Virtual Net-Metering Option for Bangladesh: An Opportunity for Another Solar Boom like Solar Home System Program

Abstract

This study explores the virtual net-metering (VNM) option for enabling inclusive investment opportunities in renewable energy for self-consumption in Bangladesh. It focuses on consumers, such as households and businesses in multi-family and multi-story buildings, who cannot participate in traditional net-metering policy due to technical and space constraints. The study adopted the classical socket parity method to identify suitable consumers for VNM. Then it determined the consumer benefits of using VNM by calculating the net present cost (NPC) and discounted payback period. The results reveal that several consumer categories can significantly save on electricity costs through VNM. For example, commercial consumers can save more than 50% of their electricity bills by investing in a VNM-enabled remote solar power plant with a discounted payback period of fewer than six years. The discussion articulates more comprehensive benefits of VNM. It addresses challenges for renewable energy development by identifying local opportunities. Therefore, this research can help initiate policy dialogues and create momentum for citizen investments in the energy transition. The proposed approach can also be used to analyze the economic feasibility and potential of VNM in other countries.

1. Introduction

Research Background

Energy transition in South Asian countries is considered to be critical due to the high dependency on fossil fuels in the region [1]. However, the good news is that among South Asian countries, Bangladesh aims to follow an ambitious roadmap for solar PV installation, despite its high population density (>1100 people per km²). The most optimistic scenario for this roadmap indicates an installed capacity of 30 GWp of solar photovoltaic (PV) systems by 2041 [2]. To achieve this target, the government must overcome several challenges, such as a lack of investment and land availability issues, to implement this sustainable energy transition roadmap [3,4]. Therefore, there is a need to escalate these issues through research and investigate innovative solution options.

Currently, Bangladesh relies on native natural gas and imported liquid and solid fuels, such as crude oil, hard coal and other oil products, for electricity generation (see Figure 1) [5]. According to the current proven reserves, native natural gas is only expected to power the country for another decade, accounting for the growing energy demand [6]. To cope with this situation, Bangladesh announced a power system master plan in 2016 that articulates the import and use of local renewable energy sources until 2041. However, as of February 2022, the total installed capacity of renewable energy systems was 780 MW, comprising 70% solar PV and 29% hydro power [7]. Bangladesh needs an average annual pace of 950 MW more solar PV capacity to reach the 30 GWp destination, while the current install capacity totals only 546 MW. The country is experiencing several challenges in attracting investors for PV system development, such as the unavailability of suitable land and high investment risks [2,3,8].

Furthermore, based on recent power purchase agreements, PPA, Bangladesh has not yet achieved grid parity for solar PV electricity due to high investment costs and subsidies in the power sector [10,11,12,13]. As a result, the government has to buy electricity from private-sector-developed solar PV plants at higher prices to achieve RE targets. To encourage rooftop installation, Bangladesh introduced a net-metering (NEM) policy in 2018. The policy brought about 1500 systems, equivalent to 36 MWp, into the grid as of February 2022 [7]. Due to power system stability issues, the NEM policy allows only 3-phase consumers to install rooftop PV systems [14]. Therefore, the policy only encourages those with roof space and a 3-phase connection to install PV systems. On that account, NEM policy fails to ensure inclusiveness for investment, as it only allows a narrow band of the consumer spectrum [15].

Thus, it is necessary to explore additional policy and system types that can help overcome space availability constraints and attract investors, especially citizens. In this context, the author argues that the current NEM policy needs an upgrade to attract a wide range of citizens to RE investment. Hence, this research investigates virtual net-metering (VNM) as an option to promote citizen investment and deal with space constraints. The study aims to (1) identify opportunities that can facilitate the implementation of VNM to overcome the barriers to renewable energy development, (2) investigate the economic feasibility of VNM, and (3) discuss its implications. Technical and environmental aspects are out of the scope of this study. These aspects are discussed as the outlook of the research.

2. Virtual Net-Metering (VNM)

VNM, as illustrated in Figure 2, is a concept that allows remote energy generation and virtual consumption via the grid to receive credits in electricity bills. Hence, it is also known as remote net-metering. Unlike traditional net-metering, which is a system installed behind-the-meter (BTM), VNM is characterized as a front-of-the-meter (FTM) system. Hence, it involves distribution system operators (DSO), and in some cases, transmission system operators (TSO) [16]. On that account, VNM users are obliged to pay additional charges for transporting energy via the grid, such as distribution and transmission costs—wheeling costs.

Countries such as the United States, Australia, Jamaica, and Brazil have adopted the VNM concept with various terms and conditions and modifications [17,18]. In [19], the authors also characterized VNM as a geographical compensation scheme and net-metering in groups. According to the authors of [18], there are two main ideas behind the different topologies of VNM: (1) generator and consumer are the same entity, also known as one-to-one, and (2) there may be multiple consumers sharing a generator, also known as one-to-many.

Langham et al. in [20] characterized VNM into four typologies: single entity, third-party, community group VNM and retail aggregation for Australia, as shown in

Table 1. Typologies of VNM, description, and potential users. Adapted from [20].

Type of VNM	Description	Potential User
Single entity (one-to-one)	An entity offsets the electricity of site B from the excess production from site A	Organizations with multiple meters
Third-party (One-to-many)	An entity sells exported electricity generation to separate entity(s)	Any generator (solar farm or landlord) or consumer
Community group VNM (One-to-many)	People of a community invest in a power plant and transfer the power to the investors/owners via the grid.	People of a community, residents of multi-family housing, commercial community
Retail aggregation (Many-to-many)	Multiple entities sell exported generation to a retailer for resale to multiple consumers.	Local generators with exportable electricity Retailers, including community retailers

. A USAID study recommended similar categories for VNM adoption in India [18]. Considering technological and regulatory complexities, the authors of [19] suggest that VNM concepts should not be adopted before implementing traditional net-metering. The authors of [20] identified the wheeling charge as one of the most critical issues for implementing VNM. Countries use various wheeling charge determination methods around the globe, such as cost recovery, historical cost, forward-looking, and nodal pricing methodologies [21]. The most common practice for wheeling charge calculation is the cost recovery and the postage and stamp methods. These methods consider historical investment, operation and maintenance costs, and system losses to identify total revenue requirements for the utility. Then it calculates per unit wheeling cost (e.g., $/kWh) by using the total energy supplied by a utility [22]. The downside of this method is that it does not consider wheeling distances and power; therefore, it raises the issue of fairness [21,22,23].

Business models of VNM also vary according to the types of VNM, as described below:

• Single-entity VNM follows a straightforward business model where a single investor develops a larger solar power plant at any site to meet energy demands for other sites. The generator site uses electricity at the rate of LCOE, and other sites pay wheeling costs. This model is also known as multi-site meter aggregation. Examples of such VNM can be found in [20,24].
• Third-party VNM follows the typical producer–retailer business model. An entity develops and operates a power plant to produce energy and sells the energy to one or multiple consumers. In Germany, this model is known as tenant electricity, where the tenants can purchase cheaper power from the landlord [25,26]. In the case of solar farms, the model is comparable with the synthetic or virtual power purchase agreement (vPPA) between a producer and consumers. The price of energy is agreed between two parties for a certain period of time. In addition to power price, consumers pay network charges for transferring the power.
• Community VNM allows a group of consumers to form a community to invest in a shared power plant to meet their energy demand, as shown in Figure 2 [24,27]. The business model for the community VNM can be complicated, as different types of consumers can form a community to produce and consume. Since electricity tariffs differ for different consumer categories, a community power plant will not generate the same benefits for everyone. SOM Energia in Spain and the Clean Energy Collective in the USA are examples of shared generation for roofless consumers [24].
• The retail aggregation VNM model uses the concept of a common platform business concept, such as the Uber and Airbnb model. In the case of energy, the aggregator virtually collects excess power from various generators and sells it to consumers [28]. Consumers receive a reduced energy price compared to the grid electricity tariff. Solshare Ltd., a private company, has implemented this concept by inter-connecting and aggregating solar home systems in Bangladesh [29]. However, unlike other European companies, such as Sonnen in Germany, Solshare builds its own distribution networks.

In [24], the authors reviewed several policies and business models for different types of prosumer aggregation policies and business models, especially in Europe and the United States. However, the study includes no examples from developing countries. The literature on VNM or similar concept is also rare for the South Asian region and developing countries. Scholarly articles, such as [29] and [30], introduce emerging concepts, such as prosumer aggregation in Bangladesh and India. However, those articles rarely consider the inclusiveness issue and do not focus on articulating challenges and opportunities in those countries.

In the literature, VNM’s economic feasibility predominantly focuses on parameters such as Net Present Value (NPV) and payback periods [30,31,32]. The author argues that the retail grid parity or socket parity and net present costs (NPC) [33] method would be more suitable for analyzing the economic feasibility of VNM. These methods are rarely used for conducting a country-level feasibility study for VNM. The background for using the NPC method is that spending on electricity is an essential cost or expenditure for each consumer. For example, paying electricity bills to the utility, or investing in a renewable energy power plant to offset electricity bills, is an expenditure or cost for the consumers. The socket parity method on the other hand can identify the potential consumer categories in a country based on individual retail tariff rates.

Although all four models of VNM may be suitable for Bangladesh, this study adopts the community group VNM option and the cost recovery method for energy wheeling for further elaboration to limit the scope. The community VNM also addresses the inclusiveness of RE investment. Furthermore, this study considers rooftop PV (RPV) and ground-mounted PV (GPV) for remote generations. The term remote solar power plant (RSPP) addresses remote generation stations in this study.

3. Rationale for VNM and This Research in Bangladesh

There are several opportunities in Bangladesh to facilitate the implementation of VNM. At the same time, VNM can address several challenges in the country. The following sections articulate both.

3.1. Opportunities for Implementing VNM

Smart metering has a significant role in facilitating the implementation of emerging energy system concepts such as VNM, especially for meter aggregation [30,31]. Bangladesh is already well ahead in this step by distributing smart prepaid energy meters (SPEM) for electricity billing. Until 2021, the country has distributed 4 million SPEM and aims to distribute 8 million more by 2022 [9,34]. Bangladesh showed relatively high success in deploying smart energy meters compared to European countries, such as Germany [35]. Therefore, the country can leverage the benefit of SPEM for implementing VNM. Similarly, the country can use its simple tariff mechanism for implementing VNM. For example, as shown in Figure 3, the cost of energy and grid charges dominate more than 90% of the tariff composition in Bangladesh, whereas in Germany, the share of energy and grid costs is about half of the tariff. This tariff structure of Bangladesh makes it suitable for VNM implementation. This energy-dominant tariff structure facilitates achieving retail grid or socket parity for consumer-owned renewable energy systems without competing with the non-energy components of the tariff.

3.2. Challenges to Overcome through Implementing VNM

Through VNM, Bangladesh can address several challenges for increasing renewable energy share in the grid and sector coupling, such as:

• VNM could provide an inclusive opportunity to invest in PV systems for those who do not have roof space. At the same time, as energy can be generated in three phases and consumed with a single-phase connection through VNM, it can also address the 3-phase policy barrier for installing PV systems. As a result, residents in multi-family buildings and commercial and small industries in multi-storied establishments can install or own PV systems despite space and single-phase connection limitations.
• VNM could promote transportation electrification in Bangladesh. The country hosts more than a million electric 3-wheelers, which consume a significant amount of energy from the grid [38]. According to the distribution operators, there are more than 10,000 registered 3-wheeler charging stations around the country [39,40,41]. These charging stations are primarily located in urban or semi-urban areas where space availability is insufficient for developing solar systems to meet the electric vehicle charging energy demands. VNM could enable the charging station owners to invest in PV systems to offer green electricity for electric three-wheelers. At the same time, it can promote the adoption of electric vehicles among VNM users.

Based on the above, the author argues that VNM may bridge the challenges and take advantage of the opportunities to play a vital role in the energy transition in Bangladesh. Therefore, this research scrutinizes the economic feasibility and potential of VNM in the country, considering all the consumer categories. To the best of the author’s knowledge, no scientific studies on this topic outline the potential and benefits of VNM or similar concepts in the country, and studies like this are rare in South Asia. On that account, this study is necessary (1) to open a new research avenue and (2) to initiate a policy-level dialogue in Bangladesh on emerging system concepts for creating a participatory renewable energy investment environment and tackling these challenges.

4. Materials and Methods

Figure 4 shows the methodological overview for analyzing economic feasibility and benefits of VNM. Two models, socket parity and VNM, were developed for a systematic economic feasibility analysis. The socket parity model was used as a traffic signal for applying the VNM model. The following subsections describe each model.

4.1. Socket Parity Model

Socket parity is a graphical situation when the cost of renewable energy generation equals the cost of energy actually paid by the users as energy bills [42]. Unlike grid parity, socket parity considers grid fees, value-added tax (VAT), and other charges. In this study, the socket parity model aims to identify whether the electricity from VNM would be cheaper than grid electricity for consumers. It considers grid electricity tariffs, investment, and energy wheeling costs. However, the model omits demand charges from the calculation. Since in traditional net-metering users have to pay demand charges, it assumes that the policy for VNM would be the same. The model determines the cost of VNM energy by calculating the levelized cost of electricity (LCOE) of fictitious remote solar power plants (RSPP) and wheeling costs.

LCOE of RSPP: Equation (1) calculates the LCOE for two types of fictitious remote solar power plants (RSPP) in Bangladesh. The equation is inspired by the National Renewable Energy Laboratory’s (NREL) LCOE calculator, which can be found in [43]. The equation includes degradation of a PV plant and follow-up investment for equipment replacement. This study assumes the community group VNM approach, as mentioned in Table 1. It assumes medium-sized (1 MWp ≥ capacity ≥ 3 MWp) PV systems, such as large rooftop PV systems (RPV) and ground-mounted PV systems (GPV). The discount rate was considered according to the value suggested in [44]. The model uses energy yield (kWh/kWp) data from [45] for each type of RSPP as first-year energy yield.

Table 2. Input parameters for RSPP LCOE calculations.

Parameter	Value		Unit	Comment/Source
RSPP Type	Rooftop PV	Ground-mounted PV
Investment cost, I	50,000	65,000	BDT/kWp	Values were collected from local project developers via email
In USD	~588	~765	USD/kWp	1 USD (2022) = 85 BDT
Follow-up investment, FI	25%		Of investment	SREDA
O&M Cost, M	1%		Of Investment	Values were collected from project developers via email
Energy Yield, EY	1373	1418	kWh/kWp	[45]
RSPP Capacity	1000		kWp
Discount rate, R	6.4%		Per year	[44]
Project Life	25		Year
Plant degradation (PDR)	0.7%		Per year	[46]
Depreciation	Linear, 4%		Per year
O&M Cost Escalation (OCER)	2.5%		Per year	Values were collected from local project developers via email

shows the other values used in the equation.

$$LCO{E}_{RSPP}=\frac{I+\frac{F{I}_t}{{(1+R)}^t}+{{\displaystyle \sum }}_{\mathrm{t}=1}^n\frac{O\&M\times {(1+O\&M_{ER})}^{\mathrm{t}} }{{(1+R)}^{\mathrm{t}}}}{{{\displaystyle \sum }}_{t=1}^n\frac{EY\times {(1-PDR)}^t }{{(1+R)}^t}}$$

(1)

where LCOE_RSPP is the calculated LCOE of each type of RSPP. I stands for initial investment,, and FI denotes follow-up investment, such as inverter replacement at the 12th year. O&M represents operation and maintenance costs and insurance for the current asset, and O&M_ER represents the escalation factor. EY is the energy yield, and PDR accounts for the plant degradation factor. t represents the calculation year and n the RSPP lifetime. R is the discount rate.

Wheeling cost: Bangladesh follows the cost recovery (or postage and stamp) model for calculating wheeling charge and distribution costs for transmission and distribution of electricity [36]. The model uses the historical costs and energy transactions of the operators. Equations (2) and (3) represent the equations for the cost recovery in Bangladesh.

$$D_{Wc}=\frac{Nt{D}_C+C_{Systm loss}}{E_T}$$

(2)

where D_WC stands for distribution wheeling charge; NtT_C is the net total CAPEX and OPEX of the transmission network for a financial year, also known as required revenue. C_{System loss} represents the cost of system loss, and E_T is the total delivered to the distributor in the same year.

$$T{D}_{Wc}=\frac{NtT{D}_C+C_{Systm loss}+{\mathrm{W}}_{C-Grid} }{E_D}$$

(3)

where TD_WC stands for distribution wheeling charge and W_C-Grid is the wheeling cost paid by the distribution operators.

Table 3. Parameters for utility-wise distribution and transmission wheeling cost estimation. Data source: [36]. Data year: 2020. MBDT = Million Bangladeshi Taka.

Utility	Net Distribution Cost (NtDc)	System Loss	Total Distributable Energy (ET)	Wheeling Cost (WC-Grid)	Puchase Cost per unit	Cost of Lost Energy (C)
	MBDT	%	MkWh	MBDT	BDT/kWh	MBDT
BPDB	11,495	7.08%	12,515	3742	6.17	5887
BREB	51,210	10.65%	35,819	11,057	4.60	19,644
DPDC	8448	7.15%	9669	3014	6.69	4982
DESCO	4728	6.94%	5749	1871	6.75	2897
WZPDC	3707	8.59%	3618	1147	5.67	1926
NESCO	4085	10.26%	3980	1272	5.34	2430
Bangladesh Total	83,673	8.45%	71,350	22,103	5.41	38,922

shows the values used in the equation.

Wheeling scenario: Energy wheeling can have two scenarios depending on the consumption and the RSPP feed-in points.

Table 4. Wheeling scenarios based on consumption and RSPP feed-in points.

Notation	Wheeling Scenario	Definition
DWc	Wheeling through a distribution network.	When the point of generation (RSPP) and consumption are under the same distribution network
TDWc	Wheeling through both a transmission and a distribution networks	When the RSPP feeds to the transmission grid and energy is consumed through a distribution grid

shows these two cases.

Socket cost of VNM electricity: Equation (4) calculates the VNM energy cost at the users’ socket for both wheeling scenarios.

$$SCO{E}_{VNM}=\left\{\begin{array}{c} LCO{E}_{RSPP}+D_{WC } ; for D_{Wc} energy whelling\\ LCO{E}_{RSPP}+T{D}_{WC} ; for T{D}_{Wc} energy wheeling\end{array}\right.$$

(4)

Here, SCOE_VNM refers to the cost of VNM energy.

Socket cost of grid electricity: The socket cost of grid electricity SCOE_Grid considers the consumer tariff (T_Consumer) and value-added tax (VAT). Utilities in Bangladesh charge 5% VAT on top of consumer tariffs during billing. The retail electricity tariff rates in Bangladesh can be found in [47].

$$SCO{E}_{Grid}=T_{Consumer}+VAT$$

(5)

Socket parity: Equation (8) represents the method for identifying socket parity considering wheeling scenarios.

$$\mathrm{Socket} Parity=\left\{\begin{array}{c}SCO{E}_{VNM D_{WC}} \le CO{E}_{Grid} for Dwc energy whelling\\ SCO{E}_{VNM T{D}_{WC}} \le CO{E}_{Grid} for TDwc energy wheeling\end{array}\right.$$

(6)

$$Consumer Surplus/Deficit=\frac{SCO{E}_{Grid}-SCO{E}_{VNM}}{SCO{E}_{Grid}}$$

(7)

VNM suitability: Equation (7) calculates consumer surplus or deficit by comparing the grid and VNM energy costs. The author sets a suitability threshold of 20%, meaning consumer surplus must be more than 20% to consider a consumer category suitable for VNM. The value was selected by considering the latest settled tariff rate for rooftop systems (OPEX model) between the system operator and energy consumer in Bangladesh [48]. In Germany, this value is 10% for the tenant electricity scheme known as Mietersrtom [25].

4.2. VNM Model

The VNM model calculates the economic benefit of VNM compared to grid electricity. It is applied to some selected consumer categories that satisfy socket parity conditions. The VNM model consists of the following steps and equations.

RSPP capacity sharing for VNM users: According to the net-metering guideline of Bangladesh, the ceiling of PV system size in AC is 70% of the sanctioned load (kW) to the consumers. However, sanctioned load varies widely among consumers and tariff classes. Therefore, the author calculated the RSPP capacity share using the average energy consumption per consumer in each tariff class. Equation (8) uses 100% of the annual energy consumption to determine the required capacity share of RSPP for the VNM schemes.

$$C{S}_{RSPP-kWp}=\frac{AE{C}_{consumer}}{AE{Y}_{RSPP}}$$

(8)

where CS_RSPP-kWp is the required capacity share, and AEC_consumer is the annual energy consumption for a consumer category. AEY_RSPP is the energy yield at the respective RSPP.

Net present costs (NPCs): The model calculates NPC_Grid for grid electricity usage and NPC_VNM for VNM electricity. It identifies the least-cost option for the consumers by comparing both the NPCs. It also calculates the NPC for RSPP to provide an overview of investment expenditure. Equations (9)–(11) describe the details.

NPC for grid electricity

$$NP{C}_{Grid}=-{\displaystyle {\displaystyle \sum }_{t=1}^n}\frac{{(CO{E}_{Grid})}_t}{{\left(1+R\right)}^t}$$

(9)

where NPC_Grid is the cost of grid electricity for the period of RSPP lifetime. COE_R-Grid is the cost of grid electricity considering consumer demand growth and electricity price escalation factor in year t, and R represents the discount factor. n stands for the lifetime of the RSPP.

NPC for RSPP

$$NP{C}_{RSPP}=-I_{0_{RSPP}}-{\displaystyle {\displaystyle \sum }_{t=1}^n}\frac{{(O\&M_{RSPP})}_t}{{\left(1+R\right)}^t}$$

(10)

where NPC_RSPP is the lifetime cost of the RSPP, I_{0_RSPP} is the initial investment cost-share CS_RSPP-kWp, and O&M_RSPP is the annual share of O&M costs, including insurance premium for RSPP.

NPC for VNM

$$NP{C}_{VNM}=-I_{0_{VNM}}-{{\displaystyle \sum }}_{t=1}^n\frac{{(O\&M_{RSPP}+W_c+SCO{E}_{Residual})}_t}{{\left(1+R\right)}^t}$$

(11)

where NPC_VNM is the lifetime cost of using the VNM scheme and W_c accounts for the cost of energy wheeling. Additionally, SCOE_Residual was determined by Equation (12):

$$SCO{E}_{Residual }=\left\{\begin{array}{c}{E}_{Deficit }\times SCO{E}_{Grid}\times VAT, if AE{D}_{consumer}>SG{E}_{RSPP-kWp} \\ -E_{RSPP-Excess}\times CO{E}_{Feed-in} , if AE{D}_{consumer}<SG{E}_{RSPP-kWp} \\ O, otherwise\end{array}\right.$$

(12)

where COE_Residual is the cost or revenue for deficit and excess energy from the grid or RSPP, respectively. Since the required capacity is based on 100% of the consumption, the expected revenue is zero.

The NPC calculation also considers the consumer tariff escalation factor of 1.8% per year, which was annualized from previous tariff growth rate data from the Bangladesh Energy Regulatory Commission (BERC) [36]. Furthermore, the consumer energy demand growth rate was set to a negligible value (0.1%), as consumption per consumer growth rate was found insignificant from the data of Dhaka Electricity Supply Company (DESCO) [39].

VNM user benefit: Equation (13) calculates the consumer category’s economic benefit by using VNM. It compares the NPC of VNM electricity with the NPC of the grid. The equation determines the total cost savings potential by using VNM during the lifetime of RSPP. It considers the absolute values of the NPCs.

$$\mathrm{Savings}, \% \mathrm{of} \mathrm{grid}=\frac{NP{C}_{Grid}-NP{C}_{VNM}}{NP{C}_{Grid}}\times 100$$

(13)

Discounted payback period (DPBT): Equation (14) calculates the payback period of RSPP based on savings from the VNM scheme by considering the time value of money.

$$DPB{T}_{VNM-RSPP}=\frac{Cost of Investment }{Discounted annual cost saving}$$

(14)

where DPBT_VNM-RSPP stands for the discounted payback period of RSPP.

4.3. Scenario and Sensitivity

• Scenarios: Two scenarios for energy wheeling were considered for each RSPP type, as shown in

  Table 5. Scenarios for sensitivity analysis.

  Scenario	Definition
  RPVRSPP + DWc	Large Rooftop and Ground-mounted PV systems located within the distribution network of consumers
  GPVRSPP + DWc
  RPVRSPP + TDWc	Large Rooftop and Ground-mounted PV systems are located outside the distribution network of consumers, and they require the transmission network for energy wheeling
  GPVRSPP + TDWc

  .

• Sensitivity: Investment cost and wheeling charge were varied to analyze the sensitivity on user benefit, as shown in

  Table 6. Base values and ranges of the variables for the sensitivity analysis.

  Parameter	Application	Base Value [Unit]	Sensitivity	Output Parameter
  Investment cost	RPVRSPP	50,000 [BDT/kWp]	± 20%	VNM user benefit [%]
  	GPVRSPP	65,000 [BDT/kWp]
  Wheeling cost	DWc	1.55 [BDT/kWh]	Minimum and maximum wheeling charges by utilities
  	TDWc	1.86 [BDT/kWh]

  .

4.4. Data Collection

Data used in this study were gathered from the latest annual reports and monthly operational data available on the websites of all the utilities in Bangladesh.

Table 7. Collected data, applications of data and sources.

Data	Application of Data	Source
Transmission and distribution operators’ costs.	Wheeling costs	[36]
Bangladesh electricity tariff	Socket parity and grid electricity cost	[36]
Tariff-wise Energy consumption Tariff-wise no. of Consumers	Required capacity share of RSPP and user benefit calculation	[12,39,40,41]

shows the sources and application of the data in this study.

Energy consumption per consumer: This study used tariff-wise energy consumption data from [39,40,41] to determine consumption per consumer in each tariff class using Equation (15). Energy consumption data for the financial year 2020/21 were used as annual energy consumption.

$$AE{C}_{Consumer}=\frac{Annual Energy Consumption in each tariff class }{Total number of consumer in the tariff class}$$

(15)

5. Results

5.1. Cost of VNM Energy and Socket Parity

The socket parity model was used to calculate the cost of VNM electricity by determining the LCOEs of RSPPs and two energy wheeling cost scenarios, as shown in Figure 5A. The LCOE calculator calculated LCOEs for RPV and GPV, 3.78 and 4.75 BDT/kWh, respectively. It identified that the LCOE of ground-mounted PV systems is higher than that of rooftop PV systems. This is the opposite case compared to other countries, such as India. In Bangladesh, private lands are expensive due to the high population density. This results in higher investment cost for GPV systems.

The wheeling costs in Figure 5A are the calculated average values among all the six DSOs in Bangladesh for both wheeling scenarios. The average wheeling costs were found 1.55 and 1.86 BDT/kWh for DWc and TDWc scenarios, respectively (see

Table 8. Utility-wise distribution and transmission wheeling costs in Bangladesh (with and without system losses).

Utility	Net Dc without System Loss	Net Dc, Including System Loss	Net Dc and Tc without System Losses	Net Dc and Tc, Including System Losses
BPDB	0.92	1.39	1.22	1.69
BREB	1.43	1.98	1.74	2.29
DPDC	0.87	1.39	1.19	1.70
DESCO	0.82	1.33	1.15	1.65
WZPDC	1.02	1.56	1.34	1.87
NESCO	1.03	1.64	1.35	1.96
Mean	1.02	1.55	1.33	1.86

). The cost of system loss was embedded with wheeling cost by considering the monetary value of system loss (energy) according to the bulk price of electricity for the utilities. Therefore, wheeling energy loss was omitted while calculating VNM electricity costs. Table 8 shows the estimated wheeling costs for all the utilities in Bangladesh.

Considering flat tariff rates in Bangladesh, the socket parity model evaluates 25 tariff classes among different consumer categories. Since low-voltage residential consumers pay their electricity bills according to block tariff, five categories of households were considered considering five levels of average monthly energy consumption. These categories can be seen in Figure 6.

Figure 5B presents the results of socket parity. It shows the number of consumer categories that achieve socket parity in four scenarios. According to the current tariff, 22 consumer categories meet socket parity for both wheeling scenarios with RPV-based RSPP. Of those 22 consumer categories, 90% are suitable for VNM considering the 20%-suitability threshold. Similarly, for GPV-based RSPP, the suitable numbers of consumer categories were found to be 19 with DWc and 16 with TDWc wheeling scenarios.

Figure 6 summarizes the results of the socket parity model for all consumer categories in Bangladesh. It shows consumer surpluses and deficits while using VNM. According to the figure, the estimated socket cost of VNM electricity is significantly lower than the grid electricity socket cost for several consumers, making VNM suitable for them. The figure also shows the consumers who are not suitable for VNM, such as agricultural consumers, social institutions, and low-energy consuming residential households. In Bangladesh, electricity for agricultural purposes and low-energy consuming households is highly subsidized. On the other hand, despite the high consumer surplus for VNM electricity, a number of consumer categories may not be suitable for VNM due to their consumer definitions and energy use cases—for example, the temporary connection consumer categories. At the same time, it can be assumed that the medium and high-voltage industry consumers have sufficient space to build their own PV systems under traditional NEM policy. In that case, VNM policy can allow industry consumers to transport over-production from PV systems to their commercial entities in other locations. For example, the garment and textile industries can produce energy in their industrial park (site A) and transport excess electricity to their commercial offices (site B) using the single-entity VNM model, as shown in Table 1.

Since many consumer categories were found suitable for VNM, the author narrowed the scope for applying the VNM model to specific consumer categories, as discussed in Section 3.2. Those categories are residential, commercial, industry, and charging station consumers.

5.2. Economic Benefit of Using VNM

The VNM model estimates the potential economic benefit of using VNM for different consumer categories.

Table 9. Saving and discounted payback period overview for all scenarios.

Parameters	Residential (600 kWh/mo)	Residential (800 kWh/mo)	Residential (1000 kWh/mo)	Commercial	Small Industry	Battery Charging Station
Scenario: RPV-DWc
Savings, BDT	271,525	514,384	746,854	609,880	1948,642	1710,575
Saving, % of Grid	34%	42%	45%	52%	44%	38%
Discounted Payback, yr	10	8	7	6	7	9
Scenario: RPV-TDWc
Savings, BDT	240,858	473,493	695,741	578,910	1806,377	1550,450
Saving, % of Grid	30%	38%	42%	49%	40%	34%
Discounted Payback, yr	11	8	7	6	8	9
Scenario: GPV-DWc
Savings, BDT	190,630	406,523	612,028	528,187	1573,375	1288,198
Saving, % of Grid	24%	33%	37%	45%	35%	29%
Discounted Payback, yr	14	11	9	7	10	12
Scenario: GPV-TDWc
Savings, BDT	159,962	365,632	560,915	497,217	1431,111	1128,073
Saving, % of Grid	20%	30%	34%	42%	32%	25%
Discounted Payback, yr	15	11	10	8	10	13

presents the cost-saving potential in four different scenarios of VNM for the selected consumers. According to the table and Figure 7, commercial consumers can save more than 50% of their electricity costs with a payback period of 6 years under the DWc scenario. Under the same scenario, the minimum savings and maximum discounted payback periods were found for residential consumers that consume 600 kWh per month. The lower benefit comes from their lower electricity tariff rates. RPV with the TDWc wheeling scenario reduces the savings by about 3% and increases the payback period by 1–2 years for different consumer categories. At the same time, GPV-based RSPP offers 8–10% lower savings and 2–4 years higher payback periods for similar wheeling scenarios. The author identified that higher consumer tariffs positively influence the savings and discounted payback periods in all the scenarios.

Figure 8 shows an example of annual cost savings during the lifetime of the RSPP for charging station consumers. According to the figure, if charging station owners share a GPV-based RSPP located nearby or within the same distribution network, they can save nearly 30% of their electricity costs through VNM. The aggregated savings offer a return on investment (ROI) of more than three-fold.

Table 10. Average annual consumption, consumer-wise RSPP capacity shares and estimated costs. The annual O&M cost includes an annual insurance premium for RSPP.

Consumer Information			RPV			GPV
Consumer Category	Annual Consumption, kWh	Tariff BDT/kWh	Required RSPP Capacity Share, kWp	One Time Capital Share, BDT	Annual O&M Share, BDT	Required RSPP Capacity Share, kWp	One Time Capital Share, BDT	Annual O&M Share, BDT
LT_Residential (600 kWh/mo)	7200	7.1	5.24	262,200	2622	5.08	330,042	3300
LT_Residential (800 kWh/mo)	9600	8.2	6.99	349,599	3496	6.77	440,056	4401
LT_Residential (1000 kWh/mo)	12,000	8.8	8.74	436,999	4370	8.46	550,071	5501
LT_Commercial	7271	10.3	5.30	264,785	2648	5.13	333,297	3333
LT_Small Industry	33,400	8.53	24.33	1,216,315	12,163	23.55	1,531,030	15,310
LT_Battery Charging Station	37,593	7.64	27.38	1,369,009	13,690	26.51	1,723,233	17,232

summarizes the investment and annual cost parameters for the selected consumer categories. The required capacity shares are different for RPV and GPV-RSPP, as the energy yields for rooftop systems are lower than those of ground-mounted systems.

5.3. Sensitivity Analysis

Since the investment cost of RSPP is volatile and wheeling costs vary based on utility, the model considers that investment and wheeling costs are the major variables for sensitivity. The sensitivity analysis was performed on both models: socket parity and VNM. The impacts of varied investment and wheeling costs on socket parity are shown in Figure 9. According to Figure 9A, 20% volatility of investment cost and the maximum and minimum wheeling costs do not significantly impact socket parity.

However, with the same parameters, the number of suitable consumer categories reduced significantly for GPV-based RSPP, as shown in Figure 9B. It can be seen that only the commercial consumer category remained suitable for the extreme case, which is a 20% higher investment cost and the maximum wheeling cost (2.29 BDT/kWh). Hence, the sensitivity analysis concludes that commercial consumers are highly suitable for VNM in Bangladesh. According to Figure 10A, there are nearly 3 million commercial consumers in the country, which indicates significant market potential for VNM. However, consumers in charging stations, residential, and small industry categories may require incentives and support to adopt VNM in the event of higher investment and wheeling costs.

Figure 11 shows the impacts of investment and wheeling costs on the savings of VNM users. The figure shows that a 20% reduction in investment cost for GPV-based RSPP can make VNM more attractive for charging stations and high-energy-consuming residential consumer categories, encouraging them to invest in RE. Since the wheeling costs are different for different utilities, as shown in Table 8, the savings will also vary based on utility. However, it is essential to pay attention to the wheeling costs, as they negatively affect the benefits of VNM. For example, wheeling through BREB is the most expensive, whereas DESCO offers the cheapest costs in the country. BREB has the lowest per kilometer consumer density in its distribution network of all the DSOs in Bangladesh—about 60 consumers/km. In addition, BREB operates through 80 sub-operators known as Pally Bidyut Samity (PBS) in Bangladesh [40]. Therefore, to offer VNM with BREB, a single PBS wheeling cost consideration would be more appropriate and fair. Furthermore, charging station consumers may require reduced wheeling costs as an incentive to adopt VNM.

The study also identified several other economic factors sensitive to the benefits of VNM. Those are discount factors, consumer energy demand growth, grid electricity and wheeling cost escalation factors, RSPP performance ratio, and operation and maintenance costs of RSPP. Among those factors, only the grid electricity tariff escalation rate positively correlates with the VNM savings, whereas others have negative correlations. For example, if the discount rate reduces by 1%, the VNM saving increases by 2%.

6. Discussion

6.1. Potential of VNM for Other Developing Countries

The energy cost component dominates the tariff composition in Bangladesh. At the same time, electricity tariffs are higher for commercial and high-energy-consuming residential consumers. These situations make VNM economically feasible in the country. A similar electricity tariffing methodology is used for other south Asian countries, such as Pakistan, Nepal, and India [49]. Figure 12 shows the countries in South Asia where the commercial tariff is higher than the average residential tariff. It compares socket parity with the global average LCOEs of PV. The figure also includes the 5th percentile of the PV LCOE, which IRENA found in India in 2020 [50]. According to the figure, business consumers in this region can significantly offset their electricity bills by installing solar PV with a net-metering policy. The surplus also shows the potential for VNM in those countries. Hence, the market potential for VNM in this region could be significant, and this study can stimulate researchers and policymakers to explore it further.

6.2. Promotion of Electric Vehicles through VNM

VNM could facilitate the adoption of electric vehicles by different consumer categories in developing countries to cope with the increasing fuel prices. According to the results, the VNM offers higher benefits for the consumer categories that pay higher tariffs. Therefore, consumer categories such as high-energy-consuming residential, commercial, and small industries, can increase their benefits by replacing fossil fuel vehicles with electric vehicles (or considering EV for the new/next vehicles). For example, a weekly mileage of 150 km with an electric passenger car in Bangladesh can increase electricity demand by around 137 kWh per month, given 18 kWh/100 km [52] with 85% charging efficiency electric cars, and 7.2 L/100 [53] km for petrol at 86 BDT/liter for conventional cars. Commercial consumers could save up to 32% on energy costs compared to grid electricity to meet this demand by using VNM. Furthermore, countries such as India, Nepal, Thailand, Vietnam, and Bangladesh have a high penetration of electric three-wheelers, and the number is soaring [38]. VNM can help those countries deal with the growing energy demand and offer green rides through electric vehicles.

6.3. Dealing with Land Availability Issues for Solar PV Systems

Due to the high population density in Bangladesh, space availability is critical for deploying utility-scale ground-mounted PV systems [54,55]. This situation does not encourage commercial or third-party investors to invest in large utility-scale power plants. In addition, land ownership is another critical issue in Bangladesh, implying smaller holding sizes. More than 80% of farm holdings in Bangladesh are less than 2.5 acres [56]. Therefore, the author argues that a potential solution would be developing small-scale solar power plants (e.g., <1 MWp) of suitable system types, such as rooftop, floating, and Agri-PV systems. These plants can be operated with mechanisms like those of community power plants and VNM by nearby communities.

On the other hand, Dhaka has significant potential for rooftop PV systems. A satellite image-based solar potential mapping project [57] estimated that rooftop PV potential in Dhaka is nearly 7 GWp. However, despite such significant potential, only a handful of the roof area has been utilized for developing PV systems. According to the latest data in [58], the aggregated capacity of installed rooftop PV systems in the Dhaka region is 40 MWp. Out of this capacity, only 6 MWp was installed under the net-metering policy, and the mechanism for the other 33 MWp is unclear. Multi-family and multi-storied commercial buildings highly dominate the building footprint of Dhaka, 86% and 9%, respectively. Therefore, the traditional NEM is inadequate to attract building owners as investors. Considering this situation, VNM can enable tenants to invest in rooftop systems regardless of their lengths of stay in the buildings. Through VNM, tenants can virtually consume energy from the PV system on any other building. Thus, VNM can facilitate utilizing the roof spaces, reducing the requirement for land to develop PV systems, and attracting citizens to invest in RE for self-consumption.

6.4. VNM for Implementing Renewable Portfolio Standards (RPS) and Mandates

Renewable policy instruments such as renewable portfolio standards (RPS) and mandates can force different entities to achieve individual RE targets [59]. However, considering the space constraints and limitations of traditional NEM, imposing individual renewable energy targets is not practical in countries such as Bangladesh. Since VNM can open the doors for RE investment for all the consumers, governments will be able to impose stricter policies, such as RPS and mandates, on high-energy-consuming consumers. In the case of Bangladesh, these consumers can be banks and other financial institutions, high-energy-consuming households, electric rickshaw charging stations, shopping malls, telecom operators, and other industrial and commercial entities.

6.5. VNM to Increase Citizen Investment in RE

Due to high-risk ratings, Bangladesh can attract few foreign investors [60]. Furthermore, investment from the private sector and the government is insufficient to achieve the RE targets of Bangladesh [3]. Hence, the country needs to seek alternative investment opportunities. The proposed VNM model is suitable for encouraging citizens or consumers in RE investment. The increasing grid electricity cost may be a catalyst for bringing citizens to RE investment [61]. The solar home systems program (SHS) of Bangladesh is considered one of the most successful off-grid projects globally. Rural people were at the center of this success. The author argues that VNM can be an opportunity for Bangladesh to facilitate another solar boom like SHS program by engaging the consumers in RE investment. Similar to the SHS program, the government can offer financial and reduced wheeling cost incentives to enable some consumers, such as charging stations and small industries, to invest.

6.6. Recommended VNM Implementation Pathway

First, it is necessary to upgrade the traditional net-metering policy to adopt VNM. However, this will require coordinated facilitation from government entities, such as ministries, utilities, and financial institutions. In Bangladesh, the Bangladesh Power Development Board (BPDB) and the Sustainable and Renewable Energy Authority (SREDA) can play the leading roles in implementing VNM. For VNM implementation, Bangladesh can adopt its affordable housing scheme (e.g., Uttara Apartment Project [62]), implemented by the Capital Development Authority (RAJUK). In the case of VNM, BPDB and SREDA can play the role of RAJUK in developing solar power plants and selling their kWp shares to consumers. Additionally, solar PV system project developers can play the role of real estate developers in the country to develop solar power plants as saleable assets. A proposed model is shown in Figure A1 in Appendix A.

6.7. Limitations and Outlook

The author used the cost recovery method for calculating the wheeling cost for the VNM. This may not reflect the actual wheeling cost for VNM. Therefore, further research is necessary to identify the cost-reflective and fair energy wheeling cost using the advanced methods described in the Introduction. Furthermore, this study was based on energy consumption and electricity tariff data from different utilities. Hence, a field study is essential to understand the views of citizens and consumers toward RE investment, which could identify the market potential of VNM and suitable policies.

The proposed VNM concept may play a significant role in offsetting electricity generation from fossil fuels during the day, reducing carbon emissions. At the same time, utilities can save by reducing energy purchase and grid wheeling costs. These benefits for the government and utility were not studied.

The author leaves the geographic feasibility of RSPP for VNM and emission reduction potential as future research outlooks. Additionally, since the cost of energy generation during the non-solar time (nights and cloudy days) is expensive, higher penetration of VNM may raise fairness issues among consumers. On that account, further policy measures, such as virtual net-billing [63], can be explored.

7. Conclusions

This study introduced VNM as a new concept in Bangladesh for creating an inclusive investment opportunity in RE to offset electricity costs. It identified VNM as a timely and economically feasible option for the country. Based on the literature review and analysis, the findings of this study can be generalized as follows:

• − The crucial challenges for renewable energy development in highly populated developing countries are land/space scarcity and lack of investment.
• − There are several under-explored opportunities, such as energy cost-dominant electricity tariffs, availability of smart energy meters, and rising demand sectors (e.g., electric 3-wheelers), in developing countries for adopting emerging system concepts such as VNM.
• − There are a significant number of consumer categories for whom adopting VNM is suitable in Bangladesh and the region.
• − VNM is an economically feasible alternative to grid electricity for consumers such as commercial, industry, and high-energy-consuming households.
• − VNM is a potential pathway for involving consumers in renewable energy investment to address the lack of investment challenges.
• − VNM could foster the implementation of rooftop PV systems and address the land/space availability challenges.
• − VNM could help tackle growing energy demands for EVs, and it could be a catalyst for promoting EVs in developing countries.
• − The existing housing models could be used for implementing VNM and developing RSPPs.

This study also enriches the literature on emerging RE concepts in the South Asian region and developing nations. The scholarly contributions of this research are as follows:

• − The research customized the socket parity method for identifying suitable consumers for VNM and prosumer aggregation concepts.
• − The net present cost method was applied for analyzing comparable cost-saving benefits between grid and VNM electricity.
• − A combined model with socket parity and NPC was developed for determining the country-level economic feasibility of VNM prosumer aggregation concepts.

The economic feasibility identification approach developed in this research is novel, and all the equations increase the transparency of the calculation. Hence, other researchers can adopt this approach for analyzing the feasibility of similar emerging RE system concepts. In addition, the results can inform citizens regarding the advantages of VNM and investment opportunities in RE. The discussion can help policymakers see the broader benefits and perspectives of VNM for addressing several challenges on the way to the energy transition.