4.8 Article

The analysis of security cost for different energy sources

期刊

APPLIED ENERGY
卷 86, 期 10, 页码 1894-1901

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2008.11.028

关键词

Energy security cost; Hirschman-Herfindahl index; Diversity measure; Supply and demand concentration

向作者/读者索取更多资源

Global concerns for the security of energy have steadily been on the increase and are expected to become a major issue over the next few decades. Urgent policy response is thus essential. However, little attempt has been made at defining both energy security and energy metrics. In this study. we provide such metrics and apply them to four major energy sources in the Korean electricity market: coal, oil, liquefied natural gas, and nuclear. In our approach, we measure the cost of energy security in terms of supply disruption and price volatility, and we consider the degree of concentration in energy supply and demand using the Hirschman-Herfindahl index (HHI). Due to its balanced fuel supply and demand, relatively stable price, and high abundance, we find nuclear energy to be the most competitive energy source in terms of energy security in the Korean electricity market. LNG, on the other hand, was found to have the highest cost in term of energy security due to its high concentration in supply and demand, and its high price volatility. In addition, in terms of cost, we find that economic security dominates supply security, and as such, it is the main factor in the total security cost. Within the confines of concern for global energy security, our study both broadens our understanding of energy security and enables a strategic approach in the portfolio management of energy consumption. (C) 2008 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Computer Science, Information Systems

Do product reviews really reduce search costs?

Naveen Amblee, Rahat Ullah, Wonjoon Kim

JOURNAL OF ORGANIZATIONAL COMPUTING AND ELECTRONIC COMMERCE (2017)

Review Green & Sustainable Science & Technology

The effect of patent protection on firms' market value: The case of the renewable energy sector

Daehyun Kim, Namil Kim, Wonjoon Kim

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)

Article Computer Science, Information Systems

On the time lag of the effect of network position on service performance in software service networks

Kibae Kim, Jorn Altmann, Wonjoon Kim

INFORMATION & MANAGEMENT (2019)

Correction Computer Science, Information Systems

On the time lag of the effect of network position on service performance in software service networks (vol 56, 103149, 2015)

Kibae Kim, Jorn Altmann, Wonjoon Kim

INFORMATION & MANAGEMENT (2020)

Article Economics

Measuring cross-country heterogeneity in the value of patents based on the patent-trade relationship

Junyoung Hong, Wonjoon Kim

Summary: The private value of patents varies across countries due to different patent protection systems and business environments. A new approach is suggested to estimate the perceived private value of patents by considering trade scales in various countries. Regardless of the level of patent protection, changes in the strategic business value of patents play a key role in determining the value of patents in different countries.

APPLIED ECONOMICS LETTERS (2022)

Article Economics

How does competition in the development of artificial intelligence affect a firm's technology search strategy? Evidence from the US pharmaceutical industry

Taekyun Kim, Wonjoon Kim

Summary: The study shows that there is a mutual learning relationship between early and late entrants during technological shifts. Late entrants learn basic technology from early entrants, while early entrants learn applied technology from late entrants.

APPLIED ECONOMICS LETTERS (2023)

Article Economics

Are researchers more likely to succeed when they start a technology-based startup?

Jeongbong Han, Daehyun Kim, Wonjoon Kim, Sunghyun Cho

Summary: This study explores the connection between a founder's occupational background and the survival rate of technology-based startups, with a focus on founders who have previous experience in research positions. By utilizing a unique database of tech-based startups, the study finds that startups founded by researchers have a lower survival rate compared to those led by founders from other backgrounds. However, prior entrepreneurial experience positively affects the relationship between a founder's research experience and startup survival rate, indicating that practical business knowledge can compensate for the lack of business expertise in a researcher's background. Additionally, the study reveals that startups established by researchers from large companies have an even lower survival rate due to constraints in acquiring essential management skills within the specialization of large organizations. These findings highlight the significance of cultivating a diverse skill set for startup success.

APPLIED ECONOMICS LETTERS (2023)

Article Public Administration

The scientific and technological interdisciplinary research of government research institutes: network analysis of the innovation cluster in South Korea

Yoonjung Jung, Euiseok Kim, Wonjoon Kim

Summary: This study investigates the development of interdisciplinary research (IDR) in various scientific disciplines and its relationship with R&D performance using network analysis of papers and patents from government research institutes in South Korea's Daedeok Innopolis. The findings show that IDR has increased over time across disciplines and research institutes, and higher interdisciplinarity in scientific publications and patents is significantly correlated with higher R&D performance.

POLICY STUDIES (2021)

Article Business

The effects of funding policy change on the scientific performance of government research institutes

Wonjoon Kim, Sungjin Min

ASIAN JOURNAL OF TECHNOLOGY INNOVATION (2020)

Article Economics

Are social entrepreneurs more risk-averse?

Sukwoong Choi, Namil Kim, Wonjoon Kim

APPLIED ECONOMICS LETTERS (2019)

Article Business

Complementary multiplatforms in the growing innovation ecosystem: Evidence from 3D printing technology

Kiho Kwak, Wonjoon Kim, Kyungbae Park

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE (2018)

Article Information Science & Library Science

Do your social media lead you to make social deal purchases? Consumer-generated social referrals for sales via social commerce

Namil Kim, Wonjoon Kim

INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT (2018)

Article Economics

Compromise effect and consideration set size in consumer decision-making

Jaewon Yoo, Hyunsik Park, Wonjoon Kim

APPLIED ECONOMICS LETTERS (2018)

Article Energy & Fuels

Theoretical and experimental investigation on the advantages of auxetic nonlinear vortex-induced vibration energy harvesting

Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou

Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.

APPLIED ENERGY (2024)

Article Energy & Fuels

Evaluation method for the availability of solar energy resources in road areas before route corridor planning

Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan

Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.

APPLIED ENERGY (2024)

Article Energy & Fuels

Impacts of PTL coating gaps on cell performance for PEM water electrolyzer

Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender

Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.

APPLIED ENERGY (2024)

Article Energy & Fuels

Coordinated pricing mechanism for parking clusters considering interval-guided uncertainty-aware strategies

Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado

Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.

APPLIED ENERGY (2024)

Article Energy & Fuels

The establishment of evaluation systems and an index for energy superpower

Duan Kang

Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.

APPLIED ENERGY (2024)

Article Energy & Fuels

A model-based study of the evolution of gravel layer permeability under the synergistic blockage effect of sand particle transport and secondary hydrate formation

Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang

Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.

APPLIED ENERGY (2024)

Article Energy & Fuels

Energy optimization for HVAC systems in multi-VAV open offices: A deep reinforcement learning approach

Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi

Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Asymmetry stagger array structure ultra-wideband vibration harvester integrating magnetically coupled nonlinear effects

Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong

Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.

APPLIED ENERGY (2024)

Article Energy & Fuels

Enhancement of hydrogen production via optimizing micro-structures of electrolyzer on a microfluidic platform

Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song

Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel day-ahead scheduling model to unlock hydropower flexibility limited by vibration zones in hydropower-variable renewable energy hybrid system

Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz

Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.

APPLIED ENERGY (2024)

Article Energy & Fuels

Archery-inspired catapult mechanism with controllable energy release for efficient ultralow-frequency energy harvesting

Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He

Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.

APPLIED ENERGY (2024)

Article Energy & Fuels

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy

Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang

Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.

APPLIED ENERGY (2024)

Article Energy & Fuels

Capacity fade prediction for vanadium redox flow batteries during long-term operations

Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung

Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.

APPLIED ENERGY (2024)

Article Energy & Fuels

State-of-charge balancing strategy of battery energy storage units with a voltage balance function for a Bipolar DC mircrogrid

Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu

Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.

APPLIED ENERGY (2024)

Article Energy & Fuels

Deep clustering of reinforcement learning based on the bang-bang principle to optimize the energy in multi-boiler for intelligent buildings

Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen

Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.

APPLIED ENERGY (2024)