A Scenario-Based Simulation Study for Economic Viability and Widespread Impact Analysis of Consumption-Side Energy Storage Systems

Abstract

This study investigates energy storage within the contexts of production-side and consumption-side energy storage concepts. The theoretical advantages of consumption-side energy storage over production-side systems are initially explored. The analysis is supported by a scenario-based simulation, with results presented to assess the feasibility and applicability of consumption-side energy storage under varying conditions. The simulation examines multiple scenarios, incorporating economic assessments to evaluate the viability of such systems. Additionally, the study explores the broader impact of consumption-side energy storage when adopted by 5 million, 10 million, 20 million, and 40 million residential consumers across separate scenarios. The analysis emphasizes the potential for shifting peak-period energy consumption to nighttime usage and assesses the corresponding reduction in energy generation requirements and transmission line loads, alongside the economic benefits derived from postponing energy infrastructure investments. The study focuses exclusively on residential consumers, with the energy storage systems referred to as residential energy storage systems (RESS). These systems are assumed to be organized and managed by energy provider companies rather than individual consumers. The research also considers the potential costs associated with implementing RESS. The simulation-based findings reveal significant benefits, including reduced reliance on new power plants, decreased risk of transmission line overload, increased utilization of renewable energy resources, financial advantages for both energy providers and consumers, and positive environmental impacts. These results provide valuable insights with implications for shaping future energy policies, particularly in the United States.

1. Introduction

The provision of electric energy brings comfort and convenience to modern life, but it requires significant challenges to be addressed in the background to ensure uninterrupted production, transmission, and distribution. For example, during peak hours, the capacity of critical transmission lines often operates at an average of 90% and, at times, approaches maximum capacity [1]. There are instances when energy production struggles to meet consumption demands, leading to reductions in energy quality or even power outages. Historical events have shown that significant voltage drops have left millions of people without electricity [2]. Additionally, climate challenges and natural disasters exacerbate these difficulties. Alongside these issues, the ever-increasing demand for energy necessitates the construction of new power plants and transmission lines, all while efforts are made to minimize environmental impacts.

Consumption-side energy storage presents a potential solution to these challenges. This concept involves consumers storing inexpensive electricity—either purchased from the grid during night hours or self-generated—and utilizing it during peak hours. If implemented on a large scale, this approach has the theoretical potential to address the aforementioned challenges effectively. The key benefits include limiting peak energy demand, shifting consumption to night periods, reducing the need for peak-hour energy generation, alleviating the strain on transmission lines, delaying the necessity for new infrastructure investments, and mitigating environmental harm. Additional advantages include minimizing consumer disruptions during outages, reducing compensation liabilities for energy providers, increasing the utilization of renewable energy sources such as hydroelectric, geothermal, and wind power during off-peak hours, and facilitating the broader adoption of renewable energy systems through the existing inverter infrastructure.

However, under current conditions, widespread adoption of consumption-side energy storage systems is not yet viable. This article researches the possibility of making these systems feasible by meeting necessary conditions and demonstrates, through a scenario-based simulation study, that achieving widespread adoption can deliver significant benefits.

This study assumes that consumption-side energy storage systems are organized by energy provider companies rather than individual consumers. The simulation focuses on energy storage in residential areas, as peak energy demand in the United States is highest in the residential sector [3,4,5]. These systems are referred to as residential energy storage systems (RESSs). This study builds upon the author’s previous research, which emphasized that RESSs must be organized by energy provider companies to ensure practicality and effectiveness [6].

When the term residential energy storage systems is referenced in the literature, it typically pertains to storage systems integrated with renewable energy sources, smart building applications, or microgrid setups [7,8,9,10]. This study primarily considers that a RESS is an independent energy storage system that stores electricity during night hours and supplies it during peak hours.

Although consumption-side energy storage is a globally applicable concept, this article focuses on the energy system of the United States (U.S.). The U.S. energy system operates under diverse models, including vertically integrated utilities, deregulated markets, municipal utilities, and cooperatives [11,12,13,14]. Widespread adoption of consumption-side energy storage could be facilitated by subunits, such as retail energy providers in deregulated markets or suitable entities in other models. For simplicity, this article refers to these entities collectively as energy provider companies (EPCs).

Achieving the widespread impact of consumption-side energy storage and realizing the anticipated significant benefits primarily depends on analyzing the feasibility of energy storage systems for consumers. To analyze this feasibility, this research is supported by a two-phase simulation study.

In the first phase of the simulation, various scenarios are developed to address how energy storage systems intended for consumer use can be organized and how their economic dimensions can be managed. Economic analyses are conducted based on these scenarios, considering the potential costs of energy storage systems and contributions from EPCs, consumers, external sponsors, and the effects of grants and interest rates provided by external sponsors.

In the second phase, scenario-based analyses are performed to demonstrate the substantial benefits that could be obtained in the event of significant widespread adoption of consumption-side energy storage. These scenarios assume varying numbers of consumers using energy storage systems—5 M, 10 M, 20 M, and 40 M. For each scenario, analyses are conducted on the amount of power shifted from peak to night hours, the reduction in transmission line load, the decrease in energy production requirements, and the resulting economic gains from deferred investments in new energy infrastructure.

It is well established that energy storage encompasses a wide range of types and applications. Some energy storage systems contribute to the production side, while others provide benefits to the consumption side. Studies on production-side energy storage are typically categorized in the literature under terms such as “grid-scale” or “large-scale” energy storage [15,16,17,18,19]. Conversely, research on consumption-side energy storage systems is generally found under the terms “user-side” or “demand-side” energy storage systems [20,21,22,23,24]. When widespread adoption of consumption-side energy storage is achieved, it can substantially reduce energy consumption during peak hours. The immense benefits targeted in this study largely derive from this reduction in peak consumption. Therefore, this article classifies energy storage systems as either production-side or consumption-side as a novel concept.

There is no specific study in the literature yet to classify energy storage systems in this way and then compare these two classes. The reason for this gap can be explained by the fact that consumption-side energy storage systems are not used sufficiently and therefore a noticeable widespread effect has not been formed. The biggest factor behind this situation is undoubtedly related to the fact that these systems are not profitable enough yet and cannot amortize themselves in a reasonable period of time [25]. As a result, consumption-side energy storage applications are mostly limited to applications emphasizing consistent and reliable energy needs.

On the production side, large-scale energy storage systems undeniably contribute significantly to improving the efficiency of power plants and maintaining grid stability. However, in theory, implementing energy storage on the consumption side—where consumers acquire storage systems tailored to their needs—holds the potential for even greater benefits. Beyond the advantages listed earlier, when energy outages occur due to reasons such as natural disasters, overloads or unexpected failures, having energy storage systems in homes can provide significant benefits in terms of preventing consumers from being victimized and protecting energy companies from having to pay compensation. In addition, energy storage on the consumption side also prepares the necessary infrastructure, to a large extent, for the widespread use of renewable energy. An energy storage system can be transformed into a solar energy system by simply adding solar panels [26,27] and even into a microgrid system [28,29,30,31] if the necessary infra-structure is prepared.

Section 2 compares production-side and consumption-side energy storage, highlighting the advantages of consumption-side energy storage. Section 3 delves into the fundamental characteristics of residential energy storage systems (RESSs) within the consumption-side energy storage concept. This section also explains why the simulation study excludes commercial and industrial consumers. Section 4 evaluates the economic feasibility of RESSs. Section 5 describes the simulation’s organization and the functions of its modules. Section 6 analyzes the simulation results to underscore the importance of consumption side energy storage.

In the conclusion section, the striking conclusions obtained from these analyses are presented for the attention of the scientific world, energy companies, and the authorities that determine energy policies in the U.S. and other countries of the world.

2. Comparison of Production-Side and Consumption-Side Energy Storage

Production-side energy storage systems can be considered a different type of power generation facility. Like other power plants, they rely on energy transmission and distribution networks to deliver stored energy to consumers [32,33,34,35,36]. In contrast, consumption-side energy storage systems are located within consumer premises, either avoiding the use of energy transmission lines entirely or utilizing a limited local network [9,37,38,39,40]. Production-side energy storage systems generally involve large-capacity systems, whereas consumption-side energy storage systems consist of numerous small-capacity units. The capacity of a consumption-side energy storage system is tailored to the consumer’s energy consumption requirements.

The fundamental characteristics and benefits of production-side and consumption-side energy storage are addressed separately below.

Energy storage on the production side increases the efficiency of power plants, ensures that excess energy is stored and utilized, and maintains the stability of the energy network by contributing to the increase in production when consumption increases [41,42,43].

When an energy production plant owner installs a large-scale energy storage system in addition to the energy production plant, the owner can increase the efficiency of the power plant, both physically and economically. For example, short-term interruptions in solar and wind energy production plants are prevented with the contribution of energy storage systems, and the energy produced is made continuous and stable [44,45,46,47,48,49,50]. The excess energy produced at night or the energy that would normally be sold cheaply is stored to be sold during the hours when energy prices are high, thus increasing the efficiency of energy production plants economically [51,52]. All the applications mentioned above have benefits in maintaining the stability of the energy system [53,54]. Especially during peak hours when energy consumption increases a lot, the provision of energy to the grid by large-scale energy storage systems in addition to energy production plants is an important benefit in preventing grid collapses [55,56,57,58].

3. Consumption-Side Energy Storage and Residential Energy Storage Systems (RESSs)

In this study, the analysis of consumption-side energy storage focuses on residential consumers, with the energy storage systems installed in their homes referred to as residential energy storage systems (RESSs). Initially, commercial and industrial consumers were not prioritized for consumption-side energy storage. The primary reason for excluding commercial areas is the decline in consumption during peak hours in many commercial settings. Additionally, as commercial areas mainly consist of stores and offices, finding suitable spaces for RESS installation may be more challenging.

Industrial areas, however, present significant potential for consumption-side energy storage applications. However, the energy storage systems in industrial areas need to be approached differently from those in residential areas. This is because industrial consumers are generally high-power users with direct access to cheaper energy.

The feasibility of implementing an RESS depends on energy prices and the system’s cost. Although the technology required for RESSs is now sufficiently mature and can be considered commonplace, and all functions required for the operation of an RESS can already be performed by a smart inverter, it does not seem feasible to expect the implementation of RESSs to be organized by residential consumers. This is due to residential consumers lacking access to cheap energy, lacking the ability to acquire RESS systems at low costs, and not having sufficient knowledge on the topic. However, as proposed in the author’s previous study [9], if RESS deployment is organized by EPCs, significant benefits can be achieved for EPCs, residential consumers, and the national economy. Furthermore, RESSs could provide substantial advantages in overcoming temporary energy crises caused by natural disasters or unforeseen failures. Humanity now lives in an era heavily dependent on energy, and stored energy that ensures uninterrupted energy comfort has become a critical factor.

According to the proposed concept, EPCs can make RESSs feasible by storing cheap energy obtained during night periods in RESS units installed in residential areas and selling this energy back to residential consumers during peak periods at peak-period prices. This approach enables EPCs to achieve approximately 62% higher profits than standard practices (Table 1). For this model to be sustainable, EPCs should allocate a portion of the additional economic revenue generated toward RESS costs, share another portion with consumers hosting RESS units, and retain the remainder for themselves. Alternatively, EPCs and consumers may seek support from external sponsors to facilitate this organization.

The most critical and costly component of an RESS device is the battery. The battery’s cost and lifespan directly impact the feasibility of RESSs. While various battery types can be used in RESS applications, the most suitable alternatives are lithium-ion (Li-Ion) and lithium-iron phosphate batteries. Comparing these two types, LiFePO4 batteries are more favorable for RESS applications, in terms of both especially cost and cycle life. Thus, this simulation study uses LiFePO4 batteries.

Based on the cycle life of LiFePO4 batteries, agreements between energy provider companies and residential consumers who agree to use RESSs are expected to last 10–12 years. This duration aligns with the average lifespan of LiFePO4 batteries, which ranges from 2000 to 10,000 cycles, assuming one charge–discharge cycle per day. EPCs require this critical duration to generate sufficient revenue to cover RESS costs and achieve the desired economic benefits. Although the energy density of LiFePO4 batteries is not as high as that of Li-Ion batteries, finding enough space for batteries in residential areas is not as critical an issue as it is in electric vehicles. Additionally, LiFePO4 batteries are more attractive for RESS applications due to their safety, environmental concerns, energy loss, and recycling, compared to lithium-ion batteries [59,60,61,62,63,64,65,66,67].

Table 1. Comparison of Li-Ion and LiFePO4 batteries.

Battery	Energy Density (Wh/kg)	Lifespan (Cycles)	Depth of Discharge (DoD) (%)	Safety	Environm. Concerns	Price	Energy Loss	Recycling
Li-Ion Batteries	150–250	1500–2500	80–90	Higher risk of overheating and thermal runaway	Toxic metals like cobalt can be harmful	Typically higher due to higher energy density	Moderate (due to heat generation)	Challenging; involves toxic materials such as cobalt
LiFePO4 Batteries	90–150	2000–10,000	90–100	Much safer; lower risk of thermal runaway	More environmentally friendly; no cobalt or nickel	Generally lower; more cost-effective over lifespan	Low (more efficient charge/discharge)	Easier; environmentally friendlier, with fewer toxic components

The environmental impact of battery technologies extend beyond their use phase, particularly in material sourcing and end-of-life management. Li-Ion batteries often contain cobalt and nickel, which are metals associated with environmentally harmful mining practices and significant human rights concerns in extraction regions. Their recycling involves complex processes, due to the presence of toxic metals, requiring specialized facilities to prevent soil and water contamination. LiFePO4 batteries, however, use phosphate-based chemistry, which is free of cobalt and nickel, reducing both extraction concerns and toxicity risks. Their simpler chemical composition makes recycling less hazardous and more energy-efficient, contributing to a lower overall environmental footprint. (OpenAI ChatGPT (Version GPT-4) [63,64,65,66,67].

Table 1. Comparison of Li-Ion and LiFePO4 batteries.

Battery	Energy Density (Wh/kg)	Lifespan (Cycles)	Depth of Discharge (DoD) (%)	Safety	Environm. Concerns	Price	Energy Loss	Recycling
Li-Ion Batteries	150–250	1500–2500	80–90	Higher risk of overheating and thermal runaway	Toxic metals like cobalt can be harmful	Typically higher due to higher energy density	Moderate (due to heat generation)	Challenging; involves toxic materials such as cobalt
LiFePO4 Batteries	90–150	2000–10,000	90–100	Much safer; lower risk of thermal runaway	More environmentally friendly; no cobalt or nickel	Generally lower; more cost-effective over lifespan	Low (more efficient charge/discharge)	Easier; environmentally friendlier, with fewer toxic components

The environmental impact of battery technologies extend beyond their use phase, particularly in material sourcing and end-of-life management. Li-Ion batteries often contain cobalt and nickel, which are metals associated with environmentally harmful mining practices and significant human rights concerns in extraction regions. Their recycling involves complex processes, due to the presence of toxic metals, requiring specialized facilities to prevent soil and water contamination. LiFePO4 batteries, however, use phosphate-based chemistry, which is free of cobalt and nickel, reducing both extraction concerns and toxicity risks. Their simpler chemical composition makes recycling less hazardous and more energy-efficient, contributing to a lower overall environmental footprint. (OpenAI ChatGPT (Version GPT-4) [63,64,65,66,67].

4. Economic Analysis of the Applicability of RESSs

The number of years it will take for an RESS to pay for itself depends on the daily consumption amount, energy prices, and the production cost of the RESS device. RESS usage does not seem economically viable for consumers with very low consumption power. However, when we look at the statistics, the average electrical energy consumption in the peak period for consumers in residential areas in the U.S. is 11.8 kWh [3,4,5,68]. This amount is sufficient for RESS application.

Table 2. Energy prices and profits of EPCs during different periods.

	Period	Wholesale Price	Retail Price	Average Profit
Current Application	Daytime	USD cents 0.2–0.4/kWh	USD cents 10–15/kWh	USD cents 5–10/kWh
	Peak	USD cents 5–15/kWh	USD cents 15–30/kWh	USD cents 10–15/kWh
	Night	USD cents 1.5–3/kWh	USD cents 8–12/kWh	USD cents 5–8/kWh
RESS Application	Peak	-	USD cents 15–30/kWh	USD cents 20.25/kWh
	Night	USD cents 1.5–3/kWh	-

The daily amount that a residential consumer pays to an EPC is 11.80 × 22.50 cents = USD 2.65. The EPC receives 11.8 × 12.5 cents = USD 1.47 in daily income from this residential consumer. Thanks to the RESS system, the EPC earns 11.80 × 20.25 cents = USD 2.39 daily from the residential consumer. Thanks to RESS, the EPC earns USD 2.39–USD 1.47 = USD 0.91 extra daily income from the residential consumer. Comparing the current daily income of EPC (USD cents 1.475) and RESS income (USD cents 2.39), it is seen that RESS income is 62% higher than the current daily income of the EPC (1.475c + (1.475c × 62%) = USD cents 2.39.

, considering the average energy purchase and sale prices in the U.S., displays at what prices an EPC buys electrical energy from producers during the day, night and peak periods, at what price it sells to consumers, and how much profit is made on a daily basis. The daily average energy consumption amount for residential consumers is also shown in Table 2. Although these data may vary depending on grid areas, seasons, and special circumstances in the U.S., they can provide an idea of the applicability of an RESS [69,70,71,72].

Based on the data in Table 2, an EPC that purchases energy at nighttime rates, stores it in an RESS, and sells it during peak periods achieves an average profit margin 62% higher than their normal margin. If this practice continues for the lifespan of the LiFePO4 batteries used in the RESS, which is approximately 10–12 years (4380 days), the financial outcomes over a 12-year RESS agreement are summarized in

Table 3. Financial outcomes of EPCs with RESS integration over a 12-year period.

Application Type	Economic Profit Rates of EPCs	Daily	12 Years (4380 Days)
Normal Operations	The daily and 12-year amount a residential consumer pays to an EPC	USD 2.65	USD 11.62
	The income that an EPC receives from a residential consumer on a daily basis and over a 12-year period	USD 1.47	USD 6.46
RESS Operations	The income that an EPC receives from a residential consumer on a daily basis and over a 12-year period.	USD 2.39	USD 10.46
	Total amount of extra income earned by an EPC daily and for 12 years	USD 10.46–USD 6.46 = USD 4006 (accepted as USD 4000)

.

Another important factor affecting the feasibility of RESSs (residential energy storage systems) is the potential cost of the devices. The main components of an RESS include LiFePO4 batteries, inverters/chargers, switching systems, cooling fans, necessary measurement components, displays, and essential metal parts. Among these components, LiFePO4 batteries and inverters/chargers are undoubtedly the most expensive.

According to recent market statistics, LiFePO4 battery prices are expected to drop below USD 75 per kWh by 2030 [73,74,75]. Considering the high-volume purchases anticipated for RESS applications, a price of USD 70/kWh for LiFePO4 batteries can be assumed.

Inverter/charger prices vary depending on their power ratings and estimated usage duration. For a 5 kW inverter/charger with an expected service life of 12 years, the average market price in bulk purchases ranges between USD 1000 and USD 2500. However, it is more appropriate for inverters/chargers in RESS systems to be integrated as embedded units within the system rather than standalone devices. Therefore, lower prices than those mentioned above are possible. Additionally, given the high number of RESS units expected to be deployed over the long term, bulk purchasing of materials will likely result in significant cost reductions. As a result, the cost of an inverter/charger is estimated at USD 800.

The remaining budget for switching systems, cooling fans, necessary measurement components, displays, essential metal parts, miscellaneous components, and labor can be set at USD 700.

Thus, the total cost of an RESS with a storage capacity of 10–15 kWh and an inverter power rating of 5 kW is expected to range between USD 2200 and USD 2500. For instance, as shown in Table 3, a calculation based on the daily average energy consumption of a residential consumer during peak periods (11.8 kWh) yields a RESS cost of USD 2420, which falls within the USD 2200–USD 2500 range.

For consumers with higher consumption than the average, the profit margins presented in Table 3 also increase, making higher RESS costs manageable. Additionally, since the costs of components including switching systems, fans, measurement tools, displays, metal parts, and labor expenses do not vary significantly, there may be partial economic advantages. However, the same cannot be said for consumers with low power consumption. For these users, the high cost of RESSs remains significant compared to the lower profit margins. Therefore, it would be more suitable to propose RESS applications for residential consumers with peak-period consumption exceeding 10 kW.

Based on Table 3, a RESS generates USD 4000 additional profit over 12 years.

Table 4. Component costs of a RESS system.

RESS Components	Total Price (USD)	Explanation
LiFePO4 battery	920	for 13.11 kWh
Inverter/charger	800	for 5 kW
Other components: Switching system, cooling fans, necessary measuring components and displays, necessary metal parts and installation	700
Total price (USD)	2420

shows an average RESS cost of USD 2420, indicating that these profits can comfortably cover the system’s cost. To ensure sustainability, profit-sharing between residential consumers and EPCs is recommended. Even if consumers see no direct financial benefits, uninterrupted energy supply remains a significant advantage. Offering residential consumers, a 5–10% discount on bills for adopting RESSs could make the system more attractive and sustainable. Simulations suggest discounts in the bills could range from 0% to 13%, depending on different scenarios.

If a sensitivity analysis is performed regarding the applicability of RESSs, it is seen that the most important factor is energy prices, because a small change in the difference between the buying and selling prices of energy can cause a significant change in an average period of 10 years, which affects the applicability of RESSs. Other factors include battery prices. The fluctuations in battery prices can affect the cost of RESSs because, as seen in the example calculation above, the battery cost constitutes about 40% of the total cost of an RESS. Low consumption power is another factor affecting the applicability of RESSs, but the effect of this factor is quite low compared to other factors, because, within 130 M subscribers, it is possible to select subscribers with more suitable consumption power for RESS application.

5. Simulation of Energy Storage in Residential Areas and Widespread Impact Analysis

5.1. Objective of the Simulation

The objective of this simulation is to generate various outcomes based on different scenarios to analyze the potential benefits for both EPCs and consumers when energy storage systems are installed in residential areas. Additionally, the simulation aims to evaluate the possible national benefits resulting from the widespread impact created when the number of such systems reaches the desired level.

5.2. General Data Used in the Simulation

5.2.1. General Information About Electric Consumer Accounts

Table 5. Number of consumers.

Consumer Type	Number of Consumers
Residential area	130 M
Commercial area	22 M
Industrial area	814,000
Total number of consumers	152.8 M

Daily average peak period consumption for residential consumers: 11.8 kWh. Daily average peak period power for residential consumers: 2.4 kW.

presents the number of electricity consumers in the United States, along with the average energy consumption and power data for residential consumers during peak periods (OpenAI ChatGPT (Version GPT-4) was employed to assist in summarizing and organizing data) [76,77,78].

Table 6. Average power generation and consumption in the United States.

Generation Power (GW)	General (GW)	WECC (GW)	MRO (GW)	ERCOT (GW)	SERC (GW)	RF (GW)	NPCC (GW)
Daytime period	670	150	95	80	120	140	85
Peak period	730	170	100	90	130	150	90
Nighttime period	590	110	90	75	110	130	75
Consumption power (GW)
Daytime (Total):	667.5
Residential:	260	57.5	37.5	32.5	47.5	52.5	32.5
Commercial:	240	57.5	32.5	27.5	42.5	47.5	32.5
Industrial:	167.5	35	27.5	22.5	27.5	37.5	17.5
Peak period (Total):	730
Residential:	290	60	40	40	55	60	35
Commercial:	270	55	35	35	50	55	35
Industrial:	170	40	27	22.5	30	40	17
Nighttime (Total):	440.2
Residential:	165.2	27.7	22.5	22.5	32.5	37.5	22.5
Commercial:	155	27.5	22.5	17.5	32.5	32.5	22.5
Industrial:	120	22.5	17.5	17.5	22.5	27.5	12.5

presents the production and consumption data from the United States, both in aggregate and for each grid area separately. It also includes data on daytime, peak, and nighttime consumption by residential, commercial, and industrial consumers (OpenAI ChatGPT (Version GPT-4) was employed to assist in summarizing and organizing data) [68,79]. The table reveals a high degree of similarity in the production-to-consumption ratios across the grid areas in the United States, indicating that RESS analysis results can be generalized nationwide.

5.2.2. Energy Prices, RESS Costs, and Economic Return Criteria

The energy prices, RESS costs, and economic return criteria used in the simulation are drawn from the detailed discussion in Section 4. The loss of monetary value due to inflation is disregarded in these calculations.

5.2.3. Determination of Load Capacity on Energy Transmission Lines and Future Projections

When the U.S. Department of Energy’s National Transmission Needs Study—October 2023 report [80] is examined, it can be concluded that the average loading on key energy transmission lines during peak hours is 90%. Therefore, using the peak period consumption of 730 GW in Table 6, the maximum consumption is assumed to be 812 GW. To better evaluate the widespread impact of RESS, it is assumed that this critical load level will increase by 10–11% in the coming years, reaching 900 GW. This increase is projected to occur in approximately 13.66 years (OpenAI ChatGPT (Version GPT-4) was employed to assist in summarizing and organizing data) [81,82,83,84].

Based on this information, it can be roughly determined how many consumers need to use RESS in order to have a significant widespread effect. If it is estimated that the RESS application will be implemented in 10–15 years, it can be assumed that the maximum capacity of the power lines at the end of this period will be around 900 GW and the necessary calculations can be made to this level. In this case, if it is estimated that the 900 GW capacity will increase by 10% in the next 10 years to 990 GW, the number of consumers using RESS will reach 37.5 M, in order for the number of residential consumers with an average power of 2.4 kW to meet the 90 GW difference power. This number can be accepted as 40 M with some tolerance.

5.2.4. Scenarios and Calculations for Widespread Impact Analysis

For the widespread impact analysis, it is assumed that RESS adoption will progress incrementally, starting with 5 M consumers, then reaching 10 M, 20 M, and finally 40 M consumers. With 130 M residential consumers in total, 40 M represents 30% of the total consumers on average [76,77,78].

5.2.5. Economic Data on Energy Production and Transmission Investments

When general data on transmission line investments in the United States and previously constructed projects are examined, a generalization can be made as seen below [85,86,87,88,89,90,91,92,93].

Energy production investment per 1 GW: USD 500 M, requiring 1 year.

Energy transmission capacity increase per 1 GW: USD 300 M, requiring 2 years.

5.3. Functions of Simulation Modules (Parts)

The flow chart in Figure 1 explains the workflow of the simulation. The details of the inputs and outputs are explained by the Matlab Simulink R2024b blocks presented in the following figures (Figure 2, Figure 3, Figure 4, Figure 5 and Figure 6). Although the flow chart and Matlab Simulink blocks generally overlap, there are some differences in the details due to common data usage and common functions.

5.3.1. Part 1

This part calculates the number of consumers and their average consumption power during peak periods for residential, commercial, and industrial areas (Figure 2). The total consumption power is calculated by multiplying the average consumption power per consumer by the number of consumers and then converting the units from kW to GW. Scenarios for future years are generated by adjusting the average power per consumer and the number of consumers. Additionally, the “rate of increase in total consumption” coefficient can be directly modified to adjust total consumption figures.

5.3.2. Parts 2 and 3

The applicability of RESS depends on energy prices and the cost of RESS. In Part 2 (Figure 3), energy prices and the daily amount of money paid for energy by a residential consumer with an average consumption power according to these prices, and the average daily economic gain obtained by EPCs from a consumer with an average consumption power, are considered. In addition, the daily extra economic income obtained by EPCs when they use the RESS system, buy electricity at a night price and sell it at a day price is calculated. Using this information and assuming that the average life of LiFePO4 batteries is approximately 12 years, the consumers’ bill for the peak period, conventional annual revenue of an EPC for the peak period, annual revenue of the EPC for the peak period with RESS application, and total profit of the EPC for the RESS application values are calculated. The total profit of the EPC for the RESS application value is accepted as the highest possible profit amount and this value is used as a reference value in calculating other profit rates.

In Part 3, an estimated RESS cost is calculated by taking into account the prices of the components that make up the RESS (Figure 4). The RESS cost is a criterion that significantly affects the attractiveness of the RESS application. For this reason, the factors that affect the RESS cost are also added to the simulation. Thus, analyzes how the changes in the RESS cost affect the economic gains of EPCs and residential consumers.

Since the depth of the discharge (DoD) rate in LiFePO4 batteries varies between 85–95% on average, the DoD rate is accepted as 90% in the simulation and the calculated LiFePO4 battery capacity is multiplied by the coefficient 1.11.

Part 3 also includes scenarios on how organizations can be made to cover the RESS costs. How each scenario affects the profit rates of the EPC and the consumer is analyzed. The results of different scenarios are shown in

Table 7. Organization scenarios that can be applied to cover the RESS cost.

Scenario	Cost Coverage Ratio for EPC (%)	Cost Coverage Ratio for Consumer (%)	External Sponsor		Increase Ratio at EPC Profit (%)	Discount Ratio at Consumer’s Bill (%)
			Contribution Ration (%)	Grant/Interest Ratio (%)
1	0	0	100	100 Grant	60	13.78
2	0	0	100	50 Grant	42.09	9.66
3	0	0	100	0 Grant	24.17	5.55
4	0	0	100	(−10) Interest	20.59	4.72
5	20	60	40	0	22.56	8.88
6	25	25	50	50	33.13	7.60
7	100	0	0	0	40.29	0
8	70	30	0	0	30.62	3.33
9	0	100	0	0	8.05	11.1

. The profit rate of the EPCs is kept at 20% higher than the profit rate of the consumers. This is because, even if the consumers do not have any economic gain, the continuous energy comfort they will obtain thanks to the RESS application is accepted as a separate gain. The highest profit rate for the EPC and the consumer is seen when they receive full support in the form of a grant from the external sponsor for the RESS cost. Even if the grant rate is reduced to 50%, higher profit rates are obtained compared to the other scenarios. The external sponsor can be government support or a financial institution.

The government grant can be 100% or a partial grant. In the fourth scenario of Table 7, it is assumed that a financial institution that covers the RESS cost receives back the capital it invested with 20% interest. In scenarios 7, 8 and 9, different options produced by the EPC and the consumer to cover the RESS cost with their own means and the profit rates they obtain for these options are shown (Table 7).

If government subsidies are implemented in the form of regulation of energy prices for consumers using RESS, this can be considered as a more sustainable and important form of support, because changes in energy prices and battery prices over time can affect the applicability of RESS and may adversely affect its applicability.

5.3.3. Part 4

The number of consumers using RESS, the total power of RESS, and the rate of RESS application affecting the peak period and night period consumption are discussed in this part.

In the simulation, the average consumption power of consumers in residential areas is assumed to be 2.4 kW. The energy capacity of an RESS that can provide this power during a 5-h peak period is also found as 13.32 kWh in part 3. However, since the rate of RESS affecting the total power (GW) in peak and night periods and the rate of affecting the total load (GW) of power lines are also discussed in this part, the average power value (kW) is used, instead of the amount of energy stored by an RESS. Instead of converting the power of RESSs from kW to GW, this value is entered as one in a million when the number of RESS users is entered into the simulation, so the result is again found in GW.

The number of residential consumers using the RESS system and the total power obtained depending on this number (in GW) are given in Figure 4. In addition, how much the consumption power in the daytime period decreases and how much the nighttime period power increases thanks to the RESS connected to the energy system are calculated in this part, both in quantity and in ratio (Figure 5).

5.3.4. Part 5

In this part, the reduction in the production power, the loading rate on the energy lines, and the savings obtained in energy investments are shown (Figure 6). The investment amount required to increase the capacity of the energy lines by 1 GW is accepted as USD 300M and the required time is accepted as 2 years. The investment required for a 1 GW increase in energy production is accepted as USD 500M and the time is accepted as one year. In this part, the effect of RESS on investments in the near future is analyzed.

6. Analysis of Simulation Results

Simulation results are presented in

Table 8. First group scenarios.

Scenarios: Sc-1a, Sc-1b, Sc-1c, Sc-1d, Sc-1e Average peak period consumption/per consumer: 2.4 kW, number of residential area consumers: 130 M Increase rate in total consumption: 0%, number of RESS users is increased as follows: 0 M, 5 M, 10 M, 20 M, 40 M
Power Values (GW) and Ratios (%)	Sc-1a	Sc-1b	Sc-1c	Sc-1d	Sc-1e
Peak period energy consumption power for residential consumers	312.00	300.00	288.00	264.00	216.00
Amount of decrease in energy consumption power during peak period for residential consumers (%)	0.00	3.86	7.692	15.38	30.77
Night period energy consumption power for residential consumers (GW)	165.20	171.90	178.50	191.90	218.50
Amount of increase in energy consumption power during the night period for residential consumers (%)	0.00	4.04	8.07	16.14	32.28
loading rate on energy lines (%)	86.85	85.35	83.85	80.85	74.85
Total generation power required for peak period (GW)	715.60	703.30	690.90	666.20	616.8
Total generation power required for night period (GW)	170.20	177.00	183.90	197.60	225.10
Increase in power quantity (GW)	0.00	0.00	0.00	0.00	0.00
Investment needed for new transmission lines (USD M)	0.00	0.00	0.00	0.00	0.00
Time required for the construction of new transmission lines (Years)	0.00	0.00	0.00	0.00	0.00
Investment needed for new power plants (USD M)	0.00	0.00	0.00	0.00	0.00
Time required for the construction of new power plants (Years)	0.00	0.00	0.00	0.00	0.00
Total investment needed (USD M)	0.00	0.00	0.00	0.00	0.00

,

Table 9. Second group scenarios.

Scenarios: Sc-2a, Sc-2b, Sc-2c, Sc-2d, Sc-2e Average peak period consumption/per consumer: 2.4 kW, number of residential area consumers: 130 M Increase rate in total consumption: 0%, The increase rate in total consumption is increased as follows: 0%, 5% 10%, 15%, 20%
Power Values (GW) and Ratios (%)	Sc-2a	Sc-2b	Sc-2c	Sc-2d	Sc-2e
Peak period energy consumption power for residential consumers (GW)	312.00	327.60	343.20	358.80	374.40
Amount of decrease in energy consumption power during peak period for residential consumers (%)	0.00	0.00	0.00	0.00	0.00
Night period energy consumption power for residential consumers (GW)	165.20	165.20	165.20	165.20	165.20
Amount of increase in energy consumption power during the night period for residential consumers (%)	0.00	0.00	0.00	0.00	0.00
Loading rate on energy lines (%)	86.85	91.19	95.53	99.88	104.20
Total generation power required for peak period (GW)	715.60	751.4	787.2	823	858.8
Total generation power required for night period (GW)	170.20	170.20	170.20	170.20	170.20
Increase in power quantity (GW)	0.00	0.00	27.21	62.99	98.77
Investment needed for new transmission lines (USD B)	0.00	0.00	8.16	18.90	29.63
Needed per year for new transmission lines setting (Year)	0.00	0.00	5.44	12.60	19.75
Investment needed for new power plants (USD B)	0.00	0.00	13.60	31.50	49.39
Needed per year for new power plants setting (Year)	0.00	0.00	2.72	6.30	9.88
Total investment needed (USD B)	0.00	0.00	21.77	50.39	79.02

and

Table 10. Third group scenarios.

Scenarios: Sc-3a, Sc-3b, Sc-3c, Sc-3d, Sc-3e Average peak period consumtpion/per consumer: 2.4 kW, umber of residential area consumers: 130 M Increase rate in total consumption: 20%, number of RESS users is increased as follows: 0–5 M–10 M–20 M–40 M
Power Values (GW) and Ratios (%)	Sc-3a	Sc-3b	Sc-3c	Sc-3d	Sc-3e
Peak period energy consumption power for residential consumers (GW)	374.40	362.40	350.40	326.40	278.40
Amount of decrease in energy consumption power during peak period for residential consumers (%)	0.00	3.205	6.41	12.82	25.64
Night period energy consumption power for residential consumers (GW)	165.20	171.90	178.50	191.90	218.50
Amount of increase in energy consumption power during the night period for residential consumers (%)	0.00	4.04	8.07	16.14	32.28
Loading rate on energy lines (%)	104.20	102.70	101.20	98.22	92.22
Total generation power required for peak period (GW)	858.80	846.40	834.10	809.30	759.90
Total generation power required for night period (GW)	170.2	177.00	183.9	197.6	225.1
Increase in power quantity (GW)	98.77	86.41	74.05	49.33	0.00
Investment needed for new transmission lines (USD B)	29.63	25.92	22.22	14.80	0.00
Needed per year for new transmission lines setting (Year)	19.75	17.28	14.81	9.87	0.00
Investment needed for new power plants (USD B)	49.39	43.21	37.03	24.67	0.00
Needed per year for new power plants setting (Year)	9.88	6.64	7.41	4.93	0.00
Total investment needed (USD Billion)	79.02	69.13	59.24	39.47	0.00

according to three scenario groups. The changes made in each scenario group are explained at the top of the tables. Graphical representations of the results are presented in Figure 7 and Figure 8 for better comparison of the results obtained from the first, second and third group scenarios.

According to the first group of scenarios presented in Table 8, as the number of consumers using RESS in residential areas increases:

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The peak period consumption power decreases by 30.77%, while the night period consumption increases by 32.28%. In other words, approximately 30% of the peak period consumption power in residential areas is shifted from the peak period to the night period.

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This change causes the required energy production power in the peak period to gradually decrease from 715.6 GW to 616.8 MW.

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This situation causes a total decrease of 13.8% in energy production and 12% in the loading of power lines.

When the number of RESS users is increased without changing the total power value with the first group of scenarios, the peak period consumption, load on the power lines and the energy production need decreases, and the night period consumption increases, can be observed graphically in Figure 7. In these scenarios, the amount of need for new energy investments is not visible because there is no increase in total energy consumption yet.

According to the second group of scenarios, Table 9 presents how much the increase in peak-period consumption in residential areas in the coming years will likely raise energy production and the additional load that will occur on energy lines, according to the second group of scenarios.

The second group scenarios are prepared to show the advantages that the third group scenarios (Table 10) will provide. In the second group scenarios, it is seen how the new investment needs arising from new energy plants and new energy transmission lines can be reduced and accommodated, depending on the use of RESSs in the next scenario.

In the third group scenarios, the consumption power is increased by 20%.

Accordingly, it is seen that the 2025 energy production capacity determined as 800 GW is 98.77 GW more than normal and the existing energy lines are insufficient.

Assuming that the annual growth rate changes by 1–1.5 [94],

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It is estimated that the higher consumption amount of 20% mentioned in the simulation will be reached within 15–20 years.

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The time required for the construction of the energy transmission lines needed in the simulation is found to be 19.75 years.

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The budget required for the new energy transmission lines needed to handle the 98.77 GW consumption increase has been determined to be USD 29.63 billion.

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Similarly, it is seen that a period of 9.88 years and a budget of USD 49.39 B are needed for energy production plants. (These calculations ignore the value that money will lose value over the years due to inflation).

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In the third group of scenarios, the number of residential consumers using RESS is gradually increased to 5 M, 10 M, 20 M and 40 M, and it is seen that the need for new energy transmission lines and energy plants decreases at each stage, and accordingly, the costs to be spent decrease and the time required for installation also decreases. When it is assumed that 40 M residential area consumers use RESS, it is seen that a 20% increase in energy consumption can be absorbed.

The relationships between the second group of scenarios and the third group of scenarios in terms of needed new energy investments and needed time can be compared more easily with the graphical representation given in Figure 8. It is seen how the increase in the total consumption in the second group scenarios, the increase in the loading of power lines, the need for energy production, and the need for new energy investments can be reduced by increasing the number of RESS users in the third group of scenarios.

7. Conclusions, Discussions and Planned Studies

This paper argues that consumer-side energy storage can be made feasible and provide significant benefits if adopted on a large scale. The study investigates these benefits, supports the findings with scenario-based simulations, and derives actionable conclusions from the results.

The research, methodology, analyses, and conclusions are summarized as follows:

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Consumer-side energy storage offers significant advantages over production-side systems in terms of benefits.

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Organizing consumer-side energy storage through energy providers, rather than individual consumers, is more feasible and sustainable, as shown by scenario-based simulations.

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The study focuses on residential energy storage systems (RESS), emphasizing their role in consumer-side energy storage.

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Simulation scenarios consider energy prices, battery costs, and organizational strategies, including potential government grants or subsidies, and quantify economic benefits for EPCs and RESS users.

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Comparative analysis reveals that LiFePO4 batteries are more suitable for RESS applications than Li-Ion batteries, considering lifespan, affordability, safety, energy losses, environmental impacts, and recyclability.

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Widespread impact analysis estimates RESS adoption effects for 5 M, 10 M, 20 M, and 40 M consumers, highlighting impacts on energy production, transmission loads, and associated costs.

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Sensitivity analysis identifies energy and battery prices as key factors affecting RESS viability.

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More specific conclusions obtained by analyzing the simulation results are listed below.

7.1. Conclusions Derived from the Simulation Results

(a)

Independent implementation of RESS by consumers is economically challenging but becomes viable and beneficial when managed by EPCs. Simulation results show that RESS applications provide economic advantages for both EPCs and consumers, making the systems both feasible and sustainable.

(b)

Beyond economic benefits, stored energy enhances living standards by minimizing grievances caused by power outages due to natural disasters, equipment failures, or overloads. This also benefits EPCs by improving customer satisfaction and reducing compensation liabilities.

(c)

If 30% of residential consumers (approximately 40 M) adopt RESS, 96 GW of peak hour power demand can shift to nighttime. This increases the economic utilization of renewable energy sources, such as hydroelectric, wind, and geothermal power during off-peak hours.

(d)

Integrating photovoltaic (PV) panels into RESSs transforms them into solar PV systems. This advantage can position RESS as an important facilitator in the transition to renewable energy. If well planned, RESS systems can even support microgrid and smart home concepts.

(e)

The simulation results show that shifting 96 GW of power from peak to nighttime reduces peak period energy generation capacity needs by 13.8% on average, easing transmission line loads. These shifts defer investments in new energy plants and transmission lines, potentially postponing USD 30 M in transmission costs and USD 50 B in energy generation investments.

7.2. Discussion

There are several critical aspects of the consumption-side energy storage concept presented in this article that require further discussion and development. These considerations are outlined below:

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The fact that the period of the RESS contract between the EPC and the consumer is 10–12 years, depending on the life of the LiFeFO batteries and the average life of the inverters, is approximately the same creates an advantage for RESS systems. This synchronization offers a significant advantage for RESS systems, as it reduces the likelihood of component replacements during the contract period, thereby minimizing potential energy losses associated with component failure, replacement logistics, and distribution disruptions. Furthermore, the long-term feasibility and affordability of RESS could be further enhanced if a structured battery recycling process is established, allowing cost-effective, recycled batteries to be used in subsequent contract cycles.

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While the widespread adoption of RESS has the potential to significantly reduce carbon emissions and land use for energy generation, it also raises concerns regarding resource extraction, battery disposal, and the environmental impact of large-scale battery implementation. However, LiFePO4 batteries, that are known for their extended lifespan, low environmental impact, and superior recyclability compared to other battery chemistries, help mitigate many of these challenges.

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In countries with centralized energy management systems, RESS implementation can be relatively straightforward and rapid. Production and assembly could be tendered to selected energy companies, while various models of state grants and incentives could be employed to accelerate widespread adoption.

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However, this level of simplicity cannot be assumed for the United States, due to its highly diverse energy management structures. Significant variations exist among grid regions concerning infrastructure, energy pricing models, and organizational frameworks. For example, while some regions are dominated by vertically integrated utilities, others operate under deregulated markets, municipal utilities, or cooperative models. Transmission line loading capacities also vary, influencing how and where future energy investments are prioritized. These structural differences, including whether certain projects have already been planned or tendered, can influence both the feasibility and the perception of RESS implementation. Therefore, a more realistic assessment of RESS applicability in the U.S. would require a detailed examination of grid regions, the collection of up-to-date data from energy authorities, and the simulation of these data to evaluate the impact of RESS in various energy contexts.

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The adoption of consumption-side energy storage technologies like RESS is expected to follow a gradual implementation timeline, likely spanning 10–15 years. This extended period is necessary to allow for supporting research, pilot projects, and case studies that can validate the benefits, technical feasibility, and economic viability of these systems. Additionally, the production and deployment stages must be carefully planned, with regulatory bodies recognizing the strategic importance of RESS and making the necessary legal adjustments to facilitate its integration. Given RESS’s potential to support smart grids, microgrids, smart buildings, electric vehicles, and the broader transition to renewable energy, establishing clear, long-term objectives from the outset will be critical for ensuring its successful adoption.

7.3. Planned Studies

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In this article, in order to maintain the integrity of the subject, the superiority of consumption-side energy storage over production-side energy storage has been emphasized, the applicability of energy-side energy storage has been attempted to be proven, and the dimensions of the economic gains that can be obtained when widespread effects occur have been attempted to be shown. Therefore, not all the details have been sufficiently covered in the article. It is planned to address these details in future studies.

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Initially, the aim is to conduct a more detailed analysis of possible organizational scenarios for consumer-side energy storage and their economic dimensions. Although an RESS can be built with a smart inverter and a battery bank, it is necessary to develop a prototype system that can perform the same functions at a lower cost. An RESS device primarily consists of LiFePO4 batteries, an inverter/charger, switching systems, cooling fans, necessary measurement components, displays, and essential metal parts. If the goal is to enable RESS to be converted into a solar PV or microgrid system when needed, the inverter must be selected accordingly. This factor directly impacts the cost of the RESS. Considering all these aspects, it is intended to approach this subject as a laboratory study and subsequently as a research paper.

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The economic analyses presented in this paper do not account for the depreciation of money over time due to inflation. Moreover, it is planned to explore in a separate study how the time required to achieve widespread adoption of RESS might affect the overall impact and the substantial savings that may be achieved from deferred investments.

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A separate investigation is needed to analyze how RESS applications should be implemented in different grid regions. There are significant differences between U.S. grid regions in terms of energy management, the types of energy companies, and the characteristics of their transmission systems. Consequently, the extent to which each grid region is affected by overloads can vary. These factors also influence the amount of savings achieved from deferred investments. Hence, it is planned to address these details through a separate simulation study.

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The availability of inexpensive nighttime energy is a crucial criterion for consumer-side energy storage. When widespread adoption of RESS is achieved, a significant increase in nighttime energy consumption is expected. The batteries of rapidly growing electric vehicle fleets are also typically charged during nighttime periods, benefiting from lower energy costs. Therefore, it is planned to analyze the impact of electric vehicles during the widespread adoption phase of RESS.

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In addition to the short-term research goals outlined above, it is planned to investigate the long-term contributions of the consumer-side energy storage concept to smart grid developments. For instance, one of the smart grid goals is to benefit from the energy stored by electric vehicles during times when peak consumption increases very suddenly [95,96,97]. An RESS designed in accordance with the microgrid system and capable of transferring the energy in electric vehicles to the grid when necessary could provide significant support to the smart grid system in this regard.