Energy Economics最新文献_第4页

Economic emission dispatching strategy considering dynamic parameter effects: A novel approach based on projection neural networks and deep learning 考虑动态参数影响的经济排放调度策略：基于投影神经网络和深度学习的新方法

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-24 DOI: 10.1016/j.eneco.2025.109104

Xueying Liu, You Zhao, Xing He

The economic emission dispatch (EED) problem is influenced by dynamic parameters such as power demand and climatic factors affecting renewable energy (RES) generation, which adds to the complexity of the dispatch process. Constrained by the serial iterative computing architecture, conventional optimization algorithms often face the challenges such as long computation time and computational inefficiency caused by repeated solving when dealing with EED involving continuous changes in dynamic parameters. To address the problem, this paper combines projection neural network (PNN) and deep learning to cope with the effect of dynamic parameters on the EED. First, a deep PNN (DPNN) is proposed by embedding PNN in deep learning. Then, the dynamic parameters in the EED are taken as input variables to the DPNN. Compared to PNN, DPNN do not require iterations and can respond immediately to dynamic parameter changes to directly provide predicted solutions for EED, which allows the DPNN reduce computation time and improve computational efficiency. Simulation results show that compared with PNN and convex solvers, DPNN can significantly reduce the computation time with good computational performance and can be adapted to EED problems containing dynamic parameters.

经济排放调度问题受电力需求和影响可再生能源发电的气候因素等动态参数的影响，增加了调度过程的复杂性。传统优化算法在处理动态参数连续变化的动态环境时，受串行迭代计算架构的限制，往往面临计算时间长、反复求解效率低的挑战。为了解决这一问题，本文将投影神经网络（PNN）与深度学习相结合，以应对动态参数对EED的影响。首先，通过将PNN嵌入到深度学习中，提出了一种深度PNN （DPNN）。然后，将EED中的动态参数作为DPNN的输入变量。与PNN相比，DPNN不需要迭代，可以立即响应动态参数变化，直接为EED提供预测解，从而减少了计算时间，提高了计算效率。仿真结果表明，与PNN和凸求解器相比，DPNN能显著缩短计算时间，具有良好的计算性能，能够适应包含动态参数的EED问题。

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引用次数: 0

Firm climate investment: A glass half-full 坚定的气候投资：半满的杯子

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109097

Prachi Srivastava , Nicholas Bloom , Philip Bunn , Paul Mizen , Gregory Thwaites , Ivan Yotzov

The green transition will require large investments from firms, yet little is known about the scale and drivers of climate-related capital expenditure across the UK economy. To address this gap, we draw on a large, representative survey of UK firms to quantify how businesses expect to adjust their medium-term investment in response to climate change. Over 2023-2026, firms expect climate-related investments to account for 5.5% of total capital expenditure. These investments will be driven by larger firms as well as those in more energy-intensive sectors. The main channels for these investments are switching to green energy sources and improving energy efficiency, and firms plan to finance them primarily using internal cash reserves. Overall, although firms are expecting to invest more resources in adapting to climate change, under reasonable assumptions, these investments are still not sufficient to meet the estimated targets implied by the UK Net Zero Pathway.

绿色转型将需要企业的大量投资，但人们对英国经济中与气候相关的资本支出的规模和驱动因素知之甚少。为了解决这一差距，我们对英国公司进行了一项具有代表性的大型调查，以量化企业预计如何调整其中期投资以应对气候变化。在2023-2026年期间，企业预计气候相关投资将占总资本支出的5.5%。这些投资将由大型企业以及能源密集型行业的企业推动。这些投资的主要渠道是转向绿色能源和提高能源效率，企业计划主要利用内部现金储备为这些投资提供资金。总体而言，尽管企业期望在适应气候变化方面投入更多资源，但在合理的假设下，这些投资仍然不足以满足英国净零路径所隐含的估计目标。

引用次数: 0

Green bubbles: A four-stage paradigm for detection and propagation 绿色气泡：检测和传播的四阶段范式

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109095

Gian Luca Vriz , Luigi Grossi

Climate change has emerged as a significant global concern that is attracting increasing attention worldwide. Although green bubbles may be examined through a social bubble hypothesis, it is essential not to neglect a “Climate Minsky” moment triggered by sudden asset price changes. The significant increase in green investments highlights the urgent need for a comprehensive understanding of these market dynamics. Therefore, the present paper introduces a novel paradigm for studying such phenomena.

Focusing on the renewable energy sector, change point detection models are employed to identify green bubbles within time series data. Furthermore, search volume indexes and social factors are incorporated into established econometric models to reveal potential implications for the financial system. Inspired by Joseph Schumpeter’s perspectives on business cycles, this study recognizes green bubbles as a “necessary evil” for facilitating a successful transition towards a more sustainable future.

气候变化已成为全球关注的重大问题，在世界范围内引起越来越多的关注。虽然绿色泡沫可以通过社会泡沫假说来检验，但重要的是不要忽视由资产价格突然变化引发的“气候明斯基”时刻。绿色投资的显著增长凸显了全面了解这些市场动态的迫切需要。因此，本文引入了一种研究此类现象的新范式。以可再生能源领域为研究对象，采用变化点检测模型识别时间序列数据中的绿色气泡。此外，将搜索量指数和社会因素纳入已建立的计量经济模型，以揭示对金融体系的潜在影响。受约瑟夫·熊彼特（Joseph Schumpeter）商业周期观点的启发，这项研究认为绿色泡沫是促进向更可持续的未来成功过渡的“必要之恶”。

引用次数: 0

Energy bill pressure stimulates investment intentions primarily for high-socioeconomic households in Australia 能源账单压力主要刺激了澳大利亚高社会经济家庭的投资意愿

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-23 DOI: 10.1016/j.eneco.2025.109111

Rohan Best , Madeline Taylor , Raúl Gutiérrez-Alvarez , David Parra

Energy bill pressure likely motivates household investment intentions, but influences could vary based on socioeconomic characteristics. A first possibility is that low-income households, who are more likely to be affected by energy bill pressure, may be more motivated than high-income households to make energy investments. A second possibility is that low-income households may be less likely to intend to invest due to barriers such as perceived unaffordability. We use Australian household survey data from 2017 to 2023 to assess influences of energy bill pressure on intentions for four investments: home batteries, electric vehicles, solar photovoltaic panels, and solar hot water systems. While the first possibility above is commonly mentioned, we instead find that energy bill pressure has a consistently lower influence on intentions for investments by households with a lower socioeconomic status. This finding is consistent across the four investment types. It is also consistent across a range of socioeconomic variables. Our results suggest that policy design should change to give disadvantaged households enhanced opportunities for investments while being responsive to variances in state and territory policies. Our results especially align with policy enhancements helping renters and households with low levels of assets.

能源账单压力可能会激发家庭投资意愿，但影响可能因社会经济特征而异。第一种可能性是，低收入家庭更有可能受到能源账单压力的影响，他们可能比高收入家庭更有动力进行能源投资。第二种可能性是，低收入家庭可能不太可能打算投资，因为他们觉得负担不起等障碍。我们使用2017年至2023年的澳大利亚家庭调查数据来评估能源账单压力对四项投资意向的影响：家用电池、电动汽车、太阳能光伏电池板和太阳能热水系统。虽然第一种可能性通常被提及，但我们发现能源账单压力对社会经济地位较低的家庭投资意愿的影响一直较低。这一发现在四种投资类型中是一致的。这在一系列社会经济变量中也是一致的。我们的研究结果表明，政策设计应该改变，在响应州和地区政策差异的同时，为弱势家庭提供更多的投资机会。我们的结果与帮助租房者和低资产水平家庭的政策加强相一致。

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引用次数: 0

Robust functional principal component analysis for detecting anomalous behaviors in electricity markets 电力市场异常行为检测的鲁棒功能主成分分析

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-22 DOI: 10.1016/j.eneco.2025.109091

Mara Sabina Bernardi , Andrea Cerasa , Luigi Grossi , Fany Nan

This paper introduces a novel methodological framework to detect potentially manipulative behaviors in deregulated electricity markets using robust statistical tools. The work focuses on identifying outlying bidding patterns in daily auction microdata by modeling the shape of supply curves, rather than relying solely on price data, to better capture strategic market behavior. The approach is grounded in robust Functional Principal Component Analysis (FPCA), which enables the detection of anomalies in supply curve shapes while being resilient to outliers. A key innovation lies in applying the skewness-adjusted boxplot of Hubert and Vandervieren (2008) to the residuals from robust FPCA, enhancing sensitivity to asymmetric and extreme behaviors. Crucially, it is shown that the anomalies detected via robust FPCA differ significantly from those identified by classical outlier detection methods applied directly to price series, as the suggested method captures deviations in the underlying strategic behavior of market participants that are reflected in the structure of the supply curves, not necessarily in prices. Applied to the Italian day-ahead market, the method detects supply-curve anomalies that differ substantially from those identified by classical price-based techniques. A comparison with the LTSts and rolling-window filtering approaches confirms the distinct contribution of the proposed method, which identifies a complementary set of suspicious events potentially linked to strategic bidding behavior. The findings provide new tools for regulators to support market integrity and ensure compliance with transparency regulations such as the Regulation on Wholesale Energy Market Integrity and Transparency (REMIT).

本文介绍了一种新的方法框架，利用稳健的统计工具来检测放松管制的电力市场中潜在的操纵行为。这项工作的重点是通过对供给曲线的形状建模来识别日常拍卖微观数据中的外围竞标模式，而不是仅仅依赖价格数据，以更好地捕捉战略市场行为。该方法以强大的功能主成分分析（FPCA）为基础，可以检测供应曲线形状中的异常，同时对异常值具有弹性。一个关键的创新在于将偏度调整的箱线图应用于鲁棒FPCA的残差，提高了对不对称和极端行为的灵敏度。至关重要的是，研究表明，通过稳健的FPCA检测到的异常与直接应用于价格序列的经典离群值检测方法发现的异常有很大不同，因为建议的方法捕获了反映在供给曲线结构中的市场参与者潜在战略行为的偏差，而不一定反映在价格中。将该方法应用于意大利日前市场，可以发现与传统基于价格的技术所识别的供应曲线异常有很大不同。与ltst和滚动窗口过滤方法的比较证实了所提出方法的独特贡献，该方法识别了一组互补的可疑事件，这些事件可能与战略投标行为有关。研究结果为监管机构提供了新的工具，以支持市场诚信，并确保遵守《批发能源市场诚信和透明度条例》（REMIT）等透明度法规。

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引用次数: 0

Carbon price volatility in the New Zealand Emission Trading Scheme 新西兰排放交易计划中的碳价格波动

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-22 DOI: 10.1016/j.eneco.2025.109107

Yudou Yang, Le Wen, Basil Sharp, Sholeh Maani

The design of an emission trading scheme (ETS) critically influences its efficacy in reducing carbon emissions. This study enhances the international discourse by analyzing carbon price volatility in the New Zealand Emission Trading Scheme (NZ ETS), a system distinct for its greenhouse gas emissions targets, direct trade of forestry entitlements by forestry participants in the secondary market, and the allowance for unlimited surrender of these entitlements to meet emission obligations. Utilizing daily time series data from 1 July 2010 to 31 December 2022, we apply ARIMA (p, d, q)-EGARCH (m, n)-X models to evaluate the effects of supply-side, demand-side, and regulatory factors on carbon price volatility in the NZ ETS. The findings reveal: (1) Entitlements exert significant long-term effects on volatility, initially positive due to increased supply followed by negative impacts, consistent with mean reversion theory; (2) Demand-side factors influence carbon price volatility only in the short term due to the stable demand for allowances; (3) Successful auctions and policy announcements related to the supply and demand of tradeable units significantly affect volatility; and (4) Regulatory adjustments to entitlement supply notably alter price dynamics in the NZ ETS. These insights assist policymakers in managing ETSs with substantial potential supplies of carbon credits, helping mitigate volatility risks. The evidence-based conclusions also serve as a valuable reference for Southeast Asian countries and those with abundant forest resources establishing or operating ETSs to meet their climate goals.

碳排放交易机制（ETS）的设计对其减少碳排放的效果有着至关重要的影响。本研究通过分析新西兰排放交易计划（NZ ETS）的碳价格波动，增强了国际话语权。新西兰排放交易计划（NZ ETS）是一个独特的体系，其温室气体排放目标、林业参与者在二级市场上的林业权利直接交易，以及为履行排放义务而无限放弃这些权利的许可。利用2010年7月1日至2022年12月31日的每日时间序列数据，我们应用ARIMA (p, d, q)-EGARCH (m, n)-X模型来评估供给侧、需求侧和监管因素对新西兰碳排放交易体系碳价格波动的影响。结果表明：(1)应享权益对波动性具有显著的长期影响，最初是由于供给增加而产生的正影响，随后是负影响，符合均值回归理论；(2)由于配额需求稳定，需求侧因素仅在短期内影响碳价格波动；(3)与可交易单位供需相关的成功拍卖和政策公告显著影响波动性；(4)对权利供应的监管调整显著改变了新西兰排放交易体系的价格动态。这些见解有助于政策制定者管理具有大量潜在碳信用供应的碳排放交易体系，帮助降低波动性风险。基于证据的结论也为东南亚国家和森林资源丰富的国家建立或运营碳排放交易体系以实现其气候目标提供了有价值的参考。

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引用次数: 0

Complexity analysis of automotive supply chains considering online reputation under dual policies 双重政策下考虑网络声誉的汽车供应链复杂性分析

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-20 DOI: 10.1016/j.eneco.2025.109105

Xiaobin Wang , Abudureheman Kadeer , Huanying He

Facing dual pressures from sluggish consumer demand and the “dual‑carbon” goals, this study constructs a synergistic policy framework that integrates carbon quota trading and trade-in subsidies, while innovatively incorporating the dynamic effects of online reputation. Based on game theory and complex systems theory, we establish a manufacturer-led Stackelberg game model and a multi-period dynamic recursive model to unravel the coupling mechanisms through which policies and digital reputation influence supply chain decision-making. Our findings reveal that differentiated pricing strategies are a key driver of complex system dynamics: when traditional fuel vehicles (TFV) adopt conservative pricing

(v_{1} < 0.02)

while new energy electric vehicles (NEEV) implement aggressive strategies

(v_{3} > 0.16)

, the system exhibits asymmetric profit oscillations, with the Largest Lyapunov Exponent of 0.48, and the volatility of NEEV direct sales prices far exceeds that of retail channels. To address this, we propose a time-delayed feedback control method, which effectively suppresses chaotic phenomena and enhances the robustness of the supply chain system. These findings provide crucial theoretical foundation and practical insights for policy coordination, dynamic pricing, and stability management in automotive supply chains under the dual‑carbon targets.

面对消费者需求疲软和“双碳”目标的双重压力，本研究构建了碳配额交易与以旧换新补贴相结合的协同政策框架，并创新地纳入了网络声誉的动态效应。基于博弈论和复杂系统理论，建立了制造商主导的Stackelberg博弈模型和多周期动态递归模型，揭示了政策和数字声誉影响供应链决策的耦合机制。研究结果表明，差异化定价策略是复杂系统动力学的关键驱动因素：当传统燃油车（TFV）采用保守定价v1<；0.02，而新能源电动汽车（NEEV）采用激进定价v1& gt；0.16时，系统呈现非对称利润波动，最大Lyapunov指数为0.48，且新能源电动汽车直销价格的波动幅度远远超过零售渠道。为了解决这一问题，我们提出了一种时滞反馈控制方法，有效地抑制了混沌现象，增强了供应链系统的鲁棒性。这些发现为双碳目标下汽车供应链的政策协调、动态定价和稳定性管理提供了重要的理论基础和实践见解。

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引用次数: 0

Distributional impacts of heterogenous carbon prices in the EU 欧盟异质性碳价格的分布影响

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-18 DOI: 10.1016/j.eneco.2025.109102

Magnus Merkle , Geoffroy Dolphin

We analyse the impact of carbon price heterogeneity on households in the EU from 2010 to 2020 using a novel dataset that combines carbon pricing policies with household budget survey data and a global multiregional input-output framework. Accounting for both heterogeneity in carbon pricing across emission sources and the indirect effects from inter-industry linkages, we obtain two key findings. First, due to incomplete carbon pricing coverage, household burdens have been lower than previously estimated. Second, carbon pricing incidence across income groups differs not only due to varying carbon intensities of demand but also due to differing expenditure shares on products that benefit from exemptions. In the majority of EU countries, low-income households have on average paid higher prices for the carbon embodied in their consumption than high-income households. Closing the carbon pricing gaps, particularly with regard to emissions embodied in imports, can help equalise burdens.

我们使用一个新的数据集，将碳定价政策与家庭预算调查数据和全球多区域投入产出框架相结合，分析了2010年至2020年欧盟碳价格异质性对家庭的影响。考虑到不同排放源间碳定价的异质性和行业间联系的间接影响，我们得到了两个关键发现。首先，由于碳定价覆盖范围不完整，家庭负担低于之前的估计。其次，不同收入群体的碳定价发生率不同，不仅是因为需求的碳强度不同，还因为受益于豁免的产品的支出份额不同。在大多数欧盟国家，平均而言，低收入家庭为其消费中包含的碳支付的价格高于高收入家庭。缩小碳定价差距，特别是在进口碳排放方面的差距，有助于平衡负担。

引用次数: 0

From synergy to spread: How environmental regulation is helping Chinese firms achieve low-carbon expansion — and take their supply chains with them 从协同到传播：环境监管如何帮助中国企业实现低碳扩张——并带动其供应链

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-18 DOI: 10.1016/j.eneco.2025.109103

An Pan , Puyu Mi , Xunpeng Shi

The synergy between carbon emission reduction and green expansion (CERGE) serves as a strategic orientation for firms to achieve green transformation. As environmental regulations are increasingly employed to promote such green growth, an important question arises as to how these policies can foster CERGE synergy—particularly by extending their influence from large enterprises to the vast number of smaller firms through supply chain linkages. This study aims to examine how the T10000P, as a command-and-control environmental regulation, influences the synergy between CERGE in the context of China's dual carbon goals and green transition. Using a sample of China's A-share listed companies from 2008 to 2020, this paper examines the impact of the top 10,000 enterprise energy saving program (T10000P) on the synergy between CERGE, measured through a coupling coordination model and assessed with a difference-in-differences approach. Results show that T10000P significantly enhances firms' synergy between CERGE, with stronger effects observed in high-tech and non-heavy-pollution industries. Financing constraints negatively moderate this impact, while alleviation of such constraints strengthens the synergy. Additionally, the supply chain spillover effect of T10000P is asymmetric: upstream firms' participation significantly improves downstream firms' synergy between CERGE, whereas downstream participation does not significantly affect upstream firms. This one-way spillover effect is more pronounced when upstream firms have greater bargaining power and closer ties with downstream firms. The findings provide valuable insights for leveraging key enterprises' leading role in supply chains and optimizing environmental regulations to promote industrial green transformation and sustainable development.

碳减排与绿色扩张的协同效应是企业实现绿色转型的战略取向。随着环境法规越来越多地被用于促进这种绿色增长，一个重要的问题出现了，即这些政策如何能够促进ge的协同作用——特别是通过供应链联系将其影响力从大企业扩展到大量的小公司。本研究旨在探讨在中国双碳目标和绿色转型背景下，T10000P作为一种命令与控制的环境调控如何影响ge的协同效应。本文以2008 - 2020年中国a股上市公司为样本，采用耦合协调模型和差中差法，考察了企业节能项目10000强（T10000P）对企业节能协同效应的影响。结果表明，T10000P显著增强了企业间的协同效应，且在高技术产业和非重污染产业的协同效应更强。融资限制对这种影响起到消极的缓和作用，而这种限制的缓解则加强了协同作用。此外，T10000P的供应链溢出效应是不对称的：上游企业的参与显著提高了下游企业在ge之间的协同效应，而下游企业的参与对上游企业的协同效应没有显著影响。当上游企业的议价能力更强，与下游企业的联系更紧密时，这种单向溢出效应更为明显。研究结果为发挥重点企业在供应链中的主导作用，优化环境法规，促进工业绿色转型和可持续发展提供了有价值的见解。

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引用次数: 0

The economics of negative price phenomenon in renewable-integrated electricity markets 可再生整合电力市场负价格现象的经济学

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics

Pub Date : 2025-12-17 DOI: 10.1016/j.eneco.2025.109086

Nima Rafizadeh

Understanding how renewable energy integration affects electricity market efficiency and price formation is an important challenge in energy economics and environmental policy. Negative electricity prices, where generators pay to produce power, now occur with increasing frequency across wholesale markets, yet their economic drivers require better understanding. This paper addresses this gap by developing a theoretical framework linking generator behavior to market outcomes, then testing it empirically using over 14 million observations from New York’s wholesale markets (2010–2022). The theoretical analysis demonstrates that negative prices can achieve welfare-maximizing allocations under operational constraints and production subsidies. The empirical analysis, using binary response and count data models with high-frequency data, identifies a clear hierarchy of drivers: renewable energy integration emerges as primary, with solar energy reducing negative price occurrences while wind energy increases them. Weather conditions rank second in importance, while grid constraints show limited influence, contrary to policy focus on transmission expansion. These findings can inform policy discussions by suggesting that rather than suppressing negative prices through regulatory constraints, policymakers should preserve these efficient price signals while prioritizing technology-specific renewable policies and weather-responsive mechanisms over transmission expansion to enhance investment signals and market stability.

了解可再生能源整合如何影响电力市场效率和价格形成是能源经济学和环境政策的一个重要挑战。负电价（发电商为发电付费）现在在批发市场越来越频繁地出现，但其经济驱动因素需要更好地理解。本文通过建立一个将发电机行为与市场结果联系起来的理论框架来解决这一差距，然后使用来自纽约批发市场（2010-2022）的1400多万次观察结果对其进行实证检验。理论分析表明，在经营约束和生产补贴条件下，负价格可以实现福利最大化的分配。实证分析使用二元响应和高频数据计数数据模型，确定了驱动因素的明确层次：可再生能源整合成为主要因素，太阳能减少了负价格的发生，而风能增加了负价格的发生。天气条件的重要性排在第二位，而电网约束的影响有限，这与政策关注的输电扩张相反。这些发现可以为政策讨论提供信息，建议政策制定者不应通过监管约束来抑制负价格，而应保留这些有效的价格信号，同时优先考虑针对技术的可再生能源政策和天气响应机制，而不是输电扩张，以增强投资信号和市场稳定。

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引用次数: 0