This paper presents a geospatially resolved modeling framework for ex-ante assessment of electricity subsidy instruments applied to least-cost electrification plans. The framework integrates subsidy modeling directly into the planning stage, enabling evaluation of how alternative subsidy structures alter private developer incentives, mini-grid system sizing decisions, and cost outcomes — before programs are deployed. We apply the framework to Sierra Leone, examining three instruments selected for their prevalence in electrification programs: direct capital subsidies, concessional finance, and supply-side tariff subsidies. The analysis yields three principal findings. First, investment subsidies introduce efficiency distortions: capital grants and concessional finance both incentivize system over-sizing, generating excess capital expenditure for developers and financiers alike, while tariff subsidies create a recurring fiscal burden without inducing the same investment distortion. Second, under a constrained public budget, the instruments produce divergent electrification trajectories: capital subsidies accelerate the rate of new connections, concessional finance may slow it, and tariff subsidies have a negligible effect on connection pace. Third, subsidy allocation strategies that prioritize developer financial sustainability tend to favor high-demand, densely populated communities, deferring connections to lower-demand settlements and thereby reinforcing existing spatial inequalities in access. These results demonstrate that the efficiency and distributional consequences of subsidy design are inseparable: instrument choice determines not only how public resources are spent but also who benefits, when, and at what long-run cost. The framework provides a practical tool for policymakers to evaluate these trade-offs before committing to a subsidy program.
Nigeria’s electricity system has long struggled to deliver reliable, affordable, and sustainable power despite the country’s substantial energy endowments. Mounting climate obligations and a rapidly expanding population underscore the inadequacy of continuing dependence on fossil-fuel-based energy generation. The sector remains hindered by chronic instability, constrained generation capacity, gas supply interruptions to thermal plants, hydrological volatility affecting hydropower output, high technical and commercial losses across the transmission network, low metering devices, and ageing infrastructure that leaves millions outside the formal grid. The Electricity Act 2023 (as amended 2024) represents Nigeria’s most ambitious legislative effort to restructure the power sector since liberalisation. This article undertakes a doctrinal and policy-oriented legal analysis to interrogate the statute’s innovations, operational constraints, and alignment with global best practices. Drawing on statutory interpretation, judicial authorities, and contemporary scholarly discourse, the paper demonstrates that although the Act signals a significant shift toward decentralisation and renewable integration, several structural deficiencies persist. These include ambiguous regulatory mandates, an over-centralised tariff-setting framework, weak coordination between federal and state regulatory spheres, and imprecise terminologies that risk administrative uncertainty in areas such as mini-grids and embedded generation. The article proposes targeted amendments to strengthen regulatory clarity, streamline institutional responsibilities, and introduce enforceable compliance mechanisms capable of supporting investment, enhancing grid resilience, and accelerating Nigeria’s transition to a diversified and sustainable electricity system. Addressing these gaps is essential for transforming the Act from an aspirational reform instrument into a functional catalyst for long-term energy security and economic development in Nigeria.
China’s distributed photovoltaic (PV) expansion has accelerated through policy support, promotional activity, and diverse ownership models. While this growth has increased deployment, it has also created user-side risks that are not always visible in aggregate installation statistics. Using Expectation-Disconfirmation Theory as an analytical lens, this study examines post-installation experiences among residential PV users in China. It draws on semi-structured interviews with 50 self-selected but information-rich users who shared installation experiences on Chinese social media platforms. Rather than estimating population-level satisfaction or problem prevalence, the study identifies recurring sources of expectation confirmation and disconfirmation. Dissatisfaction often arose from after-sales service failures, contractual or rights-protection disputes, misleading promotion, involuntary installation, and fraud-related risks. Business models shaped risk exposure by allocating ownership, maintenance responsibilities, financial obligations, and property-rights constraints in different ways. The findings show that actual performance in residential PV includes not only technical and economic outcomes, but also service, contractual, and governance-related performance. The study provides diagnostic evidence for improving consumer protection, contract transparency, and post-installation governance in China’s distributed PV sector.
Accurate estimation of peak electricity loads is important for planning infrastructure and system costs. Prospective energy system models often emphasize total generation rather than instantaneous power draw, in part for computational tractability, and thus necessarily underestimate true peak loads with coarse timesteps and low-resolution representation of demand. As the structure of electricity demand changes (e.g., due to beneficial electrification), historical heuristics about acceptable timesteps for estimating peak loads might no longer hold. Here, we use a validated agent-based model of households in Aotearoa New Zealand to estimate peak errors under electrification and other conditions by generating 1-minute residential electricity demand profiles, then resampling with timesteps from 2 min to 24 h. Coarser timesteps increase peak load errors: 1-hour timesteps underestimate true peaks by 44% for one household (with implications for e.g., electric panel sizing), and 9% for 100 households (with implications for e.g., total dispatchable generation requirements). Error is sensitive to large insulation increases, solar PV, and electric vehicles. We recommend modelers should avoid coarse timesteps for applications like capacity expansion or battery sizing, where absolute peaks matter. We encourage modelers to carefully consider how changing system structure changes assumptions about acceptable simplifications, especially in safety-relevant contexts.
U.S. transmission spending nearly tripled between 2003 and 2023, with most recent investment flowing into local projects recovered through the Federal Energy Regulatory Commission's (FERC) formula-rate process. Formula rates were introduced to streamline cost recovery and encourage transmission investment, but when paired with rate-of-return regulation and limited project-level review, they create a structural risk of overbuilding (the Averch–Johnson–Wellisz capital bias) and shift the burden of contesting unjust or unreasonable charges onto state regulators and ratepayer advocates. Drawing on FERC enforcement audits, recent commissioner statements, current litigation in PJM, ISO-NE and MISO and a growing policy literature—including Rocky Mountain Institute's Mind the Regulatory Gap (2024), Peskoe (2021, 2023), and The Brattle Group studies of competitive transmission—this paper documents an inversion of review—testing that comes after the fact rather than before it, with the burden of justification on intervenors rather than on the utility—under which billions of dollars of local-transmission spending escape meaningful ex ante scrutiny. It also documents the limited and inconsistent project-level cost data available across regions, which compounds the problem. The defect it identifies is procedural in origin and substantive in consequence: the process supplies no occasion at which need, prudence, and cost-effectiveness can be tested while the answer could still change the project. The paper sets out reforms targeted at both: project-level justification records above a materiality threshold; mandatory consideration of grid-enhancing technologies and non-wires alternatives; standardized, machine-readable cost reporting; expanded and accelerated FERC audits with rapid refunds; an Independent Transmission Monitor; outcome-linked incentives, an expanded competitive procurement process, and a dedicated intervenor-compensation mechanism. These reforms can preserve the benefits of formula-rate efficiency for clearly needed investment while restoring discipline over project selection, scope, and cost.
Brazil’s Northeast—55 million people and GDP per capita one-third the national average—hosted the developing world’s largest wind boom: from near zero to 31 GW in barely a decade. Did the gains reach the communities that hosted it? Exploiting the staggered rollout of wind farms across 1613 municipalities (2005–2021) with the Callaway-Sant’Anna (2021) and Sun-Abraham (2021) estimators, we compare 41 host municipalities to 1572 controls. Wind farm installation raises GDP per capita by about 20 % (15–23 % across estimators), and pre-treatment trends are flat under heterogeneity-robust estimation. The gains are not merely mechanical: value added in local services—a sector unrelated to electricity generation—rises about 12 %, and formal employment increases in both poorer and richer hosts. Proportional gains are larger in poorer municipalities (+29 %) than richer ones (+13 %; +26 and +16 % under the Callaway-Sant’Anna estimator), yet in absolute terms both gain similarly (R$3200–4100 per capita): the larger percentage reflects a smaller base, not a larger income gain. Results survive permutation placebo tests (p < 0.001), municipality-level wild cluster bootstrap (p = 0.008), municipality-specific linear trends, and the exclusion of any single state. Wind energy can lift incomes in some of Latin America’s poorest communities—proportionally, if not in absolute magnitude.
India’s renewable energy transition is deeply influenced by subnational institutions, particularly electricity regulators. This paper examines Karnataka’s energy landscape to explore how regulatory decisions both reflect and shape the politics of subnational energy transitions. Through an empirical analysis of over 370 regulatory and appellate orders issued between 2010 and 2022, it reveals that regulatory forums are not neutral or purely technical spaces but arenas of political and institutional contestation. This paper makes three key arguments. First, emerging actors, such as farmer-developer and developer associations in Karnataka, are increasingly participating in and challenging national energy ambitions. Policies must account for diverse interests across all regions while framing transition goals. Second, a regulatory design in which the same body creates regulations and adjudicates disputes arising from them, can produce legal uncertainty and a weak institutional framework. Finally, regulators play a central role in shaping both technical governance and socio-economic outcomes, using regulatory discretion to balance competing interests of consumers, utilities and renewable developers. This paper thus highlights that energy transition goes far beyond technology. Understanding subnational politics, the social and economic interests of all the key stakeholders, and how state regulators navigate these, is key for a sustainable and inclusive transition.
Rapid growth of variable renewable energy (VRE) is not only increasing operation challenges but also motivating wider deployment of energy storage systems (ESS). However, regulatory readiness for ESS deployment can be assessed in part by the extent to which grid codes explicitly recognize ESS and specify technical and operational obligations. Meanwhile, in single-buyer systems, ESS performance and economics depend less on market signals and more on centralized planning, dispatch decisions, and contract design, which create higher risks of underutilization and limited service stacking. Motivated by the lack of systematic review on ESS acknowledgement in grid codes, especially in single-buyer systems, this paper presents a comparative analysis of ESS acknowledgement and ESS-relevant clauses in publicly available grid codes of five Southeast Asian single-buyer countries: Cambodia, Indonesia, Malaysia, Thailand, and Vietnam. The analysis compares ESS resource classification, frequency and active-power operation requirements, voltage and reactive-power requirements, and ancillary-service participation provisions. The results show substantial differences in ESS regulatory maturity, ranging from the absence of explicit ESS recognition in Cambodia and most Indonesian grid-code provisions to dedicated ESS definitions and operational requirements in Malaysia, Thailand, and Vietnam. The findings suggest that explicit ESS recognition provides clearer operational and technical treatment of storage resources within single-buyer electricity systems and may help support more consistent implementation of ESS-related obligations and services.
The rapid expansion of variable renewable energy (VRE) is increasing net-load variability, ramping requirements, and operational uncertainty in power systems worldwide. Although a growing body of literature has developed metrics to quantify flexibility adequacy, comparatively less attention has been devoted to relating emerging flexibility constraints to the institutional responses adopted by electricity markets facing similar challenges. This article investigates the evolution of flexibility requirements in the Brazilian Interconnected System (SIN) through a probabilistic assessment framework combined with an international benchmark of flexibility mechanisms implemented in mature electricity markets. Potential flexibility stress is evaluated using probabilistic duck-curve representations, ramping indicators, flexibility deficit metrics, and representative operating conditions. The benchmark examines how jurisdictions such as California, PJM, Great Britain, Australia, and Chile have addressed increasing flexibility needs through operational and market-design mechanisms. Results indicate a significant increase in net-load variability and ramping stress under renewable-driven growth scenarios. Flexibility adequacy indicators deteriorate as renewable penetration expands, leading to more frequent and severe ramping conditions. The analysis also shows that operational patterns observed in the Brazilian system resemble conditions previously experienced in several mature electricity markets, where increasing flexibility requirements motivated the adoption of dedicated flexibility products and enhanced adequacy arrangements. Rather than proposing new flexibility metrics, the article contributes by linking quantitative flexibility assessment with the evolution of flexibility-oriented market mechanisms. The results provide a planning-oriented interpretation of flexibility adequacy indicators and highlight the growing importance of explicitly considering flexibility requirements in power systems undergoing rapid renewable expansion.
The increasing integration of artificial intelligence (AI) into the electricity grid presents both significant opportunities and challenges. This paper examines two related dimensions: "AI for the Grid," which explores the use of AIto enhance grid planning, operations, and market participation, and "AI on the Grid," which considers the rising electricity demand from AI-driven data centers and its implications for grid infrastructure and cost allocation. AI offers opportunities for the grid through advanced tools to improve system planning, operations, and resilience while also promoting affordability and reducing barriers to market entry. However, challenges remain regarding the reliability and trustworthiness of AI models, regulatory complexity, coordination across stakeholders, and potential market power concerns. Rapid load growth caused by AI on the grid will stress the bulk power system, creating challenges for reliability, infrastructure planning, and managing unpredictable loads. However, if incentivized and managed appropriately, data centers can also enhance grid flexibility and responsiveness. We establish eight specific research needs to help unleash AI innovation, while maintaining system reliability and affordability. For the grid these include, 1) evaluating productivity gains and risks of AI-assisted services, 2) advancing AI methods for operations and planning, 3) evaluating the potential of private, local, small language models (SLMs), and 4) assessing AI-driven market power risks. Research needs on the grid include, 1) establishing incentives for large load flexibility, 2) enhancing market structures and designs, 3) developing new cost-allocation strategies, and 4) balancing the costs of over-and under-planning for load growth in the face of uncertainty.
Hospitals are essential services and major electricity consumers, making them a strategically important but underused demand-side resource for utilities and regulators. This study examines the determinants of Energy Management System (EnMS) adoption in Taiwan's hospital sector to inform the design of policy instruments and demand-side management (DSM) schemes. Using survey data from 304 healthcare professionals and a Technology-Organization-Environment (TOE) framework, regression results show that market competitive pressure and financial efficiency are the primary drivers of EnMS adoption, whereas neither existing regulatory requirements nor mandates are statistically significant predictors of adoption, indicating a misalignment between top-down policy and hospitals' investment behavior. Perceived cybersecurity and information-security risks further emerge as key organizational constraints on the deployment of digitally enabled energy technologies. These findings suggest that electricity policy for hospitals should shift from a predominantly regulatory-push approach towards a market-pull strategy that combines performance-linked financial incentives and voluntary DSM programs with clear interoperability and cybersecurity standards. Such an integrated approach can better align hospital investment decisions with power system decarbonization objectives while maintaining the resilience and security of digital infrastructure.
Peer-to-peer (P2P) trading is increasingly recognized as a key mechanism for decentralized market regulation, yet existing approaches often lack robust frameworks to ensure fairness. This paper presents FairMarket-RL, a novel hybrid framework that combines Large Language Models (LLMs) with Reinforcement Learning (RL) to enable fairness-aware trading agents. In a simulated P2P microgrid with multiple sellers and buyers, the LLM acts as a real-time fairness critic, evaluating each trading episode using two metrics: Fairness-To-Buyer (FTB) and Fairness-Between-Sellers (FBS). These fairness scores are integrated into agent rewards through scheduled lambda-coefficients, forming an adaptive LLM-guided reward shaping loop that replaces brittle, rule-based fairness constraints. A linear lambda ramping curriculum stabilizes training and gradually incorporates fairness with no loss in convergence. Agents are trained using Independent Proximal Policy Optimization (IPPO) and achieve equitable outcomes, fulfilling over 90% of buyer demand, maintaining fair seller margins, and consistently reaching FTB and FBS scores above 0.80. Notably, the framework demonstrates resilience against adversarial behaviors and noise, maintaining stable performance even with corrupted fairness inputs. The training process demonstrates that fairness feedback improves convergence, reduces buyer shortfalls, and narrows profit disparities between sellers. Because the language-based critic requires no hand-crafted fairness features, the framework is structured to extend to settings with larger numbers of prosumers, a direction we examine qualitatively and leave to future work for full validation. FairMarket-RL thus offers an equity-driven approach for autonomous trading in decentralized energy systems.
Should system operators and regulators admit Bitcoin mining to interconnection and demand-response (DR) programs, and if so, under what conditions? This article develops a decision framework that separates three questions often conflated in current debates: whether a facility qualifies operationally as a Large Flexible Load (LFL), whether it should be admitted to participate in grid and market programs, and which additional public-interest safeguards should apply to that participation. The framework treats Bitcoin mining as a candidate flexible load because its computing tasks are highly interruptible, but argues that operational flexibility alone is not sufficient for admission. Participation should also depend on auditable telemetry and baseline design, location-hour environmental disclosure using Marginal Emissions Factors (MEFs), point-of-interconnection screening, and enforceable local safeguards concerning siting and community impacts. The resulting policy logic is staged rather than bundled: recognize LFL status on operational grounds, condition admission on environmental and interconnection readiness, and apply externality safeguards as a separate but enforceable policy layer. The article also emphasizes that these options should not be read as ex ante certifications of safety. Institutional adequacy can only be assessed imperfectly before admission and must be tested through observed performance, monitoring, and enforcement after participation begins. The contribution is therefore not to provide another environmental-footprint estimate, but to show how regulators can translate existing evidence into auditable approval criteria, conditional participation rules, and clear grounds for refusal where risks cannot be credibly managed.
The U.S. electricity sector is operating in an environment characterized by accelerating technological change, expanding regulatory mandates, and heightened institutional complexity. While many recent planning missteps and policy tensions have been attributed to flawed decision-making, this paper argues that suboptimal outcomes more often emerge from the interaction between cognitive limitations, institutional constraints, and political incentives. Drawing on concepts from behavioral economics and decision analysis, the paper develops a framework for understanding four recurring vulnerabilities in electricity policy and planning: inflated expectations, "magic box" thinking, reification of simplified abstractions, and cognitive distortions such as anchoring and optimism bias. Through case studies involving electrification mandates, dispatchable emission-free resource constructs, demand response accreditation, and AI-driven data center load projections, the analysis illustrates how emerging technologies and policy ambitions can outpace technical validation, infrastructure readiness, and governance feasibility. Importantly, many analytically fragile outcomes reflect rational responses to legislative mandates and regulatory constraints rather than simple errors in judgment. The paper introduces "concept validation" as a critical yet underdeveloped discipline in electricity planning, emphasizing the need to test policy and investment assumptions under deep uncertainty. It concludes that strengthening scenario diversity, stress testing, and institutional feasibility assessment can enhance robustness without dampening innovation. By situating cognitive factors within broader political and economic contexts, the paper offers a more balanced framework for improving long-term electricity policy and system performance.
Access to electricity remains limited in much of Sub-Saharan Africa, with significant implications for child survival and well-being. This study investigates the relationship between clean energy transitions and early childhood health across 28 Sub-Saharan African countries from 2000 to 2023. By combining geo-referenced Demographic and Health Surveys (DHS), satellite-derived electrification measures, and national clean energy rollout timelines, we construct a subnational panel to assess the associations between electrification and child health outcomes using fixed effects, staggered difference-in-differences, and threshold-based heterogeneity models. Clean electrification is consistently associated with lower under-five mortality, reduced ARI incidence, and higher immunization coverage, with stronger associations in rural and low-income regions and in settings with higher baseline health system readiness. Mechanism analyses indicate that electrification correlates with improvements in institutional delivery rates, vaccine cold-chain reliability, and reduced dependence on biomass fuels, pathways plausibly linked to child health benefits. Additional patterns suggest indirect links through household asset ownership, media exposure, and agricultural income. These findings highlight the potential health co-benefits of clean energy access and underscore the value of aligning electrification strategies with health system investments. Targeting energy interventions toward infrastructure-poor, health-vulnerable communities may enhance progress toward Sustainable Development Goals 3 and 7 through coordinated energy-health policy design.
This study estimates the short- and long-run elasticities of CO2 with respect to electricity consumption, urbanisation, and income in T & uuml;rkiye over 1990-2020 using an Augmented-ARDL framework. T & uuml;rkiye's fossil-based power mix links higher electricity use to higher emissions. Results indicate that a 1% increase in electricity consumption is associated with a 0.66% rise in CO2 in the long run and 0.51% in the short run. Urbanisation reduces emissions in the short-run (-0.36%), plausibly via densification and efficiency gains, but this effect does not persist in the long run. Income is positively associated with emissions (0.54% long-run; 0.42% short-run), consistent with an energy-intensive growth trajectory. Bounds-type and augmented tests provide strong evidence of cointegration among the variables. Diagnostic checks indicate no residual serial correlation or ARCH effects, approximate normality, and parameter stability (CUSUM/CUSUMSQ within 5% bounds). The findings underscore the need to accelerate the shift toward sustainable electricity, integrate urban planning into climate policy to preserve short-run efficiency gains, and calibrate growth strategies to balance economic objectives with emissions reduction-policy directions that align with Sustainable Development Goal 7 (Affordable and Clean Energy) and support progress toward SDG 13 (Climate Action).
Thailand’s power sector is experiencing rapid growth in distributed energy resources (DERs), variable renewables, and electrified demand, shifting operational challenges—visibility, congestion, voltage control, and balancing interactions—toward the distribution network. However, existing regulatory and institutional arrangements under Thailand’s Enhanced Single Buyer structure are not designed for active distribution-level system operation. This paper synthesizes six interlinked barriers to DSO development: limited grid visibility and hosting-capacity practice, weak alignment between investments in flexibility resources and enabling digital infrastructure, fragmented operational coordination across system levels, insufficient pathways for flexibility service providers (FSPs), inadequate data-sharing and market-facilitation platforms, and context-dependent transition constraints in regulated versus liberalised settings. Drawing on comparative evidence, we propose a phased regulatory and institutional framework for Thailand that clarifies DSO functions and neutrality safeguards, strengthens ICT interoperability, and operationalises coordination, verification, and settlement processes for flexibility procurement. We then discuss policy implications for organisational separation, procedural clarity, and incentive-compatible regulation to enable secure and cost-effective flexibility at scale. These insights aim to support policymakers in designing adaptive and forward-looking regulatory pathways for Thailand’s evolving power system.
Indonesia's heavy dependence on coal continues to challenge its national climate targets and the broader sustainability transition. Small and Medium Enterprises (SMEs) play a pivotal role in driving energy-efficiency innovation, yet limited access to affordable finance constrains their capacity to adopt clean technologies. This Study investigates how green loans enable SME adoption of energy-efficient technologies across Indonesia's key sectors, including agriculture, transportation, and construction. Drawing upon the Technology-Organization-Environment (TOE) framework and the Green Loan Principles (GLP), a structural equation modeling approach was used to analyze the interrelationships among technological, organizational, environmental, and financial factors. The findings reveal that technological factors-particularly relative advantage and compatibility-are the strongest predictors of adoption, while organizational readiness exerts its influence indirectly through GLP. Green loans emerge as a critical mediating mechanism that translates readiness and policy signals into bankable, auditable projects. Sectoral Analysis reveals that while the finance-enabled adoption pathway (TOE -> GLP -> AET) is structurally consistent across sectors, its economic relevance varies according to sector-specific characteristics. business revenue is found to play a contingent moderating role, strengthening the effectiveness of green loans in capital intensive sectors, particularly transportation. These findings contribute theoretically by clarifying the mediating role of green finance in technology adoption and provides clear implications for policymakers and financial institutions seeking to design inclusive green finance schemes that reduce information asymmetry, de-risk SME investments, and accelerate low-carbon transitions across emerging Asian economies.
India’s power sector decarbonization strategy relies on a transition to renewable energy, requiring states, particularly their distribution companies (DISCOMs), to significantly increase renewable energy uptake in the coming years. At the same time, states must continue efforts to expand electricity access. The financial health of DISCOMs is central to achieving both objectives, as their ability to procure renewable energy and expand access depends on their financial viability. However, research on how renewable energy uptake itself affects DISCOM finances, particularly how this relationship varies across states, remains limited. Moreover, the combined effect of increasing renewable energy uptake and expanding electricity access on DISCOM financial health is underexplored.This study addresses this gap by examining the interaction between renewable energy uptake, DISCOM financial health, and electricity access. The analysis focuses on Jharkhand and Rajasthan, two states with persistent financial challenges but contrasting contextual factors such as coal dependency, load profiles, and power purchase agreements. Using a scenario based modeling approach, the study evaluates multiple renewable energy penetration and electricity access scenarios in the medium term. The results show that the financial outcomes of renewable energy integration depend strongly on state specific factors, highlighting the importance of tailoring renewable energy and access policies to local conditions.
Voluntary carbon-free electricity (CFE) procurement has the potential to accelerate electric sector decarbonization, but procurement strategies vary widely, leading to uncertainty about emissions, investments, and costs. This study assesses the system-wide effects of voluntary CFE procurement on U.S. regional power systems using a detailed energy systems model across a range of program designs, eligible technologies, policy environments, and modeling assumptions. Results suggest that hourly matching-where clean electricity procurement aligns with hourly load-combined with new and local generation could maximize emissions reductions from CFE procurement. Emissions impacts vary widely with program design, where hourly matching combined with deliverability and incrementality produces meaningful system COQ reductions, while more flexible designs may yield limited consequential abatement despite similar attributed clean electricity claims. However, regional costs vary significantly, with a CFE cost premium ranging from $11 to 63/MWh nationally across scenarios and $1-130/ MWh across regions, broader than previous estimates. Expanding the eligible technology portfolio to include renewables, nuclear, carbon capture, and energy storage reduces costs, particularly in regions with lower wind and solar resource quality, though variable renewables and battery storage remain the dominant resources in many scenarios. Additionally, we show that the future policy environment strongly influences the effectiveness of voluntary CFE programs, with more stringent emissions policies or subsidies potentially limiting the incremental benefits of procurement. The analysis also quantifies how features of the model framework can shape insights about CFE procurement strategies.
