaller businesses, where the payback period tends to be longer due to the lower volume of energy consumed.

4.2 Costs in the captive market

This section establishes the economic baseline of the study, projecting annual energy costs in the ACR. The need to individually assess the tariffs of each modality in the captive environment corroborates the literature, which identifies the ACR as a more costly and less flexible environment, requiring accurate feasibility studies before any strategic decision-making (Teberge & Sodré, 2019).

The current CELESC tariffs (Subgroup A4, 2024–2025 cycle) were applied to the consumption and demand profiles collected, considering the full incidence of charges and taxes (ICMS and PIS/COFINS), in order to reflect the establishments' actual expenditure.

The simulation compared the two available tariff modalities: Blue (differentiated peak demand tariff) and Green (single demand tariff, but with a high peak TUSD). Table 5 details the monthly cost composition for each supermarket.

Table 5
Demand, TUSD, TE, and Tax Results for the Blue and Green Modalities.

	Sup. A	Sup. B	Sup. C
Peak Demand (BRL)	25,665.00	27,121.00	5,864.00
Off-Peak Demand (BRL)	12,397.00	13,105.40	2,833.60
Blue – Peak TUSD (BRL)	3,077.57	3,700.56	673.22
Green – Peak TUSD (BRL)	28,742.40	34,560.74	6,287.40
Off-Peak TUSD (BRL)	28,094.56	32,753.66	6,715.08
Peak TE (BRL)	13,159.01	15,822.79	2,878.53
Off-Peak TE (BRL)	75,315.83	87,805.92	18,001.77
Blue – ICMS + PIS/COFINS (BRL)	46,600.77	53,282.24	10,923.68
Green – ICMS + PIS/COFINS (BRL)	46,603.77	54,387.18	10,849.86
Total, Blue Modality (BRL)	204,299.27	233,591.57	47,889.89
Total, Green Modality (BRL)	204,312.47	238,435.69	47,566.25

The comparative evaluation of the tariff modalities reveals a direct correlation between the load profile and economic efficiency. For Supermarket A, a scenario of near equivalence was observed, with a marginal difference of less than BRL 20.00 between the options, suggesting a tariff break-even point. In contrast, for Supermarket B, the Blue modality proved economically superior, offering potential savings of approximately BRL 4,800.00 per month compared with the Green modality. This advantage stems from the cost structure of the Green tariff, which disproportionately penalizes high on-peak energy consumption (34.63 MWh) through a TUSD roughly nine times higher than that charged under the Blue modality. Supermarket C, consistent with its smaller size and reduced demand, confirmed the Green modality as the lowest-cost operating option.

Notwithstanding the theoretical advantage identified for the Blue tariff in the second establishment, it was methodologically decided to retain the Green modality costs as the baseline for all units in the subsequent analyses. This decision is based on the need to faithfully mirror the current contractual reality of the establishments analyzed. This ensures that the calculation of the savings generated by migration to the Free Market and by the implementation of new technologies reflects the real gain relative to the current actual situation, avoiding distortions arising from hypothetical prior optimizations in the captive market.

4.3 Savings in the Free Electricity Market

In this stage, the financial impact of migration to the ACL was assessed by simulating three contracting scenarios for each supermarket: Conventional Energy (no TUSD discount), 50% Incentivized Energy (i5), and 100% Incentivized Energy (i1). The analysis considers the trade-off between the energy price (MWh) — which is progressively higher for incentivized sources due to the scarcity of this supply in the market — and the savings generated by the discount on system usage tariffs (TUSD).

The analysis begins with Supermarket A. Table 6 details the projected monthly costs. It is observed that the i5 (50%) option offers the lowest total cost (BRL 150,556.47), outperforming both the Conventional and the i1 options. Although i1 energy almost entirely eliminates the peak TUSD cost, the high MWh price (BRL 341.00 vs. BRL 195.00 for i5) cancels out this benefit, resulting in a total cost even higher than that of conventional energy.

Table 6
Cost Analysis for Supermarket A.

	Conventional	i5	i1
Benefit factor	0%	50%	100%
Off-Peak Demand (BRL)	12,397.00	3,099.25	-
Peak TUSD (BRL)	28,742.40	15,909.98	3,077.57
Off-Peak TUSD (BRL)	28,094.56	28,094.56	28,094.56
Energy (BRL)	45,215.05	56,883.45	99,473.11
CEEE Charge (BRL)	3,954.48	3,954.48	3,954.48
ICMS + PIS/COFINS (BRL)	38,791.89	42,614.74	56,568.16
Total (BRL)	157,195.38	150,556.47	191,167.88

It is worth highlighting the tax calculation methodology: since the tariff discount (TUSD discount) is included in the ICMS calculation base in Santa Catarina, the tax is calculated on the "full" tariff value before the discount. This explains why the tax burden under the i1 option is disproportionately high (BRL 56,000), as it is levied on a more expensive energy tariff.

In the analysis of Supermarket B (Table 7), following the same trend, the optimal point is also found in contracting 50% Incentivized Energy. The monthly savings relative to the conventional scenario are approximately BRL 3,800. Compared with the captive market (BRL 238,435.69 under the Green modality), migration to the ACL in the i5 scenario (BRL 179,077.68) represents a significant 25% reduction in operating costs.

Table 7
Cost Analysis for Supermarket B.

	Conventional	i5	i1
Benefit factor	0%	50%	100%
Off-Peak Demand (BRL)	13,105.40	6,552.70	-
Peak TUSD (BRL)	34,560.74	19,130.65	3,700.56
Off-Peak TUSD (BRL)	32,753.66	32,753.66	32,753.66
Energy (BRL)	52,876.70	66,522.30	116,328.74
CEEE Charge (BRL)	4,501.67	4,501.67	4,501.67
ICMS + PIS/COFINS (BRL)	45,146.06	49,616.70	58,732.41
Total (BRL)	182,944.23	179,077.68	216,017.04

In the cost analysis of Supermarket C, the smallest unit (Table 8), the same logic holds. The i5 scenario resulted in a monthly cost of BRL 36,231.12. Compared with the captive market cost (BRL 47,566.25), the projected savings amount to 23.8%, confirming that migration is viable even for consumers with demand below 500 kW, who benefit from the market opening promoted by Ordinance No. 50/2022. These gains align with the findings of Teberge & Sodré (2019), according to whom the ACL is more advantageous due to negotiation flexibility and volume-based pricing. The convergence of these results reinforces that migration to the ACL is not merely an economic alternative, but a strategic management tool that frees the user from the rigid conditions imposed by local distribution utilities.

Table 8
Cost Analysis for Supermarket C.

	Conventional	i5	i1
Benefit factor	0%	50%	100%
Off-Peak Demand (BRL)	2,833.60	1,416.80	-
Peak TUSD (BRL)	6,287.40	3,480.31	673.22
Off-Peak TUSD (BRL)	6,715.08	6,715.08	6,715.08
Energy (BRL)	10,716.70	13,482.30	23,576.74
CEEE Charge (BRL)	1,490.63	1,490.63	1,490.63
ICMS + PIS/COFINS (BRL)	9,187.71	10,093.79	12,017.12
Total (BRL)	37,231.12	36,678.12	44,472.79

The comparative analysis between the captive market (baseline) and the free market (ACL) shows that contracting incentivized energy with a 50% discount (i5) is the dominant strategy for all three consumption profiles analyzed.

• Supermarket A: 26.3% savings (BRL 53,756/month).

• Supermarket B: 24.9% savings (BRL 59,358/month).

• Supermarket C: 23.8% savings (BRL 11,335/month).

These results corroborate similar studies, such as that of Fernandes (2024), who obtained a 29.66% reduction for an industrial profile. The consistency of gains above 20% validates migration to the ACL as the first and most impactful energy management measure to be adopted, regardless of supermarket size, even before considering capital-intensive investments (CAPEX) in self-generation or batteries.

4.4 Financial impact analysis of implementing photovoltaic panels

The objective of this stage was to assess the financial impact of implementing solar photovoltaic systems in the units, under the technical premise of zero-grid operation. In this model, the inverter limits instantaneous generation to the load demand, preventing the export of surplus energy to the utility grid. Consequently, all potential energy not consumed simultaneously is wasted, which negatively affects the unit cost of the energy generated (LCOE).

The installed capacity (kWp) was computationally optimized for each supermarket, seeking the point of minimum LCOE in both the captive and free market scenarios. For the initial investment (CAPEX), the market reference from GREENER (2024) was used: BRL 3.00/Wp for systems above 500 kWp and BRL 3.10/Wp for systems between 75 kWp and 150 kWp. Table 9 summarizes the optimal sizing and the resulting financial indicators.

Table 9
Analysis for the Supermarkets Considering the Implementation of Photovoltaic Panels.

	Sup. A	Sup. B	Sup. C
Captive (kWp)	1046	1214	160
Free (kWp)	896	1045	137
Captive (BRL)	3,181,000.00	3,642,000.00	496,000.00
Free (BRL)	2,688,000.00	3,135,000.00	424,700.00
Payback – captive (years)	4.49	4.46	4.60
Payback – free (years)	5.55	5.52	5.71
Photovoltaic LCOE – captive (BRL/MWh)	727.55	734.55	747.92
Photovoltaic LCOE – free (BRL/MWh)	598.98	601.11	611.94

The detailed analysis of the corrected data reveals strategic nuances that are fundamental for decision-making. First, the optimized installed capacity for the free market is systematically lower than that projected for the captive market. For Supermarket A, for example, the suggested capacity falls from 1,046 kWp to 896 kWp in the transition between environments. This resizing occurs because, in the free market, the cost of grid energy is significantly lower; consequently, the optimization algorithm avoids oversizing that would generate uncompensated surplus energy, focusing strictly on the generation that ensures immediate self-consumption and maximizes financial efficiency.

Regarding investment attractiveness, the payback period is highly competitive in the captive market, at around 4.5 years. This result converges with similar case studies in Brazilian supermarkets, such as that of Almeida & Altoé (2022), who identified a payback period of approximately 5 years for photovoltaic systems in the retail sector. This performance is driven by the need to offset a high tariff burdened by various sector charges. In the free market, by contrast, the capital return extends to approximately 5.5 years, since the "competition" is with cheaper grid energy, which reduces the monthly savings margin. Despite this increase, a payback period below six years is considered highly viable for infrastructure assets with an estimated service life of 25 years, confirming the robustness of solar technology in both scenarios.

Finally, the LCOE analysis under the zero-grid configuration indicates values between BRL 600.00 and BRL 750.00/MWh, levels higher than those typically observed in grid-injection systems (BRL 150.00 to BRL 250.00/MWh). It is essential to clarify that this higher unit cost does not stem from equipment inefficiency, but rather from the operational constraint intrinsic to the model, which prevents the export of surplus energy. The intentional curtailment of energy during periods of low demand at the unit — such as on Sunday mornings — increases the average cost of the kilowatt-hour effectively used. However, this strategy offers, in return, the elimination of dependence on complex grid access approvals and exemption from taxation on injected energy (Fio B), ensuring greater regulatory autonomy for the consumer.

4.5 Financial impact analysis of implementing Battery Energy Storage Systems (BESS)

The sizing of the BESS was guided by the peak-shaving strategy. The technical objective was to define the minimum capacity required to supply the units' demand during the three peak hours (6:30 p.m. to 9:30 p.m.), avoiding grid consumption when the tariff is most costly.

Table 10 presents the capacity sizing (MWh), the initial investment (CAPEX), and the resulting financial indicators. The comparison of the average cost per megawatt-hour (BRL/MWh) with and without the use of batteries is highlighted.

Table 10
Analysis for the Supermarkets Considering the Implementation of BESS.

	Sup. A	Sup. B	Sup. C
Sizing, captive and free (MWh)	1.700	2.040	0.255
Total CAPEX (BRL)	2,637,448.00	3,164,937.60	395,617.20
Captive / without BESS (BRL/MWh)	700.40	698.94	687.97
Captive / with BESS (BRL/MWh)	579.64	607.20	390.63
Free / without BESS (BRL/MWh)	501.79	510.68	516.19
Free / with BESS (BRL/MWh)	453.46	473.71	364.38
Estimated LCOE – captive (BRL/MWh)	833.02	828.83	829.76
Estimated LCOE – free (BRL/MWh)	675.89	670.47	671.67
Payback – captive (years)	8.35	7.75	8.03
Payback – free (years)	10.81	10.10	10.69

The data analysis reveals a balance between operational performance and financial feasibility. From a technical standpoint, BESS demonstrated high effectiveness in reducing the average energy cost. In Supermarket C (captive market), for example, the technology reduced the MWh cost from BRL 687.97 to BRL 390.63. This performance is due to the batteries' ability to supply the load during peak hours, eliminating grid consumption precisely when tariffs (peak TUSD) are highest under the Green modality.

However, this technical efficiency is offset by the high CAPEX. Although operation reduces the monthly bill, the LCOE of the batteries still exceeds the cost of grid energy in several scenarios. This observation aligns with the findings of Freitas et al. (2025), who, in analyzing the life cycle of a BESS in a public institution, emphasized that, although the system is technically viable for peak-shaving strategies, the high initial investment and operating costs over the project horizon remain the main barriers to full financial feasibility. Therefore, the financial unfeasibility observed in some cases does not stem from any immaturity of the technology — which proved fully functional and suitable for the service — but rather from the high initial capital required for its implementation.

Regarding returns, the captive market presents a payback period of approximately 8 years, approaching feasibility due to the high cost of the avoided peak tariffs. In the free market, the payback period exceeds 10 years. This occurs because the cost of energy in the free market is already low, which narrows the additional savings margin generated by the battery and prolongs the investment recovery time.

Although the current results point to the financial unfeasibility of BESS due to its high capital cost, making this technology viable in the retail sector depends on advances in the regulatory environment and on public policy. Mechanisms such as tax incentives for the import and manufacture of components, as well as dedicated financing lines with subsidized interest rates, are essential to reduce the impact of CAPEX. In addition, the regulation of new business models, such as remuneration for grid services (ancillary services) and technological innovation programs, can create complementary revenue streams, accelerating the return on investment and sustainably integrating storage into national energy planning.

In summary, when comparing the technologies analyzed, the photovoltaic solution offers a lower LCOE and a significantly faster return on investment, ranging from 4 to 6 years, in contrast to the 8 to 10 years required by battery systems. Therefore, in the 2025 economic scenario, standalone BESS used exclusively for peak shaving still faces competitiveness challenges relative to solar generation and migration to the free market. Its adoption is fully justified only in situations where energy security — such as the need for backup against outages — is a critical operational requirement, adding strategic value that goes beyond mere tariff savings.

As observed in optimization studies in other electricity-intensive sectors, where process readjustments can generate savings exceeding 10% (Menezes et al., 2024), the results for the supermarket sector in Santa Catarina reinforce that the strategic management of tariff periods is the most viable path to financial competitiveness.

Although the results of this study provide a solid basis for the retail sector, the application of these strategies in other regions of Brazil should be approached with caution. Factors such as the natural variation in solar irradiation and the climate of each state directly influence the performance of self-generation. Moreover, differences in local distribution utility tariffs an state-specific tax regulations affect the investment payback period. Thus, while the analytical logic presented is valid for any location, the final financial results depend on the specific conditions of the region where the supermarket is located.

5 Conclusion

This study analyzed the technical and economic feasibility of energy management strategies for the supermarket sector in Santa Catarina. The results show that migration to the FEM is the solution with the greatest immediate impact, providing reductions of 25% to 28% in monthly costs through the contracting of incentivized energy (50% discount).

Photovoltaic generation in the zero-grid configuration established itself as a solid medium-term alternative, with an attractive payback period of 4.5 to 5.5 years. In contrast, the BESS for peak shaving, although technically effective in reducing peak demand, proved economically unfeasible under current conditions, with returns exceeding 8 years due to the high CAPEX.

The main contribution of this study reveals that the feasibility of the solutions is independent of the establishment's size, being determined primarily by the tariff structure and the load profile. This finding complements prior evidence on how firm size conditions the adoption of energy management systems (Reis et al., 2020): while company size may shape the propensity to adopt such systems, it does not determine their economic feasibility, which is governed instead by the contractual and tariff arrangements available to each consumer. As a managerial guideline, it is recommended that the sector prioritize contract migration and solar generation before investing in storage. For future work, it is suggested to investigate the feasibility of BESS in regions with more aggressive peak tariffs, or the use of batteries for ancillary services, in line with the downward trend in the global costs of lithium technologies.

• Financial support:
  None.
• How to cite:
  Nascimento, F. O., Volan, T., & Vaz, C. R. (2026). Economic feasibility of energy strategies in retail: a comparative analysis of the Free Electricity Market, Zero-Export photovoltaic systems, and BESS in supermarkets in Santa Catarina, Brazil. Gestão & Produção, 33, e15225. https://doi.org/10.1590/1806-9649-2026v33e15225

Statement on Data Availability

All data generated or analyzed during this study are included in this published article.

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• Editor-in-Chief
  Pedro Munari

Publication Dates

• Publication in this collection
  10 Aug 2026
• Date of issue
  2026

History

• Received
  09 Dec 2025
• Reviewed
  31 Mar 2026
• Accepted
  28 May 2026