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Analysis on the synergy between markets of electricity, carbon, and tradable green certificates in China

ENERGY 2024年 302卷

作者： Li, Jialin Hu, Yu Chi, Yuanying Liu, Dunnan Yang, Shuxia Gao, Zhiyuan Chen, Yuetong North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China Beijing Inst Petrochem Technol Sch Econ & Management Beijing 102627 Peoples R China Beijing Univ Technol Sch Econ & Management Beijing 100124 Peoples R China

China has integrated tradable green certificates and carbon markets with its electricity sector to promote renewable energy and reduce carbon emissions. However, the impact mechanism of decision-making behaviors of involved entities in these integrated markets on the market equilibrium is still unclear, hence limiting the further development of renewable energy industries and carbon reduction progress to some extent. Therefore, conducting in-depth research to inform policy makers about the impacts of entities ' decision-making behaviors on market equilibrium within the context of integrated multiple markets is crucial. This study aims to analyze the characteristics of entities ' decision-making behaviors and equilibrium states within the collaborative dynamics of carbon, electricity, and green certificate markets. Specifically, an optimal decision-making model for entities given the multi-market coupling was developed by employing mathematical programming methods to analyze market equilibriums across various market combinations and policy parameters. The conclusions underscore equilibrium price shifts and decision-making characteristics among entities across multiple markets. The result shows that the carbon market could increase power prices and decrease green certificate prices. To ensure sustainable energy development, policymakers should consider the decision-making behavior of entities under multi-market coupling, which can promote the low-carbon transformation of the Chinese energy industry.

关键词： Multi-market equilibrium Tradable green certificate Carbon market Multi-market policy coordination bi-level optimization model

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Scenario-based stochastic optimization on the variability of solar and wind for component sizing of integrated energy systems

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RENEWABLE ENERGY 2024年 237卷

作者： Hua, Lin Xia, Junjie Xiang, Gao Lei, Zheng Jing, Dengwei Zhang, Xiongwen Guo, Liejin Xi An Jiao Tong Univ State Key Lab Multiphase Flow Power Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ MOE Key Lab Thermofluid Sci & Engn Xian 710049 Shaanxi Peoples R China Shanghai Elect Power Co Ltd Shanghai 200010 Peoples R China

The inherent intermittency and variability of renewable energy sources present significant challenges to the optimal design and implementation of integrated energy systems (IES). This paper introduces a novel stochastic optimization model that integrates advanced scenario generation and clustering algorithm for renewable energy sources within a multi-objective, bi-level optimization framework. Specifically, the clearness index is employed to represent the stochastic distribution of solar radiation intensity by beta distribution, while wind speed uncertainty is modeled seasonally using the Weibull distribution. Monte Carlo sampling with synchronous back substitution is applied for scenario generation and reduction of solar radiation and wind speed. To address the multi-objective evaluation, the analytic hierarchy process is utilized, and the joint optimization is achieved by combining a region contraction algorithm with stochastic programming. The proposed methodology is validated on an IES featuring various heating devices, incorporating uncertainties in both wind and solar energy. The results indicate that the absorption heat pump-based scheme achieves superior energy-saving performance, achieving an energy rate of 0.4724. Additionally, the compression heat pump-based scheme exhibits excellent economic efficiency and environmental sustainability, with a cost of energy of 0.3639 and a renewable fraction of 0.5536.

关键词： Integrated energy system Multi-objective optimization Stochastic multi-scenario optimization bi-level optimization model Optimum sizing and operation

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Research on bi-level Optimized Operation Strategy of Microgrid Cluster Based on IABC Algorithm

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IEEE ACCESS 2021年 9卷 15520-15529页

作者： Zhang, Zhiyu Wang, Zhijie Wang, Hong Zhang, Hongwei Yang, Wanhao Cao, Rongbin Shanghai Dianji Univ Coll Elect Engn Shanghai 201306 Peoples R China Tongji Univ Coll Econ & Management Shanghai 200092 Peoples R China Univ Shanghai Sci & Technol Coll Elect Engn Shanghai 200093 Peoples R China

This paper considers the economy and reliability of the microgrid cluster system, and proposes a bi-level optimized operation strategy for the microgrid cluster, which aims to improve the economic benefits of the microgrid cluster and reduce the operating risk of microgrid. The upper layer takes the microgrid cluster as the research object, with the goal of minimizing the total operating cost of the system, and establishes the optimal model of the microgrid cluster. The lower layer takes the sub-microgrid as the research object, and establishes the microgrid optimization model with the goal of optimal operating cost and operating risk index. The method of combining mixed integer linear programming and IABC algorithm is used to solve the multi-objective bi-level optimization model, and to provide decision makers with two microgrid dispatching schemes with different focuses. Finally, an example is used to verify the effectiveness of the bi-level optimization strategy and improved algorithm proposed in this paper, as well as the practicability of the two dispatching schemes.

关键词： Microgrids optimization Power generation Mathematical model Clustering algorithms Reliability State of charge Microgrid microgrid cluster multi-objective improved artificial bee colony algorithm bi-level optimization model

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The optimal emergency demand response (EDR) mechanism for rural power grid considering consumers' satisfaction

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ENERGY REPORTS 2021年 7卷 118-125页

作者： Wang, Yunchu Jin, Jianfeng Liu, Haifeng Zhang, Zhi Liu, Shengyuan Ma, Jien Gong, Chao Zheng, Yufeng Lin, Zhenzhi Yang, Li Zhejiang Univ Sch Elect Engn Hangzhou 310027 Peoples R China State Grid Zhejiang Elect Power Co Ltd Huzhou Anji Elect Power Supply Co Huzhou 313300 Peoples R China State Grid Zhejiang Elect Power Co Ltd Huzhou Elect Power Supply Co Huzhou 313000 Peoples R China Zhejiang Huayun Informat Technol Co Ltd Hangzhou 310000 Peoples R China Shandong Univ Sch Elect Engn Jinan 250061 Shandong Peoples R China

More and more requirements for the operation of the rural power systems arised with the increase of type and capacity of the rural load in China. In fact, the economy, flexibility and stability of the rural power grid can be improved by an emergency demand response (EDR) mechanism, which can fast reduce distributed load considering consumers' satisfaction. An EDR mechanism for the rural power grid is proposed considering the characteristics of small distributed load capacity in rural areas. The optimal demand response model of diversified loads is built to maximize the utility of rural private industry. A bi-level optimization model is presented to minimize the deviation between the power shortage and reduced demand, considering the active demand response of rural consumers. Case studies are finally employed to demonstrate the effectiveness of the EDR mechanism for enhancing the security of the rural power system..c 2021 TheAuthors. Published by Elsevier Ltd. This is an open access article under theCCBY-NC-NDlicense (http://***/licenses/by-nc-nd/4.0/). Peer-reviewunder responsibility of the scientific committee of the International Conference on Power Engineering, ICPE, 2020.

关键词： Emergency demand response (EDR) Rural power system bi-level optimization model Consumers' satisfaction

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Reserve provision of combined-cycle unit in joint day-ahead energy and reserve markets

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APPLIED ENERGY 2023年第1期336卷

作者： Zhang, Rufeng Sun, Haihang Li, Guoqing Jiang, Tao Li, Xue Chen, Houhe Zou, He Northeast Elect Power Univ Dept Elect Engn Jilin 132012 Peoples R China China Elect Power Equipment & Technol Co Ltd Beijing Peoples R China

With the continuous development of natural gas-fired combined cycle power generation technology, the com-bined cycle (CC) unit's installed capacity is gradually increasing in the power system because of its flexible operation characteristics. Participating in the energy and reserve markets and taking advantage of flexible mode transfer characteristics, the CC unit can provide the system with energy and sufficient reserve capacity. This paper proposes a bi-level strategic bidding model to study the CC unit's bidding behavior in the day-ahead energy and reserve markets. The upper-level model is an optimal bidding model for the configuration-based CC unit aiming to maximize its profit. The lower-level model is the joint market clearing model of the energy and reserve markets managed by the independent system operator (ISO). CC unit and ISO in this model influence each other by the locational marginal electricity prices (LMEP) and the locational marginal reserve prices (LMRP) obtained from the lower-level market-clearing model. The CC unit submits the bids to the ISO and ar-ranges the generation plan according to the market clearing results of the lower-level market-clearing model carried out by the ISO. The proposed bi-level optimization model is transformed into a mathematical equilibrium constraint (MPEC) problem by Karush-Kuhn-Tucker (KKT) conditions and duality theory. In this paper, the improved IEEE-6 bus and IEEE-57 bus systems are used as case studies to verify the effectiveness of the proposed bidding strategy for the CC unit. The results show that the proposed bidding strategy can effectively improve the profits of the CC unit in the electricity market. Compared with the case of the CC unit only participating in the energy market, the profits of the CC unit in the market increased by 8.84% and 12.3%.

关键词： Combined-cycle unit Energy and reserve markets Market clearing bi-level optimization model

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A multiple uncertainty-based bi-level expansion planning paradigm for distribution networks complying with energy storage system functionalities

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ENERGY 2023年第1期275卷

作者： Zhou, Siyu Han, Yang Chen, Shuheng Yang, Ping Mahmoud, Karar Darwish, Mohamed M. F. Matti, Lehtonen Zalhaf, Amr S. Univ Elect Sci & Technol China Sch Mech & Elect Engn Chengdu 611731 Peoples R China Aalto Univ Sch Elect Engn Dept Elect Engn & Automat Espoo 02150 Finland Aswan Univ Fac Engn Dept Elect Engn Aswan 81542 Egypt Benha Univ Fac Engn Shoubra Dept Elect Engn Cairo 11629 Egypt Tanta Univ Elect Power & Machines Engn Dept Tanta 31511 Egypt

Reliability improvement is regarded as a crucial task in modern distribution network expansion planning. Compared to previous works, this paper presents a bi-level optimization model to optimize the planning of the distribution network complying with multiple renewable energy and energy storage system (ESS) functionalities to guarantee the economical and reliable operation of the distribution network. The candidate assets include substations, distribution lines, renewable energy-based distributed generations (DGs), and ESSs are systematically involved. The load level affected by seasonal change and the multiple uncertainties, including renewable energy, load fluctuation, and contingency outage, are comprehensively considered. The uncertainties caused by the stochastic of renewable energy and load demand are described using Latin Hypercube Sampling (LHS) method. To address the computational burden and complexities associated with non-linear AC power flow, the mixed-integer linear programming (MILP)-based bi-level model is proposed via piecewise linearization methodology. Therein, the upper-level optimization model is proposed to minimize the total present value cost of the planning scheme in normal operating conditions. The lower level model, which is constrained to investment decision-making of the upper-level framework, aims to minimize the total cost of expected energy not supplied (EENS) considering the uncertainties of the single contingency outage. The effectiveness of the proposed bi-level planning model is validated by numerical studies to guarantee economic and reliability improvement for distribution network.

关键词： Reliability improvement bi-level optimization model Multiple uncertainties Piecewise linearization Expected energy not supplied

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Performance analysis of an energy system with multiple combined cooling, heating and power systems considering hybrid shared energy storage

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APPLIED THERMAL ENGINEERING 2023年第1期233卷

作者： Li, Yaohong Wei, Mingshan Tian, Ran Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou 730050 Peoples R China

The performance of multi-CCHP energy system considering hybrid shared energy storage (HSES), which comprises shared electrical energy storage (SEES) and shared thermal energy storage (STES), was analyzed through bi-level optimization. Firstly, the superiority of the HSES operation mode in terms of capacity reduction and cost savings was investigated. The HSES mode effectively utilizes the complementarity of load demand and the differences in energy consumption behavior of multiple CCHPs, which reduces the capacity of electricity and heat storage equipment by 50.5% and 82.7% and reduces the total cost of the CCHP systems by 17.0%. Subsequently, analyses on the effect of energy storage type shows that the HSES mode increases the revenue while reduces the total cost of the CCHP systems compared with SEES and STES modes. Lastly, the effect of the CCHP number on the economic performance of the energy system is investigated under the conditions of fixed and optimized capacity of energy storage stations. Results show that the optimized capacity scheme is more beneficial for the profitability of the HSES station. Moreover, when multiple CCHP systems are involved in energy sharing, the economics of the shared storage station are closely related to the investment cost of the heating pipe network, which is the special character of electro-thermal coupled energy storage.

关键词： Shared electrical energy storage Shared thermal energy storage Hybrid shared energy storage Multiple CCHP systems bi-level optimization model The complementarity of load demand

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Underground energy storage system supported resilience enhancement for power system in high penetration of renewable energy

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FRONTIERS IN ENERGY RESEARCH 2023年 11卷

作者： Qin, Boyu Shi, Wen Fang, Ruoquan Wu, Dongyang Zhu, Yu Wang, Hongzhen Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian Peoples R China Jiangsu Transportat Engn Construct Bureau Nanjing Peoples R China

High penetration of renewable energy is becoming an important development trend in new generation power system. However, frequent extreme weather events and fragile renewable energy sources pose a huge challenge to the power system resilience. As an important support technology of renewables, energy storage system is of great significance in improving the resilience of the power system. In this paper, a resilience enhancement method for power systems with high penetration of renewable energy based on underground energy storage systems (UESS) is proposed. Firstly, a resilience assessment model is established and the influence of extreme weather is quantified as the failure rate of power system components. Secondly, a bi-level optimization model for UESS operation and planning under extreme weather is built, and the life cycle of UESS is considered. Finally, taking the modified IEEE RTS-79 as an example, the optimal scheme for UESS configuration and operation is given, the investment and effectiveness of UESS is also analyzed. The results show that UESS can significantly enhance the power system resilience under extreme weather events.

关键词： resilience underground space energy storage renewable energy bi-level optimization model

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Train Timetable optimization with Consideration of Passenger Choices in a Multi-modal Rail-Transit System

Train Timetable Optimization with Consideration of Passenger...

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2024 世界交通运输大会

作者： Yiyao Zhang Jiateng Yin D'Ariano Andrea Yihui Wang State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University School of Systems Science Beijing Jiaotong University Department of Civil Computer Science and Aeronautical Technologies EngineeringRoma Tre University

With the emerging of Mobility-as-a-Service(MaaS),the coordination of multi-modal transportation,such as urban rail transit and buses,has received tremendous attention in recent years.A key challenge in the coordination of multi-modal transportation is the interaction between the operational plan and passenger choices,since passengers have different travel choices according to their individual *** address the above challenge,this study proposes a novel bi-level optimization framework,where the upper level aims to design a timetable for the trains in a rail-transit network to maximize the overall profit,while the lower level determines the itinerary choice of passengers,given the operational timetable from the upper *** solve the difficult bi-level model,we developed an iterative method,where the timetables and passenger choices are iteratively updated and improved to a local optimal *** experiments on a real-world case study in Beijing demonstrate the effectiveness of the proposed *** found that the consideration of passenger choice preferences has an obvious impact on the timetable planning.

关键词： Rail Transit Network Passenger Choice Behaviours Train Timetable Scheduling bi-level optimization model

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A 2-phase interdependent methodology for sustainable project portfolio planning in the pharmaceutical industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 174卷

作者： Salehi, Faraz Al-e-Hashem, S. Mohammad J. Mirzapour Husseini, S. Mohammad Moattar Amirkabir Univ Technol Dept Ind Engn & Management Syst Tehran 158754413 Iran Rennes Sch Business 2 Rue Robert D Arbrissel F-35065 Rennes France

In response to the increasing awareness of sustainability issues, companies have reevaluated their approach to research and development (R&D). Taking into account the long-term effects and consequences of R&D projects on social, economic, and environmental conditions, this research has presented a comprehensive methodology for planning pharmaceutical holding company project portfolios by considering both sustainability dimensions and profitability objectives. The first phase of the developed methodology consists of a new combined MCDM method that is used to determine the sustainability score of each project. The following phase focuses on developing a bi-level bi-objective optimization model that is designed to take into account the decentralized structure of pharmaceutical holdings to optimize the budgeting, selection, and scheduling of projects. This optimization model proposes that the head office of the holding company as leader allocates R&D budgets between subsidiaries as followers to maximize the holding company's profit and sustainability. In contrast, the followers are responsible for selecting and scheduling research projects. We examine the optimal strategy of each actor using an illustrative case to validate the methodology. Based on experimental results, an approach focusing on sustainability versus profitability (or vice versa) has a significant impact on decisions made at each level of operation. The results reveal that the proposed approach can be adopted by the holding companies to improve the performance of portfolio planning from the sustainability perspective.

关键词： Sustainable project portfolio planning budget allocation SWARA-COCOSO MCDM method project portfolio selection-scheduling pharmaceutical industry bi-level optimization model

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