Quantifying Social Benefits of Virtual Power Plants (VPPs) in South Korea: Contingent Valuation Method

Abstract

This study is one of the first empirical attempts to quantify the social benefit of virtual power plants (VPPs) in South Korea using the contingent valuation method (CVM). As Korea pursues its ambitious carbon neutrality goal by 2050, VPPs have emerged as a critical technology for managing the intermittency of renewable energy sources and ensuring grid stability. Despite their recognized technical potential, the social and economic value of VPPs remains largely unexplored. Through a nationwide survey of 1105 households, we employed a double-bounded dichotomous choice spike model to estimate willingness to pay (WTP) for government-led VPP implementation. The analysis revealed two distinct dimensions influencing VPP valuation: electricity bill perceptions and electricity generation mix preferences. Results indicated that Korean households exhibited significant but heterogeneous WTP for VPP implementation, with unconditional mean annual WTP ranging from KRW 23,474 to KRW 26,545 per household. Notably, support for renewable energy transition showed stronger positive effects on WTP compared to nuclear expansion preferences, suggesting VPPs are primarily valued as renewable energy enablers. The substantial spike probability (32–34%) indicated that approximately one-third of the population has zero WTP, highlighting challenges in introducing novel energy technologies. Key determinants of positive WTP included perceived fairness of electricity pricing, support for market-based mechanisms, and preferences for transitioning from coal and nuclear to renewables. These findings provide critical policy insights for VPP deployment strategies, suggesting the need for phased implementation, targeted communication emphasizing renewable integration benefits, and coordination with broader electricity market reforms. The study contributes to energy transition economics literature by demonstrating how public preferences for emerging grid technologies are shaped by both economic considerations and environmental values.

1. Introduction

South Korea has set an ambitious target of achieving carbon neutrality by 2050, alongside an intermediate goal of reducing greenhouse gas emissions by 40% from 2018 levels by 2030 [1]. The realization of these challenging objectives necessitates a fundamental transformation of the energy sector, particularly in electricity generation and distribution [2]. Central to this transition is the rapid expansion of variable renewable energy (VRE) sources, such as solar and wind power, as outlined in the 10th Basic Plan for Electricity Supply and Demand [3]. However, the intermittent and distributed nature of VRE poses significant challenges to grid stability and reliability, creating an urgent need for innovative solutions to ensure efficient integration of these resources into the existing power system [4].

Virtual power plants (VPPs) have emerged as a promising technological solution to address these challenges. A VPP integrates geographically dispersed distributed energy resources (DERs) through ICT and advanced control technologies to operate as a single integrated entity [5]. By optimizing the operation of these distributed resources and enabling real-time coordination, VPPs can enhance grid flexibility, improve system stability, and facilitate the integration of higher shares of renewable energy.

Despite the recognized technical potential of VPPs, research has predominantly focused on technological development, optimization algorithms, and market participation strategies [6,7,8]. There exists a notable gap in understanding the social and economic value that VPPs generate for society as a whole. This gap is particularly pronounced in the South Korean context, where no empirical studies have attempted to quantify the social benefits of VPP implementation. Such valuation is crucial for informed policymaking, investment decisions, and public acceptance strategies.

The benefits provided by VPPs exhibit strong characteristics of public goods [9]. Enhanced grid stability, reduced blackout risks, environmental improvements through increased renewable energy integration, and contributions to climate change mitigation are non-rival and non-excludable in nature. Furthermore, VPPs likely possess significant non-use values, including the existence value, bequest value, and altruistic value [9]. These characteristics necessitate the use of non-market valuation techniques, as traditional market-based approaches fail to capture the full spectrum of VPP benefits.

The contingent valuation method (CVM) presents the most suitable approach for valuing VPP benefits. In energy economics, CVM is the methodology capable of measuring the total economic value (TEV), including non-use values [10]. Unlike revealed preference methods that rely on observable market behavior, CVM can capture both use and non-use values through carefully designed hypothetical scenarios [11]. This is particularly relevant for VPPs, which represent a novel technology not yet fully experienced by the general public in South Korea.

This study aims to fill the existing research gap by empirically estimating the social benefits of VPPs in South Korea using CVM. Specifically, the research objectives are three-fold: (1) to estimate the average household WTP for the establishment and operation of public-based VPP systems, (2) to identify key determinants of WTP, with particular focus on electricity bill perception and preferences for electricity generation mix, and (3) to aggregate individual WTP estimates to derive the total social benefits of VPP implementation at the national level. This study makes several significant contributions to the literature on energy transition economics and policy. First, while previous VPP research has predominantly focused on technological optimization and business models from the perspective of operators, this investigation quantifies the total social benefits of VPPs from a national perspective. This shift from operator-centric to society-centric valuation provides critical insights for public investment decisions and policy design. Second, by applying the CVM, we capture both use values, such as improved grid reliability, and non-use values, such as environmental benefits and energy security, offering a comprehensive measure of VPPs’ total economic value. Third, our methodological approach employing the double-bounded dichotomous choice spike model enables the identification and analysis of zero-WTP segments within the population, providing valuable insights into public resistance to novel energy technologies. Finally, by examining the relationship between generation mix preferences and VPP valuation, this research offers evidence-based guidance for positioning VPPs within Korea’s broader energy transition narrative.

2. State-of-the-Art Review

2.1. Concepts and Benefits of Virtual Power Plants

VPPs represent a paradigm shift in electricity system operation, moving from centralized generation to coordinated distributed resource management. According to the literature, a VPP is comprehensively defined as a system that integrates geographically distributed heterogeneous energy resources (DERs) using ICT and advanced control technologies to operate and control them as a single unified entity [5]. This virtual aggregation transforms small-scale, dispersed resources into a reliable and controllable power plant equivalent, capable of participating in electricity markets and providing various grid services.

The core components of a VPP system include three main elements [12]. First, distributed energy resources encompass small-scale generation facilities (solar, wind, small hydro, and CHP), battery energy storage systems (ESS), electric vehicles with V2G capability, and demand response resources, such as smart thermostats and controllable industrial loads. Second, ICT infrastructure comprises smart meters, sensors, bidirectional communication networks, and cloud-based platforms that enable real-time data exchange and control. Third, the central control system employs software for real-time monitoring, forecasting, optimization algorithms, and market bidding and settlement functions.

The operational mechanism of VPPs involves several interconnected processes, as documented in recent studies [7]. The VPP operator aggregates multiple contracted DERs into a virtual pool, monitors and controls each resource’s status and grid conditions in real-time through ICT systems, employs AI-based prediction models for short- and medium-term forecasting of generation, load, and market prices, develops optimized operation plans based on predicted information and system constraints, participates in wholesale energy and ancillary service markets, and conducts settlement processes to distribute revenues among participating resources.

VPPs can be classified based on various criteria. The most common classification distinguishes between supply-side VPPs (focusing on generation resources), demand-side VPPs (emphasizing demand response), and hybrid VPPs (integrating both supply and demand resources) [13]. Another classification differentiates commercial VPPs (maximizing market revenues) from technical VPPs (prioritizing grid stability and reliability) [12].

Recent technological advances have further enhanced VPP capabilities. The integration of artificial intelligence and machine learning has improved forecasting accuracy and enabled real-time optimization [14]. Advanced energy storage technologies provide greater flexibility in balancing supply and demand [15]. Enhanced cybersecurity measures and interoperability standards ensure secure operation of diverse resources.

Recent technological advancements have significantly enhanced VPP capabilities, which improve coherency with legacy electricity system. Liu et al. [16] provided a comprehensive review of VPP technologies, including their conceptual evolution, control strategies, and demand-side frequency ancillary services (D-FCAS), and outlined an integrated path forward for building sustainable power grids, while advanced cybersecurity frameworks have strengthened system resilience against potential threats. As noted by Li et al. [17], enhancing cyber-resilience in integrated energy systems with demand response through deep reinforcement learning has become a critical component of modern VPP architecture. Similarly, Ryu et al. [18] emphasized that VPPs with renewable energy sources and energy storage systems provide substantial sustainability benefits for power grids through advanced formation and control techniques. These technological developments have expanded VPPs’ potential contributions to social welfare beyond their initial market participation functions, creating positive externalities that are not fully captured in conventional business models or market transactions.

The global VPP market is experiencing rapid growth, with projections reaching up to a value of more than USD 4.7 billion in 2027, expanding at a robust CAGR of 34% from 2021 to 2027 [19]. Europe, particularly Germany, with companies like Next Kraftwerke, has developed the most mature VPP markets. In North America, FERC Order 2222 has created a regulatory framework enabling DER aggregation in wholesale markets [20]. Australia has seen significant residential VPP development, leveraging high-rooftop solar penetration [9]. In South Korea, the regulatory foundation for VPPs is being established through the Special Act on Distributed Energy Activation (effective June 2024), which explicitly defines VPPs as integrated power plants and provides a legal basis for their operation. The Small-scale Power Brokerage Business (implemented in 2019) serves as an early model for supply-side VPPs.

2.2. Economic Valuation of Energy and Environmental Technologies Using CVMs

The CVM represents a cornerstone of non-market valuation techniques, specifically designed to estimate the economic value of goods and services not traded in conventional markets [21]. Rooted in welfare economics, CVM measures individuals’ willingness to pay (WTP) or willingness to accept (WTA) compensation for changes in the provision of non-market goods through carefully structured survey instruments.

The theoretical foundation of CVM rests on Hicksian welfare measures. As explained in the literature [22], measured WTP/WTA can be interpreted as an indicator representing changes in individual utility or welfare in monetary units, based on the Hicks’ compensating or equivalent surplus. This stated preference approach contrasts with revealed preference methods, which infer values from observed market behavior.

CVM possesses unique advantages in valuing non-market goods. Its primary strength lies in capturing total economic value, including both use and non-use values [10]. The literature emphasizes that while RP methods are limited to measuring use values reflected in market behavior, CVM is virtually the only methodology capable of measuring non-use values [23]. This comprehensiveness is particularly crucial for public goods like environmental quality or energy system improvements. The implementation of CVM follows a structured six-step methodology, as outlined in the NOAA Panel guidelines [24]. However, CVM faces several methodological challenges. These include hypothetical bias, starting point bias, information bias, strategic bias, and scope insensitivity effects [24]. To address these concerns, best practices have evolved following NOAA Panel recommendations, including conservative design choices, adequate information provision without overwhelming respondents, and inclusion of follow-up questions to identify protest responses.

Table 1. Major CVM studies in energy and environment sectors.

Study	Valuation Object	Location	CVM Design	Key Results
[25]	Renewable energy expansion	Beijing, China	Face-to-face interview/DC/monthly electricity bill surcharge	Monthly WTP: USD 2.7–3.3; income, electricity consumption, and RE knowledge significant
[26]	Renewable energy share increase	Urban Greece	Questionnaire/DC/quarterly electricity bill	Quarterly WTP: EUR 26.5; education level and government subsidy perception significant
[27]	Community solar participation	South Korea	Online survey/DBDC/monthly payment	Monthly WTP: KRW 25,572; gender, solar experience, and income significant
[28]	Renewable energy support policy	USA	National phone/online/DC/monthly bill (mandatory vs. voluntary)	Mandatory payment method preferred; environmental attitudes and income influential
[29]	Grid fortification (outage reduction)	Oklahoma, USA	Mail/online survey/DC/monthly electricity bill	Monthly WTP: USD 14.69; outage experience and risk perception significant
[30]	Grid improvement	Oklahoma, USA	Mail/online survey/DC/monthly electricity bill	WTP related to cost, political orientation, institutional trust, and outage risk perception

is a summary of major CVM studies in energy and environment sectors.

Recent energy sector CVM applications have revealed several important patterns. Studies on renewable energy expansion consistently find positive WTP values, with environmental concerns and energy security motivations as primary drivers [25,26]. Research on grid modernization shows significant public valuation of reliability improvements, with past outage experiences influencing WTP [29,30]. The choice of payment vehicle (taxes vs. fees vs. voluntary payments) can significantly affect stated WTP values [28]. Despite ongoing methodological debates, CVM remains the appropriate method capable of capturing the full range of values associated with non-market goods, particularly non-use values [23]. When properly implemented following established guidelines, CVM provides valuable insights for policy decisions involving public goods and complex technological systems, like VPPs.

3. Methodology

3.1. Research Framework

This study employed a theory-driven approach to investigate the determinants of WTP for VPPs in South Korea. The research framework is grounded in two theoretical foundations: (1) the economic valuation of non-market goods through stated preference methods, and (2) the analysis of heterogeneous preferences in energy transition contexts [31].

The conceptual framework posits that WTP for VPPs is influenced by two primary dimensions. The first dimension encompasses electricity bill perception factors, including current electricity consumption levels, perceived fairness of electricity pricing, support for location-based pricing mechanisms, and attitudes toward fuel cost adjustment systems [32]. The second dimension focuses on electricity generation mix preferences, specifically examining attitudes toward nuclear power expansion, support for replacing nuclear power with renewables, and preferences for transitioning from coal to renewable energy sources [33,34].

To accommodate the possibility that some respondents may have zero WTP for VPP implementation, this study employed the double-bounded dichotomous choice (DBDC) spike model [35]. This methodological choice reflects the recognition that innovative energy technologies may face resistance from certain population segments, resulting in a meaningful proportion of zero-WTP responses [35].

The methodological approach in this study represents an important advancement in valuing emerging energy technologies. By employing the CVM with a double-bounded dichotomous choice spike model, we addressed two critical challenges in valuing VPPs. First, CVM enables the estimation of both use and non-use values, capturing the full spectrum of benefits that VPPs provide. This is particularly important for public goods like grid stability and environmental improvement that would be undervalued by revealed preference methods. Second, the spike model explicitly accounts for the possibility of zero WTP, which is a common feature when valuing unfamiliar technologies to the public. This methodology allowed us to distinguish between those who assign no value to VPPs from those who assign very low values, providing a more understanding of public acceptance barriers.

3.2. Samples

The empirical analysis utilized data collected through a nationwide survey of 1105 South Korean households conducted in February 2024. The sampling strategy employed stratified random sampling to ensure adequate representation across all major regions of South Korea. The professional survey firm conducted interviews following the guidelines established by the NOAA Panel for contingent valuation studies, ensuring high data quality and response reliability.

Table 2. Sample respondents’ distribution.

Variable	Label	Frequency	Percent
Gender	Male	560	50.7
	Female	545	49.3
Age	20–29	183	16.6
	30–39	201	18.2
	40–49	238	21.5
	50–59	259	23.4
	60–69	224	20.3
Education	Middle school or below	25	2.3
	High school	141	12.8
	College/University	779	70.5
	Graduate school	160	14.5
Household Income	Below 1M KRW	53	4.8
	1–3M KRW	203	18.4
	3–5M KRW	338	30.6
	5–7M KRW	217	19.6
	Above 7M KRW	294	26.6
Residence Type	Apartment	711	64.3
	Detached house	87	7.9
	Villa	195	17.6
	Others	112	10.1
Total		1105	100

shows a sample summary.

The sample demonstrated strong representativeness of the national population. Gender distribution was nearly balanced, with males comprising 50.7% and females 49.3% of respondents. Age groups were represented across the 20–69-year-old range, with the largest cohorts in the 40–49 (21.5%) and 50–59 (23.4%) age brackets. Educational attainment in the sample reflected Korea’s highly educated population, with 85% of respondents having completed college education or higher. Household income distribution spanned all major income categories, with the median falling in the KRW 3–5 million monthly range, consistent with national statistics.

The descriptive statistics of

Table 3. Descriptive statistics of variables.

Variables	Mean	SD	Correlation
			1.	2.	3.	4.	5.	6.	7.
1. Average Electricity Bill	5.48	3.12	1
2. Fairness on Electricity Fare Design	2.73	0.75	−0.22	1
3. Support on LMP	3.23	1.12	−0.05	0.16	1
4. Support on Fuel Cost Adjustment	3.24	0.87	0.01	0.16	0.34	1
5. Preference for Nuclear Expansion	3.12	1.15	0.07	0	0.01	0.16	1
6. Preference for Nuclear Reduction and Renewable Expansion	3.81	1.01	−0.01	0.05	0.16	0.02	−0.52	1
7. Preference for Coal Reduction and Renewable Expansion	4.12	0.8	−0.06	0.06	0.14	0.03	−0.26	0.55	1

reveal several noteworthy patterns among the key variables in our study. The average electricity bill showed considerable variation (M = 5.48, SD = 3.12), indicating substantial heterogeneity in household electricity consumption levels across the sample. Respondents generally demonstrated moderate fairness expectations regarding electricity fare design (M = 2.73, SD = 0.75) and moderate support for both LMP implementation (M = 3.23, SD = 1.12) and fuel cost adjustment mechanisms (M = 3.24, SD = 0.87). Interestingly, preferences for renewable energy expansion showed higher support (M = 3.81–4.12) compared to nuclear expansion (M = 3.12), suggesting a public inclination toward renewable energy sources. The correlation analysis indicated that preferences for nuclear expansion and preferences for nuclear reduction with renewable expansion were negatively correlated (r = −0.52), confirming the expected opposing nature of these policy preferences. Additionally, support for fuel cost adjustment and LMP showed a moderate positive correlation (r = 0.34), suggesting that individuals who support one market-oriented pricing mechanism tend to support others as well.

The survey instrument was carefully designed to elicit accurate WTP responses. It began with a detailed scenario description of government-led VPP implementation, emphasizing the public goods’ nature of the system and its role in facilitating renewable energy integration. In the survey questionnaire, we also specifically explained why the government budget must be spent to install public-led VPPs. The DBDC format presented respondents with an initial bid amount, followed by a higher bid if they accepted the initial amount or a lower bid if they rejected it. This approach improved statistical efficiency compared to single-bounded formats, while maintaining similarity to real-world decision-making processes [36]. The questionnaire also included comprehensive questions on electricity bill perceptions and generation mix preferences to capture the key explanatory variables in our theoretical framework.

We analyzed the distribution of response patterns across different initial bid amounts.

Table 4. Cross-table of first bid and respondents’ answer.

Bid	No–No–No	No–No–Yes	No–Yes	Yes–No	Yes–Yes
1000	15	2	8	13	71
2000	20	5	8	22	56
3000	21	3	13	26	49
4000	22	3	14	25	47
5000	23	4	10	36	38
6000	20	4	17	43	29
7000	22	9	15	27	37
8000	18	10	5	33	43
9000	24	17	9	29	31
10,000	21	13	12	24	39

presents the cross-tabulation of initial bid values (ranging from KRW 1000 to KRW 10,000) and respondents’ response patterns. The systematic variation in response patterns across bid levels provided critical evidence for distinguishing zero WTP from responses that have little benefit. Notably, the proportion of “No–No–No” responses remained relatively stable across different bid amounts, ranging from 13.7% to 21.8%. Moreover, there was an observable trend indicating that the “No–No” response rate increased with higher initial bid amounts. The presence of “No–No–Yes” responses indicated respondents who rejected the specific payment amounts but acknowledged positive value for VPPs, supporting the validity of our spike model specification. This pattern confirmed that the spike probability identified in our models represents preference heterogeneity, providing robust evidence for interpreting approximately one-third of the population as having legitimate zero WTP for VPP implementation.

3.3. Statistical Model

The analysis employed the DBDC spike model developed by Kriström [37] and refined by Yoo and Kwak [38]. This model is particularly appropriate for valuing public goods where a significant proportion of the population may have zero WTP. The spike model explicitly accounts for the probability mass at zero WTP, distinguishing between zero utility and non-zero responses. The DBDC spike model can be expressed as follows. Let WTP denote the latent willingness-to-pay, which follows a mixed distribution:

$$WTP=\left\{\begin{array}{c}0withprobabilityp\\ exp(\mathbf{x}\mathsf{\beta }+\epsilon )withprobability(1-p)\end{array}\right.,$$

(1)

where:

p is the spike probability (proportion of respondents with zero WTP),

$\mathbf{x}$ is a vector of explanatory variables,

$\mathsf{\beta }$ is a vector of coefficients to be estimated,

$\mathsf{\epsilon }$ is a random error term following a logistic distribution.

For the double-bounded format, respondents face two bid amounts. The first bid (B₁) is followed by a second bid (B₂), which is either higher (B₂^H = 2B₁) if the first bid is accepted, or lower (B₂^L = B₁/2) if the first bid is rejected.

The response patterns can be categorized as:

YY: accept both bids (WTP ≥ B₂ᴴ),

YN: accept first, reject second (B₁ ≤ WTP < B₂^H),

NY: reject first, accept second (B₂ᴸ ≤ WTP < B₁),

NNY: reject both bids, but WTP > 0,

NNN: true zero WTP.

The likelihood function for the DBDC spike model is:

$$\begin{gathered} L={\prod }_{i=1}^N{\left[\left(1-p\right)\times \mathrm{Pr}\left(WTP\ge B_2^H\right)\right]}^{Y{Y}_i}\times {\left[\left(1-p\right)\times \mathrm{Pr}\left(B_1\le WTP<B_2^H\right)\right]}^{Y{N}_i}\times {\left[\left(1-p\right)\times \\ \mathrm{Pr}\left(B_2^L\le WTP<B_1\right)\right]}^{N{Y}_i}\times {\left[\left(1-p\right)\times \mathrm{Pr}\left(0<WTP<B_2^L\right)+p\right]}^{N{NY}_i}. \end{gathered}$$

(2)

The mean WTP is calculated as:

$$E\left[WTP\right]=\left(1-p\right)\times E\left[WTP|WTP>0\right],$$

(3)

where $E\left[WTP|WTP>0\right]=\exp \left(x^{\prime }\mathsf{\beta }+{\mathsf{\sigma }}^2/2\right)$ for the log-normal distribution.

The model specification followed a two-part structure. First, the probability of having positive WTP was modeled using a binary choice framework. Second, conditional on positive WTP, the magnitude of WTP was estimated using the responses to the double-bounded questions. The combined model yielded three key parameters: the spike probability (proportion with zero WTP), the mean WTP conditional on positive WTP, and the unconditional mean WTP for the entire population [38].

The empirical specification included age and household income as demographic controls, consistent with the CVM literature [35,39]. The key explanatory variables were grouped into two sets corresponding to our theoretical framework: electricity bill perception variables (current electricity level, perceived fairness, support for location-based pricing, and fuel cost adjustment preferences) and generation mix preference variables (nuclear expansion support, nuclear-to-renewable transition support, and coal-to-renewable transition support) [25,26,27].

4. Analysis Results

The estimation results from the double-bounded spike model revealed distinct patterns in the determinants of WTP for VPP implementation. Two separate models were estimated to examine the effects of electricity bill perceptions and generation mix preferences on public valuation of VPPs.

Table 5. DBDC spike model results with electricity bill perception.

Variable	Coefficient	Std. Error	t-Value	p-Value
Constant	−2.156 ***	0.432	−4.993	0.000
Age	−0.015 **	0.007	−2.142	0.032
Household Income	0.184 ***	0.041	4.488	0.000
Average Electricity Bill	−0.082 **	0.038	−2.158	0.031
Fairness on Electricity Fare Design	0.246 ***	0.064	3.844	0.000
Support on LMP	0.189 ***	0.058	3.259	0.001
Support on Fuel Cost Adjustment	0.214 ***	0.061	3.508	0.000
Log-likelihood	−1842.56
Spike Probability	0.342 ***	0.034	10.059	0.000
N	1105

Note: *** and ** denote significance at 1% and 5% levels, respectively.

shows the analysis results of the DBDC spike model with the electricity bill perception model.

In the electricity bill perception model, all included variables demonstrated statistically significant effects on WTP. Age exhibited a negative coefficient (−0.015, p < 0.05), indicating that older respondents have lower WTP for VPP implementation. This finding aligns with previous studies, showing that younger generations tend to be more supportive of innovative energy technologies [26]. Household income showed a strong positive effect (0.184, p < 0.001), confirming the theoretical expectation that higher-income households have a greater ability to pay for environmental improvements.

Among the electricity perception variables, the current electricity consumption level had a negative impact on WTP (−0.082, p < 0.05), suggesting that households with higher electricity bills were less willing to pay additional amounts for VPP implementation. Conversely, the perceived fairness of current electricity pricing demonstrated a positive effect (0.246, p < 0.001), indicating that respondents who viewed the current system as fair were more willing to support new investments. Support for location-based pricing (0.189, p < 0.001) and fuel cost adjustment mechanisms (0.214, p < 0.001) both showed positive effects, suggesting that market-oriented respondents exhibited higher WTP for VPPs.

These findings carry some notable implications for VPP deployment strategies and policy design from a social benefits perspective. The negative relationship between current electricity consumption and WTP suggests that high-usage households, who could potentially provide the greatest grid stabilization benefits through VPP participation, may require targeted incentive mechanisms rather than simply relying on voluntary participation. The strong positive coefficient for income (0.184) highlighted a potential equity challenge, as higher social welfare gains from VPPs could be concentrated among affluent households unless specific mechanisms are designed to engage lower-income segments who may benefit most from reduced electricity costs. The positive effects of market-oriented preferences (LMP and fuel cost adjustment support) indicated that VPP programs may achieve greater social acceptance and participation rates in regions where consumers already understand and support dynamic pricing mechanisms, potentially accelerating the realization of grid-level benefits, such as reduced peak demand and improved renewable energy integration. Most significantly, the positive effect of perceived fairness (0.246) suggested that transparent communication about how VPP programs distribute costs and benefits across different customer segments will be crucial for maximizing social welfare gains and ensuring broad public support for these grid modernization investments.

Table 6. DBDC spike model results with generation mix preference.

Variable	Coefficient	Std. Error	t-Value	p-Value
Constant	−1.892 ***	0.398	−4.754	0.000
Age	−0.012 **	0.006	−2.000	0.046
Household Income	0.168 ***	0.039	4.308	0.000
Preference for Nuclear Expansion	−0.156 ***	0.052	−3.000	0.003
Preference for Nuclear Reduction and Renewable Expansion	0.278 ***	0.063	4.413	0.000
Preference for Coal reduction and Renewable Expansion	0.235 ***	0.059	3.983	0.000
Log-likelihood	−1798.23
Spike Probability	0.318 ***	0.032	9.938	0.000
N	1105

Note: *** and ** denote significance at 1% and 5% levels, respectively.

presents the analysis results of the DBDC spike model with the generation mix preference model. The generation mix preference model revealed a different set of dynamics. While age and income maintained their directional effects, the generation preference variables showed interesting patterns. Support for nuclear expansion exhibited a negative coefficient (−0.156, p < 0.01), indicating that pro-nuclear respondents had lower WTP for VPPs. In contrast, support for transitioning from nuclear to renewables (0.278, p < 0.001) and from coal to renewables (0.235, p < 0.001) both demonstrated strong positive effects on WTP. These results suggested that VPPs are primarily valued as facilitators of renewable energy integration rather than as general grid infrastructure.

The spike coefficients in both models were highly significant, with values of 0.342 and 0.318, respectively. These estimates indicated that approximately one-third of the population had zero WTP for VPP implementation, highlighting the challenge of introducing innovative energy technologies to the general public.

These generation mix preferences revealed crucial insights for maximizing VPPs’ social benefits through strategic positioning within Korea’s energy transition discourse. The strong positive coefficients for renewable energy transition preferences (0.278 and 0.235) indicated that VPPs could generate greater social welfare by explicitly framing their value proposition around facilitating renewable energy integration, such as managing intermittency and enabling higher renewable penetration rates. The negative coefficient for nuclear expansion (−0.156) suggested that VPPs will face greater public resistance in scenarios where they are perceived as supporting nuclear infrastructure, potentially limiting social acceptance and the realization of grid-wide efficiency gains. The high spike probability (31.8%) represented a significant portion of society that may miss out on VPP benefits entirely, pointing to the need for comprehensive public education programs that demonstrate how VPPs can reduce overall system costs and improve energy security for all consumers, not just direct participants. From a social equity perspective, the positive correlation between renewable energy support and VPP valuation suggested that VPP programs can help achieve broader societal goals of environmental sustainability while generating economic benefits, but success will depend on clearly communicating how VPPs accelerate the clean energy transition rather than merely serve as technological upgrades to the existing system.

Based on these coefficient estimates, the models yielded specific WTP values, as shown in

Table 7. Estimated WTP values (KRW per household per year).

Model	Mean WTP (Conditional)	Mean WTP (Unconditional)	Median WTP
Electricity Bill Perception	35,672	23,474	18,956
Generation Mix Preference	38,924	26,545	21,387

. For the electricity bill perception model, the mean WTP conditional on positive WTP was estimated at KRW 35,672 per household per year. When accounting for the spike probability, the unconditional mean WTP across the entire population was KRW 23,474 annually. The generation mix preference model produced slightly higher values, with a conditional mean WTP of KRW 38,924 and unconditional mean WTP of KRW 26,545 per year.

5. Discussion

5.1. Theoretical Implications

The empirical findings contributed to several theoretical domains at the intersection of energy economics, environmental valuation, and behavioral economics. This study extended the application of the contingent valuation methodology to emerging energy technologies, specifically VPPs. The significant spike probability observed in both models validated the theoretical importance of accounting for zero-WTP responses when valuing innovative technological solutions [40]. This finding aligns with innovation adoption theory, which predicts that early-stage technologies face resistance from risk-averse population segments [41].

The differential effects of electricity perception variables versus generation mix preferences on WTP revealed the multidimensional nature of energy transition preferences. This empirical evidence supports theoretical frameworks suggesting that public acceptance on energy infrastructure depends on distinct cognitive schemas [42]. Economic considerations, captured through electricity bill perceptions, operate independently from environmental values reflected in generation mix preferences. This heterogeneity challenges simplistic models of energy technology acceptance and highlights the complexity of public decision-making in energy transitions [43].

The contrasting effects of nuclear expansion preferences versus renewable transition support provide empirical evidence for what scholars have termed the “nuclear paradox” in climate policy [44]. Despite nuclear power’s low-carbon credentials, public preferences aligned more strongly with renewable energy pathways. This finding suggests that non-carbon attributes, such as perceived safety risks and waste management concerns, significantly influence energy technology valuations, supporting theoretical models that incorporate multiple attribute frameworks in environmental valuation.

Furthermore, the positive effects of perceived electricity pricing fairness and support for market-based mechanisms on WTP extend institutional economics theory to the energy sector. These results demonstrated that market design features and institutional trust influence public acceptance of energy investments, suggesting that successful energy transitions require not only technological innovation but also institutional legitimacy.

5.2. Managerial and Policy Implications

The heterogeneous nature of WTP determinants revealed in this study has profound implications for energy policy design and implementation. Policymakers must recognize that public support for VPPs is not uniform but varies systematically with individual characteristics and attitudes. This heterogeneity necessitates targeted communication strategies that address specific concerns of different population segments.

A key contribution of this study is its shift from business-centric to society-centric valuation of VPPs. While previous research has focused on revenue optimization and market participation strategies for VPP operators, our approach quantified the broader social benefits that justify public investment in these systems. The estimated annual WTP values of KRW 23,474 to KRW 26,545 per household represent the social welfare gains from VPP implementation, encompassing both tangible benefits, such as grid reliability improvements, and intangible benefits, such as environmental quality enhancement and energy security. When aggregated to the national level, these values provide policymakers with a comprehensive measure of VPPs’ contribution to social welfare, enabling more informed allocation of public resources for energy transition.

For households currently experiencing high electricity costs, communication should emphasize VPPs’ potential for improving system efficiency and reducing long-term electricity prices. These messages should be coupled with transparent information about how VPPs can optimize electricity distribution and potentially lower peak demand charges. Conversely, for environmentally conscious consumers who support renewable energy transition, messaging should highlight VPPs’ critical role in managing renewable energy intermittency and facilitating higher renewable penetration rates.

The substantial spike probability observed in both models indicates that approximately one-third of the population currently has zero WTP for VPP implementation. This finding suggests that immediate universal deployment may face significant public resistance. Instead, a phased implementation approach is recommended, beginning with pilot projects in regions showing higher predicted acceptance based on demographic and attitudinal characteristics. These pilot projects should be designed to demonstrate tangible benefits, creating positive spillover effects that may shift public perceptions over time.

The positive correlation between support for market-based electricity pricing mechanisms and WTP of VPP suggests that VPP implementation should be coordinated with broader electricity market reforms. Policymakers should develop transparent pricing mechanisms that clearly reflect the value VPPs provide to the grid, including services such as frequency regulation, voltage support, and peak shaving. Regulatory frameworks must enable fair compensation for VPP participants, creating economic incentives that align with the public good benefits identified in this study.

The observed negative relationship between nuclear expansion preferences and VPP willingness to pay presents a fundamental policy challenge, as VPPs are perceived primarily as renewable energy enablers rather than comprehensive grid stability solutions that benefit all generation sources. This misperception creates unnecessary friction because VPPs provide critical grid support services, including frequency regulation, voltage control, and emergency response capabilities, that enhance operational safety and efficiency for nuclear power plants alongside other generation sources. Policymakers should develop messaging strategies that emphasize VPPs’ role in enhancing overall power system reliability rather than focusing exclusively on renewable integration, highlighting how these systems provide distributed backup power, reduce transmission stress, and ensure stable grid conditions necessary for safe nuclear operations. A strategic implementation approach should begin with pilot projects in regions with diverse generation portfolios, demonstrating how VPPs improve grid stability metrics, reduce outage frequencies, and enhance system resilience that benefit all electricity consumers and generation facilities. By positioning VPPs as technology-neutral grid optimization platforms that enhance the performance of Korea’s entire energy infrastructure, policymakers can build broader public support while avoiding polarization between competing energy technology narratives.

Lastly, based on the estimated unconditional mean WTP values ranging from KRW 23,474 to KRW 26,545 annually per household, policymakers can design funding mechanisms that align with public valuation levels. These amounts suggest that a modest surcharge on electricity bills could generate substantial funding for VPP development while remaining within acceptable bounds for most households. However, the presence of a significant zero-WTP population segment suggests that voluntary opt-in programs or tiered participation structures may be more politically feasible than mandatory universal charges.

5.3. Limitations and Future Research

Several limitations of this study should be acknowledged. First, the hypothetical nature of the contingent valuation scenario may lead to stated preferences that differ from revealed preferences once VPPs are implemented. While we employed best practices to minimize hypothetical bias, including scenario consequentiality, the novelty of VPPs means that respondents had limited prior experience to inform their valuation. Future research should complement these findings with a pilot study based on revealed preference data as VPP implementation progresses, allowing for validation and calibration of WTP estimates.

Second, the cross-sectional design captured valuations at a specific point in time, whereas public acceptance of innovative technologies, such as VPPs, typically evolves as familiarity increases. Longitudinal studies tracking WTP before, during, and after demonstration projects would provide valuable insights into preference formation and stability. Such research could identify whether the significant spike probability we observed diminishes over time with increased exposure to VPP benefits.

Third, our study examined preferences for government-led VPP implementation, but alternative ownership and governance models may yield different valuation patterns. Comparative analysis of WTP for public, private, community-owned, and hybrid VPP models would provide important insights for institutional design. Such research could identify whether the zero-WTP segment we observed is responding to the technology itself or to specific implementation mechanisms.

Finally, while our national-level survey provided robust overall estimates, regional variations in renewable resource availability, grid conditions, and energy culture may influence local WTP patterns. Future research employing spatially explicit analysis could identify high-acceptance regions for initial VPP deployment, optimizing the sequencing of national implementation strategies.

6. Conclusions

This study provided a comprehensive empirical economic valuation of VPPs in the South Korean context using the CVM, which is an appropriate method for capturing the non-use value. The research demonstrated that Korean households exhibited significant but heterogeneous WTP for VPP implementation, with estimated annual values ranging from KRW 23,474 to KRW 26,545 per household depending on the underlying motivational factors considered.

The analysis revealed that VPP valuation was influenced by two distinct dimensions: electricity bill perceptions and generation mix preferences. These dimensions operate through different psychological and economic mechanisms, with generation mix preferences showing particularly strong effects when aligned with renewable energy transition goals. The finding that support for renewable energy transitions correlates more strongly with WTP of VPP than does support for nuclear expansion suggests that public perception of VPPs is intimately connected to broader energy transition narratives.

The substantial spike probability identified in both models, indicating that approximately one-third of the population has zero WTP for VPP implementation, highlights fundamental challenges in introducing novel energy technologies. This finding underscores the critical importance of carefully designed implementation strategies that account for varying levels of public acceptance and understanding.

From a policy perspective, our results provide evidence-based guidance for VPP deployment strategies. Successful implementation requires integration with broader electricity market reforms, development of transparent pricing mechanisms, and strategic alignment with renewable energy expansion goals. The heterogeneous nature of public preferences calls for differentiated implementation approaches that address diverse stakeholder concerns while building upon existing support for energy transition.

Future research should investigate temporal dynamics of VPP acceptance as public familiarity with the technology increases. Longitudinal studies could reveal how demonstration projects and early implementations influence public perceptions and WTP over time. Additionally, regional variations in WTP determinants warrant further investigation, as local electricity market conditions and renewable resource availability may significantly influence public support. Comparative studies examining different VPP ownership models, particularly the relative acceptance of public versus private VPP operators, could provide valuable insights for optimal institutional design.

This study contributes to the expanding literature on energy transition economics by providing rigorous empirical evidence on public valuation of emerging grid technologies. As nations worldwide pursue increasingly ambitious decarbonization targets, understanding public preferences for enabling technologies such as VPPs becomes crucial for effective policy design and implementation. The methodology and findings presented here offer a foundation for similar investigations in other national contexts, potentially contributing to a comparative understanding of energy transition dynamics across different institutional and cultural settings.