Economic Energy Efficiency Research Articles

A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices

The advancement of hydrogen technology and rising environmental concerns have shifted research toward renewable energy for green hydrogen production. This study introduces a novel tri-level transaction methodology for microgrid clusters, addressing uncertainties and price fluctuations in hydrogen. We establish a comprehensive microgrid topology with distributed power generation and hydrogen production facilities. A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. Additionally, we propose a tri-level game-theoretic framework for analyzing stakeholder interactions in microgrid clusters, incorporating supply–demand dynamics and a master–slave structure for microgrids and users. A distributed algorithm, “KKT & supply-demand ratio”, solves large-scale optimization problems by integrating Karush–Kuhn–Tucker conditions with a heuristic approach. Our simulations validate the methodology, demonstrating that accounting for uncertainties and dynamic hydrogen prices enhances renewable energy use and economic efficiency, optimizing social welfare for operators and economic benefits for microgrids and users.

Unraveling the environmental Kuznets curve: The influence of economic diversity, energy efficiency, and industrial dynamics on carbon emissions in developing economies

A new path of economic development among emerging and developing nations has a distinct impact on the environment than seen in the past. The current study attempts to examine how these growth patterns in the developing world have impacted the degradation of the environment. This study contends that merely considering GDP per capita and the proportion of manufacturing in GDP fails to encapsulate the complete growth dynamics of developing and emerging countries. Consequently, such an approach does not adequately reflect the impacts of environmental degradation. As a result, the economic complexity index (ECI) is introduced to the model to reflect the full effects of new growth trajectories on CO2 emissions by using the Panel Fully Modified OLS (PFMOLS) model of 67 emerging and developing countries during 1996–2020. The results indicate that the complexity of developing and emerging economies, on the one hand, raises CO2 emissions, likely through expanding economic activities (the scale effect). Moreover, ECI reduces CO2 emissions by moving the economy toward more high-tech and environmentally friendly technologies and industries and favorable changes in the energy mix (the efficiency effect). Overall, the empirical outcomes emphasize that the final impact of ECI on the environment was negative in most samples, indicating an improving impact of economic complexity on environmental degradation, reflecting that the “efficiency effect” outweighed the “scale effect.” The findings imply that technology and knowledge transfer are essential for energy efficiency and sustainability.

Trade‐offs and synergies: Examining the impact of natural resource rents and energy efficiency on financial development in the RCEP context

AbstractThis study investigates the complex interplay between financial and economic development within the Regional Comprehensive Economic Partnership (RCEP) countries—Australia, China, Indonesia, Japan, and South Korea—from 2000 to 2022, with a focus on the impacts of natural resource rents and energy efficiency. Employing moment quantile regression to address non‐normal data distribution identified by the Jarque–Bera (JB) test, we unveil diverse slopes and cross‐sectional interdependencies, necessitating a nuanced examination. Panel unit root tests confirm non‐stationarity, enabling a thorough investigation. Our findings reveal a long‐term cointegration relationship between natural resource rents, energy efficiency, economic development, and foreign direct investment (FDI), providing a holistic understanding of their dynamics. Notably, our analysis exposes the trade‐off between natural resource abundance and financial growth, as evidenced by negative coefficients for natural resource rents, while positive coefficients for economic growth, energy efficiency, and FDI counterbalance this effect, fostering a conducive financial environment. Additionally, our examination of location and scale characteristics unveils vulnerabilities associated with natural resources alongside stability indicators linked to economic growth, energy efficiency, and FDI. By employing quantile regression, our study sheds light on the nuanced impacts of natural resources, offering valuable insights for policymakers and researchers in navigating sustainable financial development within the RCEP framework.

Comprehensive evaluation of CCUS technology: A case study of China's first million-tonne CCUS-EOR project

CCUS, an emerging technology for reducing carbon emission, plays a crucial role in achieving the goal of carbon neutrality. CCUS technology exemplified by CO2 enhanced oil recovery (EOR) is gradually progressing from project demonstration to large-scale application. However, the commercial application still faces uncertainties in economic cost, energy efficiency and environmental benefits. This paper takes China's first million-tonne CCUS-EOR project (Qilu Petrochemical-Shengli Oilfield CCUS-EOR project) as an example, and establishes a comprehensive research framework for evaluating CCUS from the three dimensions of energy, environment, and economy, based on economic viability, energy input-output analysis, and carbon input-output analysis. The results demonstrate that during the project lifecycle, when the average oil price is $90/bbl, the project's NPV is $56.09 million, the project's IRR is 13.4 %, the payback period is 8.34 years, and the threshold oil price for the project to be economically profitable is $81.52/bbl. Furthermore, the Energy Return on Investment (EROI) of the project is 9.09, which considerably superior to that of the Shengli Oilfield's non-EOR, and the net energy output is approximately 18,472.57 kilobarrels. The Carbon Return on Investment (CROI) of the project is 4.12, with significant environmental benefits, and the cumulative net carbon emission reduction is approximately 8078.55 kilotonnes. Furthermore, the trends in EROI and CROI of the CCUS-EOR project demonstrate nearly opposite trajectories. The variation trends in EROI emerge N-shaped curve, while that of CROI emerge S-shaped curve. In summary, the Qilu Petrochemical-Shengli Oilfield CCUS-EOR project exhibits notable advantages in terms of energy efficiency and environmental benefits. However, the threshold oil price for triggering economic profitability is relatively high, which may pose certain economic risks to investors during periods of low oil price.

Exploring the Complexity of Energy Poverty in the EU: Measure it, Map it, Take Actions

AbstractEnergy poverty presents a pressing challenge in the European Union (EU), worsened by recent geopolitical events and economic vulnerabilities, particularly highlighted by the COVID-19 crisis. This article explores the complexity of energy poverty within the EU context, emphasizing the necessity to define, measure, and monitor it comprehensively. It reviews the evolution of energy poverty definitions and causes, underlining the multifaceted nature of the issue influenced by factors such as low-income, high-energy prices, and building inefficiencies. Various measurement indexes are examined, and categorized into consensus, expenditure-income comparison, and direct/indirect measurement indicators, offering insights into their advantages and limitations. Furthermore, the work discusses mapping methodologies to pinpoint instances of energy poverty spatially. It also examines best regulatory practices employed by nations, including economic accessibility enhancements and structural interventions like investments in energy efficiency and renewable sources. Finally, the authors propose a novel approach to map energy poverty at municipal granularity in Italy, integrating economic vulnerability and building energy efficiency indices.

Economic sanctions and energy efficiency: Evidence from Iranian industrial sub-sectors

Improving energy efficiency is vital for reducing energy consumption and can have substantial impacts on reducing carbon emissions. This study investigates the impact of sanctions on Iran's energy efficiency across different industrial sub-sectors from 2015 to 2019. We compute a sanction intensity index for each industrial sub-sector using principal component analysis. This index measures how much each sub-sector has been affected by sanctions. Additionally, energy efficiency is measured using the directional distance function method, considering the emission impacts as undesirable outputs. We use fixed effects regression analysis, adjusting for various manifestations of cross-sectional (spatial) and temporal dependence and controlling for other sectoral drivers of energy efficiency. We find a significant negative effect of sanction intensity on energy efficiency at the industrial sub-sector level in Iran. The negative effect of sanctions on energy efficiency is significantly larger for industrial units with higher import dependency.

Techno-economic, energy, and environmental impact assessment of hydrogen supply chain: A comparative study of large-scale production and long-distance transportation

Hydrogen energy has made significant progress as one of the technological pathways that can facilitate the green transformation of various sectors, including the chemical industry, steel production, transportation, and power generation. However, areas with high demand for hydrogen are typically located thousands of kilometers away from large-scale production facilities. Hydrogen transported from the most cost-competitive large production sites to areas that lack hydrogen resources requires converting gaseous hydrogen into a high-density liquid. Thus, global market trade is important for hydrogen carriers in long-distance and large-scale transportation. In this study, liquefied hydrogen (LH2) and ammonia (NH3), which are hydrogen-based energy carriers, are analyzed and compared in terms of economic costs, energy efficiency, and carbon dioxide (CO2) emissions. It has been demonstrated that the LH2 supply chain is more energy-efficient and has higher CO2 emissions compared to the NH3 supply chain. Furthermore, this study shows that the levelized cost of hydrogen transportation (LCoHT) delivered from Australia to Ningbo, China, is lower for NH3 (19.95 yuan/kg-H2) compared to LH2 (22.83 yuan/kg-H2). Meanwhile, the LCoHT for the two supply chains is in a similar range (27.82 yuan/kg-H2 and 21.53 yuan/kg-H2 for LH2 and NH3, respectively) from Norway to Ningbo, China. The impacts of important parameters on the LCoHT, energy efficiency, and CO2 emissions of the LH2/NH3 supply chain are also considered through a sensitivity analysis.

Green growth governance and total factor energy efficiency: Economic growth constraint and policy implementation in OECD countries

This study aims to examine the nature and governance of green growth strategy in OECD countries. As the strategy implies a sustainable relationship between economic growth and energy efficiency, we considered economic, environmental, and policy factors to empirically analyze green total factor energy efficiency (GTFEE) performances for 2001–2020 period. For this purpose, we employed a two-step methodology. In the first step, we estimated GTFEE scores from an undesirable output model by using robust order-m frontier efficiency method. In the second step, we used GTFEE estimates and built a panel data model to investigate the impact of governance and environmental policy factors. The panel data regression results point to several implications. Firstly, market-based environmental stringency policies are found to be effective. Also, economic globalization is found to be effective only in market-based and mix policy cases. The findings indicate the key roles of market-based pricing mechanisms and economic actors for the inclusive governance of green growth. Secondly, economic growth is found to be negatively related with GTFEE which shows the trade-off between economic growth and energy efficiency. Lastly, the analysis by commitment periods of the Kyoto Protocol points to the importance of global consensus on the implementation of green growth strategy.

Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence

This paper proposes an automated approach to the technology selection of High-Voltage Alternating Current (HVAC) Offshore Substations (OHVS) for the integration of Oil & Gas (O&G) production and Offshore Wind Farms (OWF) based on Artificial Intelligence (AI) techniques. Due to the complex regulatory landscape and project diversity, this is enacted via a cost decision-model which was developed based on Knowledge-Based Systems (KBS) and incorporated into an optioneering software named Transmission Optioneering Model (TOM). Equipped with an interactive dashboard, it uses detailed transmission and cost models, as well as a technological and commercial benchmarking of offshore projects to provide a standardized selection approach to OHVS design. By automating this process, the deployment of a technically sound and cost-effective connection in an interactive sandbox environment is streamlined. The decision-model takes as primary inputs the power rating requirements and the distance of the offshore target site and tests multiple voltage/rating configurations and associated costs. The output is then the most technically and economically efficient interconnection setup. Since the TOM process relies on equivalent models and on a broad range of different projects, it is manufacturer-agnostic and can be used for virtually any site as a method that ensures both energy transmission and economic efficiency.

Output feedback distributed economic model predictive control for parallel system in process networks

Abstract This paper proposes a distributed economic model predictive control algorithm for parallel systems which uses only output feedback. Such parallel systems are a fundamental system architecture frequently encountered in process networks where, in many cases, the state of the plant is not measurable. Economic performance is a key consideration in the operation of such industrial plants and it is of interest to develop theoretically rigorous approaches to tackle what is a practically very relevant scenario. The competitive couplings and competitive constraints inherent in parallel systems are explicitly addressed in the proposed controller design framework. Three measures are considered for optimization of such parallel systems including an economic stage cost function, energy efficiency and tracking accuracy. An economic cost function is optimized by the resulting distributed controller which can realize global control performance while also reducing the computational time for large-scale parallel systems. Stability of the system is formally proved using the principles of dissipativity. Finally, the effectiveness of the proposed theoretical approach is verified by both numerical simulation and experimentation to demonstrate practical relevance.

Understanding the Economic Drivers of Climate Change in Southeast Asia: An Econometric Analysis

This study analyses macroeconomic trends in Southeast Asian countries and their implications for climate change, focusing on urbanisation, GDP per capita, energy intensity, FDI, inflation, and trade. Using panel data from 1970 to 2020, we investigate climate change drivers across Indonesia, Malaysia, the Philippines, Singapore, and Thailand through panel ARDL with PMG and MG analyses, along with Hausman tests. Our results highlight the need for tailored urbanisation policies for sustainability, as the consistent positive correlation between GDPs per capita and emissions, underscores the challenge of decoupling economic growth from emissions. Urbanisation’s varying impact calls for proactive planning, and mixed FDI results suggest nuanced investment approaches aligned with sustainability. Inflation’s negative impact hints at environmental benefits during price increases, necessitating integrated economic and climate policies. The positive relationship between trade openness and emissions emphasises the need for eco-conscious trade agreements to mitigate emissions from industrial activity. Our study stresses the importance of considering macroeconomic heterogeneity in crafting climate policies. Policymakers must adopt multifaceted approaches that prioritise sustainability across economic growth, energy efficiency, technology adoption, and trade to balance development with environmental preservation. This approach enables Southeast Asian countries to contribute effectively to global climate change mitigation.

Hybrid-timescale optimal dispatch strategy for electricity and heat integrated energy system considering integrated demand response

An integrated energy system realizes multi-energy management and multi-load integrated supplement. However, because of the uncertainties of the renewable energy and loads and different dynamic characteristics of multi-energy, the efficiency of the system is constrained. To ascend the flexibility, a hybrid-timescale dispatch strategy considering integrated demand response is proposed. Firstly, a deep integrated demand response strategy is proposed using price demand response and ground source heat pump. Secondly, a linear dynamic model of the heat network is adopted to calculate the real-time energy transfer status in the heat pipeline, reflecting the thermal delay. Thirdly, to embed the linear dynamic model into the optimal scheduling process, a hybrid-timescale optimal dispatch framework for electricity and heat integrated energy system is proposed. Simulation results on MATLAB show that compare to the system that does not consider integrated demand response, the wind desertion, user cost and operation cost are reduced by 16.4 %, 0.85 %, and 2.72 %, respectively. And compared with the system only using energy storage, the planning cost is reduced by 47.0 %. By introducing the IDR strategy, and adopting the dynamic model of heat system, the flexibility of the system is released and the balance between economic cost and energy efficiency are achieved.

Harvesting energy horizons: Bifacial PV and reversible fuel cells unite for sustainable building solutions

This study explores the integration of bifacial photovoltaic (PV) panels with proton exchange membrane (PEM) reversible fuel cells (RFC) to enhance renewable energy storage across various U.S. climates. It assesses the impact of environmental variables like sunlight exposure, climate fluctuations, and energy demands on system efficiency and resilience. The cities considered in the study were Tucson, Los Angeles, Denver, Dallas, and Minneapolis. Each city was chosen for its unique climatic characteristics, ranging from the arid heat of Tucson to the cold temperatures of Minneapolis. This diverse selection helps to evaluate the system's performance and economic viability across a broad spectrum of environmental conditions. Economic analysis focuses on metrics such as the Levelized Cost of Electricity (LCOE), Levelized Cost of Hydrogen (LCOH), and Levelized Cost of Storage (LCOS). Findings indicate significant economic benefits through varying bifacial PV gains from 0 to 20% yield with reductions in LCOE by 16%, LCOH by 14%, LCOS by 13%, and overall system LCOE by 18%. The results highlight the potential of bifacial PV and PEM-RFC systems to boost energy yield and economic efficiency amid dynamic environmental conditions. This analytical framework offers detailed insights into the economic viability and advantages of these systems in different climatic zones in the United States.

Sustainability Indicators Correlation Matrix

Abstract: This study explores the complex interplay between economic growth, environmental preservation, and energy efficiency in the context of sustainable development. Leveraging analytical tools such as the OSeMOSYS model and Pearson correlation coefficient, the research investigates how economic decisions impact energy resource utilization and environmental quality. Key sustainability indicators, including Energy Payback Time (EPBT), Internal Rate of Return (ITR), and Climate Change Impact Mitigation (IMPcc), are analyzed within the framework of the Atlantis energy system. The study emphasizes the need to balance economic priorities with environmental considerations to achieve sustainability objectives effectively. Furthermore, the research evaluates the correlation between sustainability indicators when integrated into the optimization process of the OSeMOSYS energy modeling system. This approach, advocated in previous studies, underscores the importance of incorporating sustainability metrics into decision-making processes. In conclusion, the findings highlight the necessity of reevaluating the weighting of indicators within optimization functions to prioritize sustainability goals. By providing insights into the complex relationships between economic, energy, and environmental factors, the study contributes to advancing sustainable development practices for policymakers, businesses, and society as a whole.

Improving Distributed Renewable Energy Power Planning Through Particle Swarm Algorithm

The ongoing energy structure reform in our country has led to the emergence of distributed renewable energy as a primary source of energy development and utilization, primarily due to its utilization of local resources. However, challenges such as undefined objectives and ineffective planning have impeded its progress. This study specifically investigates distributed renewable energy power planning by enhancing a particle swarm algorithm with a strategy for updating local optimal solutions. The refined algorithm tackles issues related to renewable energy variability and economic efficiency, thereby optimizing the planning of distributed renewable energy power systems. The outcomes illustrate improvements in system operation, economic viability, and environmental sustainability. This research contributes to the progression of particle swarm algorithms for the planning of distributed renewable energy power systems.

Techno-economic optimization of photovoltaic (PV)-inverter power sizing ratio for grid-connected PV systems

- The accurate sizing of the inverter, specifically the power sizing ratio (PSR) plays a vital role in maximizing energy production and economic benefits. Existing studies often overlook the complex interplay between maximizing energy capture and minimizing inverter-related economic costs when selecting the optimal PSR. This research presents a techno-economic approach to optimizing the PSR for grid-connected photovoltaic (PV) systems. A simulation model is developed, incorporating real weather data and inverter efficiency curves. The model is calibrated using a Pattern Search Algorithm (PSA) to ensure an accurate representation of real-world inverter behavior by achieving a minimum relative difference of 13.78 % (Norm-RMS) in AC power output. The analysis explores the trade-off between PSR, annual energy yield, and inverter clipping. An optimal PSR of 1.19 is identified, balancing energy capture (up to 2000W inverter capacity) and economic efficiency. This approach promotes cost-effective inverter selection and wider PV adoption.

Can forests realize the carbon neutrality dream? Evidence from a global sample

The enlarge in economic activities and the urban population at the global level has brought about an increase in the demand for energy, food, and natural resources, as well as an exacerbation in global climate change concerns. In this respect, it is important to ensure the balance between global climate change and global economic activities. Therefore, a wide literature has emerged that searches for alternative solutions to improve climate change and carbon dioxide (CO2) emissions. The majority of existing studies emphasize the importance of renewable energy sources in environmental improvement efforts. Few studies highlight the importance of forestation in environmental improvement efforts, highlighting the non-linear effects of forestation. To fill this gap, this study uses panel data from 181 countries between 1990 and 2022 and evaluates the non-linear impact of economic growth, forest extent, energy efficiency, and urban growth on per capita CO2 emissions using a dynamic panel threshold and dynamic panel quantile threshold methods. Furthermore, we extend the model and conduct robustness tests examining the non-linear threshold effects of renewable and non-renewable energy consumption on per capita CO2 emissions. Our findings provide pieces of evidence that forest extents are an alternative solution to renewable energy use and energy efficiency in environmental improvement efforts.

Economy-wide rebound and the returns on investment in energy efficiency

In this paper we re-examine the relationship between global Gross Domestic Product (GDP), Primary Energy Use (PEU) and Economic Energy Efficiency (EEE) to explore how investment in energy efficiency causes rebound in energy use at the global scale. Assuming GDP is a measure of final useful work, we construct and fit a biophysics-inspired nonlinear dynamic model to global GDP, PEU and EEE data from 1900—2018 and use it to estimate how energy efficiency investments relate to output growth and hence economy-wide rebound effects. We illustrate the effects of future deployment of enhanced energy efficiency investments using two scenarios through to 2100. The first maximizes GDP growth, requiring energy efficiency investment to rise ~ twofold. Here there is no decrease in PEU growth because economy-wide rebound effects dominate. The second scenario minimizes PEU growth by increasing energy efficiency investment ~ 3.5 fold. Here PEU and GDP growth are near fully decoupled and rebound effects are minimal, although this results in a long run, zero output growth regime. We argue it is this latter regime that is compatible with the deployment of enhanced energy efficiency to meet climate objectives. However, while output growth maximising regimes prevail, efficiency-led pledges on energy use and emissions reduction appear at risk of failure at the global scale.

Factor mismatch measurement of resource-based cities: Evidence from all-round optimization total factor productivity decomposition framework

In-depth analysis of the factors affecting the transformation of resource-based cities can provide effective support for the transformation and development of resource-dependent regions. How to comprehensively identify the factors affecting the transformation of resource-based cities is a complex problem. This study starts from the total factor productivity model and focuses on the two core basic factors that affect the transformation process of cities reliant on resources. Economic benefits and energy efficiency, respectively, from the economic benefit analysis framework and energy efficiency analysis framework for reconstruction, the two frameworks are combined with the use of distorted prices of resource elements to solve the problem that the synergistic effect of economic benefits and energy efficiency can not be measured. In order to quantitatively analyze the factors that affect the development efficiency of cities reliant on resources under the single or synergistic effect of the comprehensive framework, this study optimizes the directional distance function from three perspectives: exogenous weight, direction vector endogeneity, and absolute distance transformation relative distance, thus achieving an accurate assessment transformation efficiency of cities reliant on resources. Considering the impact of the new coronavirus epidemic, this study only selected the data of resource-based cities from 2003 to 2018, and found through model calculation that the impact on the transformation of cities reliant on resources: (1) Labor mismatch is mainly achieved by affecting the structure about the production of resource-based enterprises and industrial human resources; (2) Capital mismatch is mainly realized by affecting the production of resource-based enterprises; (3) Energy mismatch is mainly achieved by affecting high energy consumption enterprises and low production technology level enterprises. Further research shows that the main objects of these factors are the four parts of production technology level, energy consumption, total factor productivity and industrial structure. Through these contents, they affect environmental efficiency and deeply affect the transformation process of resource-based cities.

Управління розвитком підприємств паливно-енергетичного комплексу на засадах процесноорієнтованого підходу

The article explores the possibilities of developing enterprises in the fuel and energy complex of Ukraine based on implementing a process-oriented approach to management. The process-oriented approach is considered an essential tool for developing enterprises of the fuel and energy complex in the conditions of activation of the system of destabilizing and crisis factors, strengthening resource limitations. Actual tasks for the development of the fuel and energy complex in the future are highlighted, namely: focus on territorial decentralization in the placement of enterprise capacities, development of small-scale energy, non-traditional energy systems, diversification of energy supply sources for enterprises, formation of fuel and energy resource reserves at different levels of the territorial-production hierarchy, orienting enterprises to their resources. Attention is focused on the need to define the essential tasks of enterprise development policy in modern conditions: security orientation of management policy, ensuring the reliability of energy systems, operational flexibility, and economic efficiency. The contradictory nature of the combination of such tasks in the practical plane is revealed. It has been proven that the process approach makes it possible to implement tools that would overcome these contradictions and form the prerequisites for the development of enterprises. The need to find management models that would rationally integrate functionally oriented and process-oriented approaches to management, allowing to focus on the principles of economic security, priorities of flexibility, and economic efficiency, is substantiated. Keywords: enterprise development, process-oriented approach, fuel and energy complex, economic security, operational flexibility, reliability of energy systems, economic efficiency.