Faraz Farhidi

doi:10.19080/ACJPP.2024.01.555574

Review Article

Utility Scale Energy Storage as a Service in Nevada

Faraz Farhidi*

NV Energy, Las Vegas, NV, USA

Submission: August 02, 2024; Published: August 16, 2024

*Corresponding author: NV Energy, Las Vegas, NV, USA

How to cite this article: Faraz F. Utility Scale Energy Storage as a Service in Nevada. Acad J Politics and Public Admin. 2024; 1(5): 555574. DOI:10.19080/ACJPP.2024.01.555574.

Abstract

A utility company based in Nevada is currently advancing a pioneering shared battery storage solution tailored explicitly for solar energy consumers. This innovative service integrates advanced bill minimization algorithms, a dynamic time-of-use tariff structure, a sophisticated home automation interface, and incentives aimed at intermittently providing crucial support to the electric grid. Through this initiative, consumers have the option to lease storage capacity from a utility-managed battery resource, as opposed to procuring individual energy storage systems. Noteworthy is the unparalleled affordability of this service compared to the conventional approach of acquiring dedicated home batteries. Complemented by potential savings from time-of-use billing and additional compensation for grid support, the utility is exploring a lowest-cost guarantee wherein customers would only incur expenses equivalent to the lesser of their current service arrangement or the newly bundled service on an annual basis.

In addition to its cost-effectiveness, this service offers a sense of assurance. By obviating the necessity for individual home batteries, consumers are relieved of concerns pertaining to fire risks or equipment malfunctions within their premises. The utility assumes the responsibility for managing and optimizing the integration between solar generation and storage through advanced automation software, thereby ensuring homeowners derive enduring benefits from a seamlessly administered energy storage solution. Ultimately, the utility size battery would cost (purchasing, installation, and managing) 30% less compared to the residential battery, and also provide a safer environment for customers, while decrease the outage probability by providing grid services and enhance grid reliability.

Keywords: Cost-benefit analysis; Energy arbitrage; Energy storage as a service; Peak load management; Utility size battery

Abbreviations: PV: Photovoltaic; ESaaS: Energy Storage as-a-Service; GSS: Grid Services Set; BTM: Behind-The-Meter; BESS: Battery Energy Storage System; KW: Kilowatt; NPV: Net Present Value; PLM: Peak Load Management; EA: Energy Arbitrage; VESB: Virtual Energy Storage Block

Introduction

With the increased residential adoption of photovoltaic (PV) energy, consumers are facing the question of how to store excess solar energy and use it when needed. With the growing interest in storing solar power, energy companies have become decentralized and increasingly reliant on consumers and battery suppliers. To take an active role in managing their energy production and consumption, many consumers choose to purchase and own their own batteries. Owning in-house batteries provides a concrete solution for storing excess solar energy. The in-house batteries thus allow consumers to benefit from a self-managed solution and not rely on a centralized grid for their backup power source. The local residential energy companies now have the potential to create a new financial incentive program called energy storage as-a-service (ESaaS). ESaaS asks consumers to rent batteries from a centralized facility, while the utility manages the batteries for consumers as a backup power source. Using this managed solution, consumers will be sharing the grid with other consumers and actively benefit from a utility-managed solution.

The concept involves the installation of a battery that would be connected to a local distribution system, in this case a utility substation as shown in Figure 1 below.

ESaaS projects are currently not as widespread as shared renewable resources since their potential revenue streams are still not fully understood. Howland [1] reported that large size battery storage placement is relatively easy to justify in areas where customers have high demand charges or try to maximize the self-consumption of rooftop photovoltaics as a result of drop in net metering rates, such as Hawaii and parts of Texas. Apart from the above cases, ESaaS will require multiple revenues to make financial sense.

An ESaaS has the potential to provide a cost-effective energy storage solution for customers with PV who will be able to store excess solar PV energy which they can then access later to offset their energy import [2]. In parallel, the ESaaS can also use the excess storage (not utilized by the participating customers) to provide grid services and potentially trade in the wholesale energy market, thus providing additional value [3-9]. By stacking multiple use cases and revenue sources, the business model for an ESaaS offers a) cost reductions through economies of scale compared to BTM batteries, b) capacity optimization through diversity of customers’ energy usage patterns, c) opportunity to generate value from multiple revenue streams, leading to a more economical solution, and d) maximum benefits at all times through continuous optimization of the battery dispatching [10].

ESaaS is a new product offering to be developed for NV Energy customers that uses a substation battery (≈1MW/4MWh) to lease blocks of storage capacity to customers with PV (as illustrated in Figure 1) to enable them to store excess solar energy for later use to offset their energy import or manage demand charges. In parallel, the ESaaS will also be used by NV Energy to support the Grid Services Set (GSS).

Major software components that have been developed to represents the operations and state of the virtual energy storage blocks; and cloud layer service to aggregate ESaaS information into battery controller command set for subscribed portion of battery. There is a virtual meter service to track virtual exported and imported energy flows related to the ESaaS product in order to facilitate creation of the customer’s billing determinants for their electricity bill; besides, there is a customer facing software tool to assist with recommending ESaaS virtual energy storage block size (Figure 2).

ESaaS Economic Analysis

BTM-ES Cost

Conducting a primary analysis of the behind-the-meter (BTM) energy storage solutions in Nevada, revealed that Tesla Powerwall and LG Chem jointly command an impressive 90% share of the state’s energy storage market. This dominance underscores the substantial market presence and widespread adoption of these two products within Nevada’s dynamic energy landscape. The Tesla Powerwall and LG Chem emerge as the premier choices for behind-the-meter energy storage, signifying their prominence and influential role in addressing the region’s energy storage requirements. Consequently, for individuals contemplating the purchase or financing of a BTM energy storage system from the market, the associated monthly fee is estimated to range between $38 and $48 per equivalent kilowatt as illustrated in Tables 1 and 2 below which provide valuable insights.

Substation Battery (ESaaS) Cost

The confirmed cost of a 1MW/4MWh substation battery at Beltway totals $3.6 million before factoring in the federal tax incentive. To conduct a meaningful comparison between the Beltway Battery Energy Storage System (BESS) and other notable behind-the-meter energy storage (BTM-ES) solutions in the market, it is crucial to standardize the charging/discharging rate across all three systems, expressed in dollars per kilowatt (kW). Following this normalization process, the analysis reveals that the monthly fee required to reach the breakeven point for the substation battery is $26.2. This figure stands significantly lower-by less than 30%-than the cost associated with the most economical BTM-ES available in the market. Such a compelling outcome underscores the cost-effectiveness and competitive advantage of the Beltway BESS, firmly positioning it as a financially attractive option within the energy storage landscape (Tables 3).

ESaaS Services and Revenue

The optimization of ESaaS revenue hinges on the strategic implementation of value stacking, a method that consolidates all potential revenue streams associated with ESaaS. This approach ensures that the asset is deployed in a manner that prioritizes the most lucrative revenue sources, thereby maximizing returns across a spectrum of services. The integration of rooftop PV customers, distribution services, and network grid services contributes significantly to enhancing the Net Present Value (NPV) of a substation Battery Energy Storage (BESS) in a considerably shorter timeframe. Rooftop PV customers stand to benefit by subscribing to ESaaS blocks, enabling them to store excess PV generation during daylight hours. This stored energy can then be discharged during nighttime, augmenting self-consumption. Additionally, the ability to shift morning PV energy to later afternoon hours proves advantageous in avoiding peak retail pricing periods. Distribution grid services leverage the aggregated excess capacity of subscribed storage blocks, along with the non-allocated capacity of the ESaaS. This utilization occurs particularly during network constraints, such as preventing substation transformer overload - a function known as peak load management (PLM) service.

Network grid services, on the other hand, harness both subscribed and unsubscribed capacities of ESaaS to offer energy arbitrage (EA) services. Participation in the CAISO Energy Imbalance Market (EIM) facilitates effective energy trading. Furthermore, this asset can concurrently engage in frequency regulation (FR) services, optimizing revenue potential when higher returns are anticipated. The strategic alignment of these services underscores the versatility and profitability of ESaaS, positioning it as a dynamic solution for diverse energy needs.

The following benefits were identified to calculate the potential revenue generates by subscribing to the utility size energy storage instead of the BTM-ES:

a) Energy Arbitrage Value: Calculated based on storing energy when prices are low and discharging it when prices are high, thereby capitalizing on price differentials.

b) Avoided Costs Value: Represents the savings obtained by using stored energy during peak periods, avoiding higher-priced electricity from the grid.

c) Avoided Transmission Losses: Reduction in energy loss during transmission by using stored energy locally instead of transmitting it over long distances.

d) Enhanced Grid Reliability: Considers the value associated with improved grid stability resulting from stored energy availability.

e) Environmental Impact: Quantifies positive environmental effects, such as reduced reliance on non-renewable energy sources or lower emissions, attributable to the energy storage system.

Customer ESaaS Cost-Benefit Analysis

The Energy Storage Calculator is a tool designed to analyze the potential benefits of implementing an energy storage system based on various input parameters. This report aims to provide an overview of the calculator’s functionality, the parameters involved, and the significance of the calculated results.

How to calculate breakeven points

E: Export to the ESaaS (or to the grid);

η: Roundabout efficiency (or loss due to charge and discharge, equivalent to the residential batteries if customers decide to purchase); η<1

SB: Subscribed Block

PE: Premise’s electricity uses which is divided to PE_off and PE_on, distinguishing off-peak and on-peak use.

PB: Premise’s bill

R_on: on-peak rate, R_off: off-peak rate

Defining cost-benefit parameters and equations

The calculator considers the following parameters:

i. PV Size: Represents the size of the photovoltaic system in kW.

ii. System Efficiency: Indicates the efficiency of the system, given as a percentage.

iii. Average Daily Use (Excluding Summer Season): Specifies the average daily energy consumption in kWh.

iv. Current Rate (TOU: Assuming TOU rate is more customized already for customers who are mindful in using energy): There are three rates: Off season (0.08 per kWh), off peak on season (0.09 per kWh), on peak on season (0.34 per kWh).

Cost-Benefit Equations:

The calculator utilizes specific equations to determine cost and revenue:

• Cost: Calculated as 12 times the monthly fee multiplied by the battery size.

• There are six potential benefits identified to the energy storage:

• Avoided Costs: Charge when the price is low (off peak) and discharge when the price is high (on peak).

• On peak season (June-September): 122*(on peak price – off peak price) *battery size

Given:

Summer On-Peak Price: $0.34609/kWh

Summer Off-Peak Price: $0.05156/kWh

Battery Size: 1 kWh

Avoided Costs calculation:

Avoided Costs=122 × (0.34609−0.05156)×1

Avoided Costs=122×0.29453

Avoided Costs=$35.95

• The BESS round-trip efficiency is assumed to be 90% in this calculator, which can alternate depending on any the battery efficiency.

• Avoided cost proportional with BES capacity up to a certain point (which depends on the PV system size and load demand). After that point, the avoided cost for each additional kWh will drop.

The round-trip efficiency adjustment has been implemented by multiplying the relevant calculations by 0.9 in the code. This adjustment acknowledges a more realistic efficiency assumption for the Battery Energy Storage (BESS). The adjusted avoided cost calculation now considers a proportional relationship up to a specified point. Beyond this point, a reduction factor is introduced to simulate the diminishing returns associated with increased BESS capacity. This adjustment aligns with the observation that avoided costs may vary with BESS capacity up to a certain limit.

• Energy arbitrage: taking advantage of the price fluctuation in the market, one can purchase energy when the price is low (sometimes even negative) and sell it when its high demanded.

• Off peak (8 months, September-May): 243* (Max-ave market price1 – Min-ave market price1) * battery size

TOP 35TH percentile of energy prices from 2020- 2023

109.2398809mwh

=109.2398809/1000(convert to kwh)

0.10923988

LOW 35TH percentile of energy prices from 2020-2023

13.01625768mwh

13.01625768/1000(convert to kwh)

= 0.01301625768

Given:

Top 35th percentile converted to kWh: 0.10923988 kWh

Low 35th percentile converted to kWh: 0.01301625768 kWh

Battery size: 1 kWh

Time frame: 243 days

The formula to calculate energy arbitrage based on the price fluctuation between these percentiles.

would be:

=243 * (0.10923988 - 0.01301625768) * 1

=$23.37478645 kWh

• The above assumes the ESaaS or BTM BESS charges and discharged on a daily basis. Consider cases where the price fluctuation remains minimal for several days or even weeks. Thus, i included a parameter to increase price flexibility of the calculator. This parameter was introduced to consider price fluctuations over a specified time interval (e.g., a week), allowing for scenarios where price variations remain minimal for several days or weeks.

• Additionally, considerations were made for scenarios where net-metering is abolished under a bundled tariff, resulting in zero credits for solar energy export. The calculator includes a variable, which, when set to True, adjusts the avoided cost calculations for both Photovoltaic (PV) and BESS. This adjustment aligns with the potential need for maximizing self-consumption by storing excess PV power during the day and utilizing it at night, thereby saving the customer about $12.00 per kilowatt-hour (kWh) of BESS capacity. These modifications enhance the code’s adaptability to diverse scenarios.

• Avoided transmission losses= ($0.00784 per kWh): When using utility battery, we can avoid energy losses in transmission (from generation to substations).

• Year around: 365*avoided transmission cost*battery size.

• Distributed generation (such rooftop PV) reduces transmission loading. Although a BESS is not a source of power generation, it can also partially reduce transmission losses by flattening the load curve during peak demand. The above $ value may need adjustment to split the reward between PV and BESS.

• TOU tariff already rewards the customer by providing very low electricity rates during off peak times.

• To address the consideration of distributed generation (e.g., rooftop PV) reducing transmission loading and the potential role of Battery Energy Storage (BESS) in partially reducing transmission losses, the calculator now incorporates a variable for adjusting the reward distribution between PV and BES. While BES is not a direct power generation source, its ability to flatten the load curve during peak demand contributes to reducing transmission losses. The introduced variable allows for a more nuanced assessment of the economic value attributed to both PV and BESS in this context.

• Reviving potential revenue loss (opportunity cost): Customers, depending on the tranche they are, will use 9%-25% of the potential revenue due to exporting to the grid based on the net-metering agreement. The opportunity cost is important to calculate the economic profit (not for the accounting profit).

• Calculating opportunity cost (net-metering revenue loss): 243 * 0.25 * current rate price * (4 * PV size * system efficiency - average daily use) * battery size.

If net-metering is not applicable under the bundled tariff, the revenue loss will be at 100%. In this case, Energy arbitrage and avoiding loss of revenue from excess PV power will be conflicting. In scenarios where net-metering is not applicable under the bundled tariff, the system faces a decision between energy arbitrage and avoiding the loss of revenue from excess PV power. When prices for grid electricity fluctuates energy arbitrage becomes crucial. The calculator prioritizes energy arbitrage if there is a substantial risk of revenue loss from excess PV power export to the grid. If net metering is abolished 100%, BESS directly utilizing excess PV power during peak demand times to maximize self-consumption. In this scenario, the code considers avoiding the loss of revenue from excess PV power when the risk of revenue loss is minimal. Thus, the decision depends on the balance between the potential revenue loss from excess PV power and the benefits of energy arbitrage. If the risk of revenue loss is significant, the system prioritizes energy arbitrage. Otherwise, it focuses on maximizing self-consumption to avoid any conflicting goals.

• Enhance grid reliability: Since the renewable resources such as solar and wind have lower reliability compared to nuclear energy or fossil fuel-based power plant, pairing them with energy storage will enhance the energy production and distribution reliability, and avoiding outages, so such benefit should be valued and included in the benefit calculation.

• Using SAIDI/SAIFI indices: 365*Monetary value per kWh*battery size.

• A BESS will enhance grid reliability if it is used to assist with ramping, and smoothing the power supply to reduce peak demand, fluctuations in voltage and frequency (i.e., regulation).

• The integration of renewable resources like solar and wind with energy storage, as implemented in the code under “Enhance grid reliability,” plays a crucial role in improving energy production and distribution reliability. This combination addresses the intermittent nature of renewables, contributing to grid stability and outage prevention. The utilization of System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in the code, under “Using SAIDI/SAIFI indices,” quantifies the economic impact of the Battery Energy Storage (BESS) on enhancing grid reliability. Additionally, a BESS optimized for customer bill minimization, as depicted in the code, indirectly enhances grid reliability by actively participating in load shifting, voltage regulation, and providing stability during changes in power demand. These features contribute positively to grid reliability, reinforcing the BESS’s dual role in minimizing customer bills and bolstering the overall stability of the electrical grid.

• Environmental impact: There is potential to reduce greenhouse gases, thus the environmental benefit should be valued and added to the calculations.

• Assigning monetary value to GHG reduction: Grid Electricity offset*Round-Trip Efficiency*(Emission Intensity*(gas-based power plant CO₂ production per kWh (half kg) - Battery generation of CO₂ production per kWh):0.2kg.

• Since producing energy using solar energy and producing battery contribute to the GHG, so we should include them considering the life cycle.

• Grid Electricity offset: 365 * (Average daily household consumption - Average daily solar generation).

• Round-Trip Efficiency: 92-95%.

• CO₂ equivalent contribution:

• Gas-based power plant: 0.5kg of CO₂ /kwh

• Battery: 0.2kg of CO₂ /kwh.

• Calculation for Monetary Value of GHG Reduction

• Average daily household consumption: 30 kWh

• Average daily solar generation: 1.8 kWh

• Round-Trip Efficiency: 92% (0.92)

• Emission Intensity of Grid Electricity: 0.5 kg CO₂/kWh

• Emission Intensity of Battery: 0.2 kg CO₂/kWh

• Value per ton of CO₂ reduced: $8

• Calculation Steps:

• Grid Electricity Offset Calculation:

• Grid Electricity offset = 365 * (Average daily household consumption - Average daily solar generation)

• Grid Electricity offset = 365 * (30 kWh - 1.8 kWh)

• Grid Electricity offset = 365 * 28.2 kWh

• GHG Reduction Calculation:

GHG reduction = Grid Electricity offset * Round-Trip Efficiency * (Emission Intensity of Grid Electricity - Emission Intensity of Battery)

• GHG reduction = 365 * 28.2 kWh * 0.92 * (0.5 kgCO₂/ kWh - 0.2 kgCO₂/kWh)

• GHG reduction ≈ 3018.78 kgCO₂

• Monetary Value Calculation:

• Monetary value = (GHG reduction in tons) * (Value per ton of CO₂ reduced)

• GHG reduction in tons ≈ 3018.78 kgCO₂ / 1000 tons

• Monetary value ≈ $24.15 (with $8 per ton of CO₂ reduced)

• Environmental saving in a glance: With a value of $8(EIA rounded up value) per ton of CO₂ reduced, the approximate monetary value of reducing approximately 3018.78 kgCO₂ is around $24.15. Adjust this value based on the specific rate applicable in your context.

It is important to emphasize that the utility company, as simulated in this calculator, does not engage in Greenhouse Gas (GHG) trading. Rather, the calculation presented herein signifies the environmental advantages derived from the utilization of Battery Energy Storage Systems (BESS). This benefit is elucidated as a non-monetary value, specifically categorized within the subset of environmental-societal values. By not participating in GHG trading, the focus remains on the inherent ecological benefits of incorporating BESS, highlighting its positive impact beyond monetary considerations and underscoring its contribution to broader environmental and societal values.

• Revenue (Benefit):

• If 4 times the PV size times system efficiency exceeds the average daily use:

• 243 * 0.25 * current rate price * (4 * PV size * system efficiency - average daily use) * battery size + 122 * (Max-ave market price – Min-ave market price) * battery size.

• Otherwise:

• 365 * (Max-ave market price2 - Min-ave market price2) * battery size.

• Objective Function:

• The primary objective is to maximize profit, calculated as revenue minus cost.

• Calculations and Conditions

The calculator employs the following conditions and calculations:

• Parameters and Variables:

• Current rate: TOU rate ($0.09).

• Market price variations: Max-ave and Min-ave market prices for different scenarios.

• Conditions:

• Monthly fee based on BESS calculation cost ranges from $10 to $51.

• Battery size ranges from 0 to 1.5 times the PV size.

• Profit Analysis:

• Iterative computation of profit within a reasonable.

Contextual Factors and Interpretation

The report also incorporates contextual information related to grid reliability and interruptions in Nevada.

• Grid Reliability:

• SAIDI (System Average Interruption Duration Index): 195.1 minutes per year.

• SAIFI (System Average Interruption Frequency Index): 0.984 times per year.

• CAIDI (Customer Average Interruption Duration Index): 198.2 minutes per interruption.

• Calculation of Grid Reliability:

• Cost per interruption = (SAIDI * Percent of Customers Reported) / 60

• Calculation: (195.1 * 1.026) / 60 ≈ 3.34

• Monetary Value of 1 kWh

• Monetary value of 1 kWh = Cost per interruption / SAIDI

• Calculation: 3.34 / 195.1 ≈ $0.0171 per kWh

• Calculation of the monetary value of 1 kWh: $0.0171 per kWh.

The Energy Storage Calculator provides a comprehensive analysis of potential profitability based on input parameters, considering various pricing scenarios and grid reliability factors. It serves as a valuable tool for assessing the financial viability of implementing energy storage solutions.

Customer Subscription Fee

ESaaS Rider: Price and capacity calculations

A software calculator will be developed and provided online to customers. The calculator will determine the “optimal” virtual energy storage block (VESB) for a customer. This depends on customer specific yearly load profile, customer PV system size, and the resulting benefits a specific VESB can provide by PV energy shifting under a particular utility rate schedule.

Below are the subscription plans based on the calculated cost. Prices are fixed over the contract periods, and after that they are subject to change according to the inflation:

i. $26.2 per kW per month for 10-year plan (this plan is set to be equivalent to financing battery from other vendors).

ii. $26.2 per kW per month for annual plan (the price is fixed only for the first year).

iii. $32.75 per kW per month for quarterly plan.

iv. $36.03 per kW for a monthly plan.

Under this project, the utility rate schedule that will be applied to customers who will enroll in ESaaS will be a modified version of the Time of use rate. The new version shifts the on-peak period from 1:00 pm - 7:00pm to 3:00pm - 9:00pm to better line up with the network peak period. In addition, critical peak pricing scheme (an added to the time of use rate) will be limited to 14 events that last only 3 hours instead of 6 hours, but at a higher price. Additionally, the ESaaS calculation will need to be revised to consider extra savings associated with a reduction in daily demand charges and benefits through participation in revenue-generating grid services.

Additional revenue can be generated by allowing the utility to utilize the excess capacity of the subscribed block for revenue-generating grid services, such as energy arbitrage. Herein, profit sharing among the utility and the ESaaS subscribers will be determined through some mathematical formulation in proportion with the excess capacity of each participant which is explained in the Grid Rider, separately. A financial settlement will be followed monthly. But such activity is limited during the summer months as the VBES blocks are largely used for off-peak to on-peak solar energy shifting.

Summary of Findings

The Energy Storage Calculator provides a comprehensive analysis of potential profitability based on input parameters, considering various pricing scenarios and grid reliability factors. It serves as a valuable tool for assessing the financial viability of implementing energy storage solutions. Upon user input of parameters including PV size, efficiency, and average daily energy use, the tool computes the optimal monthly fee and battery size that maximize the system’s profit. The results are displayed dynamically in the graphical interface, showcasing the optimal configuration and the expected yearly profit. This energy storage system analysis tool offers a versatile means to estimate the most profitable configurations based on user-provided data and a range of benefit factors. It enables informed decision-making for deploying energy storage systems by considering multiple revenue streams and cost factors.

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