Search Results (113)

Residential electricity tariff structures in emerging economies are often highly complex, dynamically combining regional climatic variables and multi-tiered price adjustments. In Mexico, despite a preferential scheme designed to mitigate seasonal expenditure fluctuations, baseline energy subsidies frequently fail to protect low-income households due to structural targeting inefficiencies based strictly on regional temperature thresholds rather than socioeconomic status. This study addresses this methodological and regulatory gap by developing the Energy-Economic Impact Index (EEII), a novel mathematical and heuristic framework that couples complex Increasing Block Tariffs (IBT) architecture with localized household income dynamics at the state level. The proposed methodology was comprehensively validated using synchronized biennial empirical datasets from all 32 Mexican states, combining Federal Electricity Commission (CFE) billing data and National Surveys of Household Income and Expenditures (ENIGH) spanning the 2018–2024 period. Quantitative results reveal a severe, non-linear escalation of the financial energy burden across the territory, demonstrating that rising residential electricity costs significantly outpaced domestic income growth trajectories. Notably, households situated within high-temperature geographic regimes (Tariffs 1D, 1E, and 1F) exhibited the most critical economic vulnerability, with the calculated energy cost impact absorbing up to 14.90% of the real monthly household income in 2024. Ultimately, the EEII framework proves to be a robust predictive and decision-support tool for energy policy planners aiming to optimize fiscal subsidy allocation, reduce energy poverty gaps, and mitigate socioeconomic risks in transition economies. Full article

Counting electricity connections is easy. Understanding what those connections actually do for people is harder—and more important. This study examines how a 450 kWp Smart Grid Hybrid Microgrid on Semau Island, East Nusa Tenggara, Indonesia, shaped the daily lives and economic futures of a community in one of the country’s most geographically isolated 3T territories (Frontier, Outermost, Underdeveloped), using a sequential explanatory mixed-methods design (SEM-AMOS, n = 123; key informant interviews, n = 4)—and we find that forty percent of households have shifted from passive consumption to productive agricultural use within five years of grid connection, a rate that challenges common assumptions about rural electrification in eastern Indonesia. The data also reveal a troubling pattern at the heart of Indonesia’s subsidy architecture: the 450 VA tier, which absorbs the highest per-kWh State Budget subsidy (IDR 10,518/kWh; 96.2% of Cost of Supply), is associated with the weakest welfare returns. Meanwhile, an estimated IDR 1.87 billion per year in lost capacity—a figure we term the Governance Maintenance Loss (GML)—is linked to governance shortfalls rather than hardware failure. SEM-AMOS results (χ²/df = 1.613; RMSEA = 0.049; CFI = 0.973; TLI = 0.983; SRMR = 0.043) indicate that, among the constructs examined, Energy Diversification Policy shows the strongest association with community welfare (β = 0.718, p < 0.001)—more so than the physical infrastructure itself. In response, this study proposes three governance instruments: the MIDEK framework, a Knowledge Transfer Mandate (KTM), and a Productive Energy Tariff (PET). Together, these tools offer a replicable, low-cost pathway for Indonesia’s 1200 planned island installations under Presidential Regulation No. 112/2022—one that is simultaneously revenue-positive for PLN, budget-positive for the State, and welfare-positive for the communities these systems are meant to serve. Full article

Against the global backdrop of carbon peaking and carbon neutrality goals, renewable energy subsidy policies worldwide are shifting from universal, tariff-based schemes toward targeted, market-oriented mechanisms. However, existing research remains divided on the incentive effects of subsidies on firm investment and the risk of resource misallocation, and few studies have established a clear micro-macro linkage between firm-level subsidy receipts and regional employment and growth outcomes. Taking China’s 2016 renewable energy subsidy reform—characterized by competitive project bidding and green certificate trading—as a quasi-natural experiment, this study constructs a two-layer panel dataset covering 286 A-share listed renewable energy firms (2010–2023, 2412 firm-year observations) and 30 provincial-level regions in China (2010–2023, 420 region-year observations). Employing difference-in-differences (DID), triple difference-in-differences (DDD), mediation effect models, and threshold regression, combined with instrumental variables and placebo tests to address endogeneity, we empirically examine how subsidy policies transmit from firm behavior to regional employment and economic growth. The results indicate that the 2016 reform significantly boosted regional employment (elasticity = 0.035, p < 0.01) and economic growth (elasticity = 0.031, p < 0.05) in treated provinces. At the firm level, subsidy intensity exhibits an inverted U-shaped relationship with investment efficiency, with an estimated inflection point at 8.3% of operating revenue within the sample. Mechanism analysis shows that easing financing constraints, stimulating technological innovation, and reducing operational risk serve as core transmission channels, with the strongest contribution from financing constraint alleviation. Heterogeneity analysis further finds larger effects for private firms, high-tech enterprises, and coastal regions. This study develops a nonlinear analytical framework of “subsidy intensity–firm behavior–regional outcomes”, identifies context-specific boundaries of subsidy effectiveness, and provides integrated micro-macro empirical evidence for optimizing subsidy policies and advancing the global energy transition. Full article

Uzbekistan has rapidly expanded solar photovoltaic (PV) capacity as part of its transition toward a low-carbon energy system, supported by guaranteed purchase tariffs and an evolving regulatory framework. This paper evaluates the economic feasibility of solar PV investments in Uzbekistan through a combined ex post and ex ante analysis, focusing on both commercial-scale rooftop installations and a proposed large utility-scale floating photovoltaic (FPV) project. Ex post performance data from four commercial rooftop PV systems in Tashkent (20–304 kW) over the period 2024–2025 are analyzed using lifecycle investment appraisal metrics, including the Equivalent Uniform Annual Cost (EUAC)/LCOE framework, Net Present Value (NPV), and Internal Rate of Return (IRR), to benchmark real operating outcomes against modeled expectations. These results are subsequently used to calibrate ex ante simulations for a 491 MW FPV installation planned on the Sardoba reservoir, assessed using RETScreen Expert and a bespoke three-statement financial model incorporating detailed tax, financing, and operational assumptions. The findings indicate that commercial-scale rooftop PV projects in Tashkent operate close to the financial break-even point, with EUAC-based levelized costs of energy broadly aligned with current guaranteed purchase prices for PV electricity, resulting in near-zero NPVs. In contrast, the large-scale Sardoba FPV project demonstrates moderate but positive financial viability, with nominal IRRs of approximately 14–16% and payback periods under ten years at the prevailing tariff levels. Importantly, the monetized value of environmental externalities—primarily avoided CO₂ emissions—amounts to roughly from one quarter to a third of initial capital expenditure, materially enhancing the project’s overall economic value. The results suggest that while large-scale solar projects in Uzbekistan generate limited private financial rents, their societal benefits justify continued policy support, stopping short of additional direct subsidy disbursements but conducive to lower cost-of-capital measures. Full article

This study proposes a comprehensive techno-economic methodology to assess the economic viability and optimal sizing of grid-connected residential photovoltaic (PV) self-consumption systems without storage in emerging economies. The model uses net present value (NPV) as the optimization criterion and estimates internal rate of return (IRR) and discounted payback time (DPBT) as complementary profitability indicators. It integrates hourly PV generation, synthesized hourly demand profiles, local tariff structures, surplus-energy remuneration, investment and operating costs, inflation, performance losses, and discount-rate assumptions, while explicitly accounting for context-specific limitations related to data availability, storage-free operation, and financing assumptions. The methodology is applied to 30 Colombian residential scenarios, covering five cities and six socioeconomic strata, and is complemented with a replicability case in Jaén, Spain. In Colombia, PV self-consumption is economically viable in all cases, but profitability is highly uneven: maximized NPV ranges from 2.8 € in the least favorable low-income case to 2816 € in the best high-income case, IRR ranges from 5.0% to 14.7%, and DPBT ranges from 8 to 24 years. From an energy-justice perspective, tariff subsidies improve affordability but may reduce PV attractiveness for low-income users, highlighting the need for capital grants, low-interest loans, or community solar schemes. Full article

Climate change is intensifying hydroclimatic extremes and agricultural water scarcity, sharpening trade-offs among yield stability, water saving, and farm incomes in major grain regions. Existing studies often optimise cropping patterns or irrigation schedules separately, seldom embedding yield robustness and policy instruments in one decision framework. We propose an integrated Machine-learning–System-dynamics–Non-dominated-sorting-genetic-algorithm-II (ML–SD–NSGA-II) framework linking long-horizon meteorological scenario generation, crop–water–economy feedback and multi-objective optimisation of crop areas and irrigation depths. ML models generate daily climate sequences to drive an SD model of soil moisture, yield formation, basin-scale allocable water, and farm returns; NSGA-II searches Pareto-optimal strategies that maximise profit and irrigation water productivity while minimising yield deviation. Applied to a rice–wheat irrigation system in the middle Yangtze River Basin, knee-point solutions lift irrigation water productivity by about 14%, maintain near-baseline profits, and reduce yield deviation. Scenario tests with block tariffs, quota-based subsidies, and extreme drought show pricing mainly curbs low-value water use in normal years, while under drought, physical scarcity dominates and economic tools offer limited buffering. This reveals the existence of a scarcity-regime threshold beyond which economic instruments become second-order relative to binding biophysical constraints. The framework supports transparent ex ante testing of tariff–subsidy packages for irrigation governance and adaptation. Full article

The energy transition represents a complex, multi-level system subject to profound uncertainty and recurrent shocks. Current policy design approaches predominantly rely on static optimization frameworks (centralized, calculative models that presume stable conditions and predictable technological trajectories). Yet evidence from the 2021–2023 energy crisis in Europe, coupled with structural challenges in market liberalization and renewable integration, demonstrates persistent challenges in policy implementation. Price interventions affect competitive dynamics; subsidies influence technology selection; capacity mechanisms create coordination tensions; and rigid tariff structures create misalignments with evolving grid needs. This paper argues that these recurrent policy tensions stem not from implementation gaps, but from an inadequate theoretical foundation: the treatment of energy systems as optimizable rather than as complex, adaptive systems operating under Knight–Mises uncertainty and Huerta de Soto dynamic efficiency. This work explores an alternative framework grounded in dynamic efficiency, complex–uncertain systems, decentralized incentives, and adaptive governance (international–domestic, public–private, etc.). This review uses the theoretical and methodological framework of the Heterodox Synthesis, an alternative to the Neoclassical Synthesis. There is a reinterpretation of some insights from Knight and Mises (uncertainty), Hayek (distributed knowledge), Huerta de Soto (dynamic efficiency) and contemporary complexity economics into operational criteria applicable to energy policy design: (1) robustness to deep uncertainty; (2) preservation of price signals and risk-bearing mechanisms; (3) alignment of incentives across distributed actors; (4) institutional adaptability; and (5) minimization of ex post policy corrections. Through illustrative application to four critical policy instruments (price caps, renewable subsidies, capacity mechanisms, and network tariff design), it is shown how this framework identifies systematic tensions and consequences that conventional analysis overlooks. The contribution is exploratory in a bootstrap way: theoretical, by integrating classical and contemporary economics into energy governance; methodological, by operationalizing dynamic efficiency into evaluable criteria distinct from existing adaptive governance frameworks; and sectorial, by providing policymakers and regulators with diagnostic tools for assessing design robustness in conditions of deep uncertainty and rapid transition. According to this review, improved energy policy design under uncertainty is not achieved through more sophisticated optimization (in a calculative way), but through institutional architectures that preserve creative and adaptive learning, maintain distributed decision-making capacity, and remain functional when assumptions prove incorrect or not well-known. Full article

In the context of advancing two pivotal national commitments, namely the “Dual Carbon” goals and the common prosperity strategy, energy policy formulation must move beyond purely economic or environmental considerations and adopt integrated social welfare assessments. This study develops an optimal dispatch model for a multi-microgrid system that incorporates dynamic cross subsidy and tiered carbon trading. From the perspective of welfare economics, the socioeconomic impacts of the proposed model are then systematically evaluated. First, a unified operational framework is established, combining dynamic electricity tariff cross subsidy with a tiered carbon trading mechanism. Next, a quantitative model for electricity tariff cross subsidy is proposed, and a dynamic subsidy rate linked to renewable energy output is designed to guide electricity consumption behavior. Finally, a comparative simulation is conducted across three scenarios: no subsidy, traditional cross subsidy, and the proposed dynamic cross subsidy. The results demonstrate that the proposed dynamic mechanism reduces system carbon emissions by 17.05% compared to the non-subsidy baseline while significantly optimizing total costs. Full article

This paper investigates the coordination between logistics and policy decisions for electric vehicle (EV) exports under the Belt and Road Initiative. Focusing on the two modes—maritime shipping and the China Railway Express (CR Express)—along with government production subsidies, import tariffs, and service premium, a Stackelberg game model for a cross-border supply chain comprising a domestic manufacturer and an overseas retailer is constructed. The equilibrium outcomes under four scenarios formed by combining subsidy policies and transportation modes (Models NM, NR, GM and GR) are compared theoretically and numerically, with further evaluation of capacity constraints and power structures, as well as the robustness verification of the core findings. Results show that the CR Express mode exhibits a service-driven nonlinear cost pattern, where its service premium amplifies positive market responses. Its appeal to the manufacturer, however, is tightly constrained by fixed cost. Furthermore, government subsidies can overcome this barrier by synergizing with the service premium, turning the CR Express into a relatively advantageous strategy. Moreover, subsidy efficacy is conditional, depending heavily on the service premium level and logistics cost coefficient, leading to a proposed differentiated subsidy framework. This study offers a theoretical basis for corporate logistics strategy and targeted policy design. Full article

Policy instability and regulatory barriers remain key obstacles to the long-term viability of agriphotovoltaics (APV) deployment. The Penthéréaz case in Switzerland provides empirical evidence of how cooperative governance and collective self-consumption can restore project feasibility after subsidy withdrawal. Using a single-case study and process-tracing approach based on cooperative documentation and regulatory records, the analysis explains how Penthéréaz Énergie Photovoltaïque S.A. cooperative (PEP)., initially structured as a subsidy-dependent venture, transitioned into a resilient collective self-consumption network supported by a private micro-grid. Following the withdrawal of federal feed-in tariffs, the project faced major economic risk and responded through decentralized financial restructuring, including community-funded debt at a 2% interest rate. The installation comprises 1180 photovoltaic panels with an installed capacity of 283 kWp, producing approximately 290,000 kWh per year while providing water-tightness and light permeability for agricultural infrastructure. The findings further indicate that operational success contributed to Swiss regulatory adjustments, enabling private distribution networks to cross public roads and secure geographic continuity for local energy sharing. With a reported self-consumption rate of 40% across a diversified user base including agri-food and residential consumers, the case demonstrates the operational value of local load-matching. The findings propose six context-dependent lessons derived from a single case, emphasizing governance capacity, tariff risk management, regulatory adaptability, and demand-oriented system design. Full article

Electric vehicles have strengthened the coupling between transportation systems and power distribution networks, giving rise to new challenges in the coordinated management of traffic flow and charging demand. Monetary incentives, such as tariffs and subsidies, have been widely adopted to influence drivers’ route and charging decisions and to improve system-level performance. This paper proposes a user-centric incentive framework in which a system operator allocates rewards to guide drivers’ behavior, thereby enabling coordinated operation of power–traffic networks. A reward scheme is developed to provide joint subscription-based and path-based incentives that account for drivers’ behavioral responses through a logit choice model for scheme adoption embedded within a traffic assignment model. The resulting interaction is formulated as a bilevel optimization problem, in which a coupled power–traffic system operator determines incentive schemes to achieve system optimality within a given budget constraint, while individual drivers respond by selecting routes and charging strategies to minimize their perceived travel costs. A single-level Karush–Kuhn–Tucker (KKT) reformulation is developed, and linearization techniques are employed to compute the resulting equilibrium, yielding a tractable mixed-integer second-order cone program (MISOCP). Numerical experiments demonstrate the effectiveness of the subscription-based and path-based reward schemes in improving network performance and budget saving. Full article

Industrial deployment of photocatalysis for recalcitrant wastewater treatment remains constrained by economic uncertainty and scale-up limitations. This study first reviews the current technological routes and application status of photocatalytic processes and then addresses the key obstacles through a quantitative techno-economic assessment (TEA) of a full-scale (10,000 m³/d) photocatalytic wastewater treatment plant. A process-level model integrating mass- and energy-balance calculations with equipment sizing was developed for a 280 kW UVA-LED reactor using Pt/TiO₂ as the benchmark catalyst. The framework quantifies capital (CAPEX) and operating (OPEX) expenditures and evaluates the overall economic performance of the photocatalytic treatment system. Sensitivity analysis reveals that the catalyst replacement interval and electricity tariffs are the principal economic bottlenecks, whereas improvements in catalyst performance alone provide limited cost leverage. Furthermore, the analysis indicates that supportive policy mechanisms such as carbon-credit incentives and electricity subsidies could substantially enhance economic feasibility. Overall, this work establishes a comprehensive integrated TEA framework for industrial-scale photocatalytic wastewater treatment, offering actionable design parameters and cost benchmarks to guide future commercialization. Full article

This study presents an integrated ex-post evaluation of a municipal window-retrofit program in Goyang, Republic of Korea (heating-dominated, Dwa). Using field surveys and pre- and post-utility bills for 36 dwellings, mainly pre-2000 low-rise reinforced-concrete buildings, we normalize climate with HDD and CDD and prices with CPI-deflated tariffs to isolate the intrinsic effect of window replacement. Area-normalized indicators ($∆e$, $\eta$, DPB, NPV, AC) were computed. Average annual savings were 30.2 kWh per m² per year ($\eta$ ≈ 16 percent), consisting of 10.6 kWh per m² per year of gas and 19.6 kWh per m² per year of electricity (n = 36). The median discounted payback was 7.0 years. Under a 50 percent subsidy, about 80 percent of projects recovered private investment within 15 years and showed positive NPV with a median of about USD 4944. The electricity-tariff multiplier had the largest influence on cash flows and payback. The median abatement cost was about USD 352 per tCO₂-eq. A portfolio view indicates that prioritizing low-cost cases maximizes total abatement, and that higher-cost cases merit design or cost review. Using the first post-retrofit year 2023, portfolio abatement is about 623 tCO₂-eq per year. The framework jointly normalizes climate and price effects and yields policy-relevant estimates for heating-dominated contexts. Full article

The United Nations Sustainable Development Goals (SDGs) set the criteria for sustainable economic development. These goals encompass four dimensions, including social, human, economic, and environment, of which the last two goals (i.e., economic and environment) were contemplated in this study. A case study for Corner Brook, a middle-sized city, located in the western region of the province of Newfoundland and Labrador, Canada, revealed that the current urban water use pricing mechanism is not matched with the SDGs, which reflects impediments to the city’s achievements to become a sustainable economic development community. Residents are billed a fixed rate for water use rather than a tiered or usage-based rate. This is not a resilient policy, as it fails to conserve water resources, ultimately leading to wasting freshwater produce, inhibiting economic growth, creating social exclusion, and degrading natural resources. We recommend changing the current flat-rate based water billing mechanism to either increasing block tariffs or two-part tariffs, adjusted by seasonal rates; issuing governmental policies, such as rebates, subsidies, and lower property taxes to entice residents’ willingness-to-install water meters on their premises; encouraging provisions such as using rain barrels to help cut down water consumption; and raising public knowledge through social media on how high per capita water use is in the region, including how much it costs to install water meters. These recommendations will also help provincial and municipal policymakers pursue the SDGs. Full article

The clean energy transition of the power sector is essential for achieving sustainable development. However, an important question is how, and to what extent, government subsidy policies contribute to this transition. Using county-level data on wind and photovoltaic capacity and power generation in China, we demonstrate that Feed-in Tariff (FIT) subsidies have substantially increased both the installed capacity and power generation of wind and PV energy. Specifically, for every 10% increase in FIT subsidies, wind power installed capacity increases by 24.33%, and power generation increases by 19.33%. Similarly, PV power installed capacity increases by 19.80%, and power generation increases by 15.50%. Further analysis reveals that FIT incentivizes market participants to invest in wind and PV power generation by increasing the likelihood of profitability for renewable energy enterprises. However, fixed FIT subsidies, probably due to over-incentivization, transmission constraints, and the intermittent nature of renewable energy, cause a decline in the capacity utilization rate of wind and PV power. Additionally, our findings highlight that tailoring FIT policies to local resource endowments and improving transmission infrastructure can enhance policy effectiveness and support the clean energy transition. Full article