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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Qiao, Huiting Wu, Liangzheng Wen, Shangyong Xue, Mengke Huang, Yan China Southern Power Grid Energy Development Research Institute Guangzhou510530 China North China Electric Power University School of Economics and Management Beijing China

ISBN: (纸本)9798350347159

In the context of low carbon distribution network, this paper proposes a mixed integer second-order cone programming model for active distribution network considering carbon emission and flexible load. The objective is to provide the investment strategy with the minimum total cost under the premise of satisfying network operation constraints and CO2 emission ceiling. Considering the uncertainty of new energy, load and energy price, a scenario clustering method based on K-means was proposed. The decision variables of the model include replacing overload lines, investing in new energy and energy storage devices, and investing in voltage control devices such as voltage regulators and capacitor banks. The polynomial voltage dependent flexible load, network reconstruction and carbon emission limit constraints are considered. Aiming at the nonconvex nonlinear characteristics of the programming model, the network reconstruction was modeled as a mixed integer linear programming form by using the virtual demand method, and an improved second-order cone relaxation method based on Taylor expansion was proposed to solve the problem of the traditional second-order cone relaxation caused by the flexible load model. Finally, the model is solved under the framework of two-stage stochastic programming. The model was tested by a 69-node system, and the results show that the proposed model not only has a lower total planning cost, but also contributes to reducing carbon emissions. © 2022 IEEE.

关键词： stochastic programming

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Optimization and self-dispatching of hydro-power companies in the electricity market 2

Optimization and self-dispatching of hydro-power companies i...

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2022 2nd International Conference on Power System and Energy Internet, PoSEI 2022

作者： Liang, Zhencheng Liang, Qingqing Li, Ling Luo, Cuiyun Dispatching Control Center of Guangxi Power Grid Corporation Guangxi Nanning China Xingjian College of Arts and Sciences Guangxi University Nanning China

The deepening reform of the power system has resulted in increased competition between electricity market participants. The ADP method is applied to solve the optimal self-dispatch problem of hydro-power companies under uncertain conditions. Firstly, according to the characteristics of hydropower generation technology and self-dispatching, the operation model of hydropower is given. Then, according to the organization and trading behavior of the forward contract market and day-ahead market, a medium and long-term contract quantity decision framework based on stochastic programming is given. Based on the stochastic programming decision framework, the ADP method is used to solve the generation and water decisions in each stage, and the distribution strategy of the electricity quantity of forward transactions and day-trading electricity quantity is obtained. Finally, an example is given to demonstrate the effectiveness of the proposed model and ADP method. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： stochastic programming

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Multi-objective operation of distributed generations and thermal blocks in microgrids based on energy management system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2021年第9期15卷 1451-1462页

作者： Homayoun, Rohollah Bahmani-Firouzi, Bahman Niknam, Taher Islamic Azad Univ Dept Elect Engn Marvdasht Branch Marvdasht Iran

The optimal multi-objective operation of microgrids with distributed generations and thermal block based on the energy management system is presented. In the thermal block, the combined heat and power system and boiler and thermal storage system supply the load of the block thermal. Therefore, the proposed strategy minimises three objectives of an microgrid's operation, that is, cost, energy loss and voltage deviation functions. Also, it is subject to AC power flow equations, system operation limits and distributed generations and thermal block constraints. The problem is modelled as a multi-objective optimisation method;then is converted to a single-objective problem model using the epsilon-constraint-based Pareto optimisation. Moreover, the proposed strategy includes uncertainties of the load, energy price and active power of renewable distributed generations;hence, a stochastic programming based on the hybrid Mont Carlo simulation and point estimate method is used to model these uncertain parameters. Then, the teaching-learning-based optimisation and firefly algorithm are utilised to solve the problem to achieve a reliable optimal solution. Finally, the proposed strategy is simulated on the IEEE 69-bus microgrid, and thus, the capabilities of the proposed strategy are extracted.

关键词： system operation limits IEEE 69-bus microgrid multiobjective optimisation method Power system management, operation and economics Optimisation techniques AC power flow equations Pareto optimisation distributed power generation thermal block constraints energy management systems energy loss block thermal teaching-learning-based optimisation thermal storage system supply renewable distributed generations single-objective problem model constraint-based Pareto optimisation energy price optimisation Monte Carlo methods stochastic programming power system Distributed power generation strategy minimises three objectives multiobjective operation load flow energy management system Optimisation microgrids firefly algorithm

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Risk-averse optimal participation of a DR-intensive microgrid in competitive clusters considering response fatigue

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APPLIED ENERGY 2023年 339卷

作者： Tostado-Veliz, Marcos Hasanien, Hany M. Jordehi, Ahmad Rezaee Turky, Rania A. Jurado, Francisco Univ Jaen Dept Elect Engn Linares 23700 Spain Ain Shams Univ Fac Engn Elect Power & Machines Dept Cairo 11517 Egypt Islamic Azad Univ Dept Elect Engn Rasht Branch Rasht Iran Future Univ Egypt Fac Engn & Technol Elect Engn Dept Cairo Egypt

The massive integration of renewable generators, energy storage systems, and demand response requires the development of smart power infrastructures. In this upcoming context, microgrids will be essential for the optimal integration of such assets. When different microgrids are located near each other, they can be centrally coordinated within a novel paradigm called Microgrid Cluster. In such structures, the microgrids involved can collaborate in a cooperative way or compete by developing internal market structures. This paper develops a novel optimal bidding strategy for a demand response-intensive microgrid partaking in competitive clusters. The new proposal is envisaged as a three-stage methodology that aims at reducing the effects of response fatigue. Uncertainties related to inflexible demand and renewable generation are modeled via scenarios, while the risk associated with uncertain parameters is handled by enforcing the Conditional Value at Risk. The resulting computational tool is effective and tractable, as shown in the results obtained on a benchmark three-microgrids cluster. Indeed, the developed methodology is able to reduce the total response signals by 88 % in some cases. Moreover, this case study allows analyzing the effect of response fatigue minimization in the overall cluster performance, showing that the collective welfare can be reduced by 32 % when response fatigue is taken into account.

关键词： Demand response Microgrid cluster Response fatigue Risk-averse optimization stochastic programming

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Vessel weather routing subject to sulfur emission regulation

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2023年 177卷

作者： Lee, Sang-Jeong Sun, Qinghe Meng, Qiang Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore Hong Kong Polytech Univ Fac Business Dept Logist & Maritime Studies Kowloon Hong Kong Peoples R China

The International Maritime Organization (IMO) rolled out a set of new regulations that limit the sulfur content in the fuel oil used by ships, which came into effect from 2020. This study aims to explore the operational decisions of vessels inside and outside emission control areas (ECAs) under uncertain weather conditions and scrutinizes the economics of two types of ships: fuel-switching and scrubber installation. Such operational decisions include speed, trim, and path decision. We construct a navigation grid system, in which each grid contains weather parameters and sea condition. This navigation grid system can be applied to other type of ships due to the well-established cost structure. To improve fuel consumption estimation, we train fuel consumption estimation functions with respect to weather parameters, sea conditions, and operational decisions. This study then develops a stochastic dynamic programming model to optimize the path decisions, vessel speed, and trim. To evaluate the efficiency of the developed stochastic dynamic programming model, we further conduct a case study on a Post-Panamax container vessel that operates westbound from Hamburg to Houston. We identify the path decision, speed and trim under ECAs and the uncertain weather conditions. Surprisingly, this case study demonstrates that the ship utilizing fuel-switching takes a detour trip;in contrast, the ship with a scrubber chooses the shortest path by maximizing the speed. Additionally, we observe a knock-on effect - scrubber installation lifts carbon dioxide emissions due to increased vessel speed outside the ECA region. Rich managerial insights and potential policy implications are discussed.

关键词： Speed Trim Weather routing Emission control area (ECA) stochastic programming

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Two-stage Optimal Risk Management of Large Electricity Consumer Using Second-order stochastic Dominance

Two-stage Optimal Risk Management of Large Electricity Consu...

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2022 IEEE International Conference in Power Engineering Application, ICPEA 2022

作者： Nourollahi, Ramin Mazaheri-Khamaneh, Saman Mohammadi-Ivatloo, Behnam Zare, Kazem Anvari-Moghaddam, Amjad Abdul-Malek, Zulkurnain University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran Aalborg Denmark High Voltage High Current Institute Universiti Teknologi Malaysia School of Electrical Engineering Johor Malaysia

ISBN: (纸本)9781665416290

Various energy consumers, such as large energy consumers (LEC), are targeted to procure the demanded energy from various power markets such as the pool market and different energy resources, including renewable energy resources (RES), and conventional energy resources optimize the traded energy. In this article, a novel decision-making framework is proposed to schedule the LEC. The proposed technique in this article is based on the second-order stochastic dominance (SSD) to investigate the uncertainty in the total operation cost of the LEC. It is assumed that the market price, pool price, electricity load, and the power output of renewable energy sources (RES), including PV and WT, are uncertain parameters. In the proposed SSD-constrained stochastic programming, demand response programming (DRP) is provided to decrease the operation cost of the LEC. A case study is used to illustrate the effectiveness and efficiency of the novel SSD approach. According to the simulation results, the operation cost of LEC is remarkably decreased from 62,960 to 59,550 in the risk-neutral case (without including risk factor) and SSD case (worst case) with considering DRP, respectively. © 2022 IEEE.

关键词： stochastic programming

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Operational Planning of Fixed-Route Buses Considering the Charging of Electric Cars 12

Operational Planning of Fixed-Route Buses Considering the Ch...

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12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

作者： Ohzeki, Takuma Sato, Tetsuya Shiina, Takayuki Hamada, Ryunosuke Waseda University School of Creative Science and Engineering Department of Industrial and Management Systems Engineering Tokyo Japan Denso Corporation Tokyo Japan

ISBN: (数字)9781665497558

ISBN: (纸本)9781665497558

In this study, we examined the problem of creating an operational schedule that considers the charging of multiple electric buses. We considered a model in which fixed-route buses with gasoline-powered engines are replaced with electric vehicles (EVs). This necessitates the charging of their batteries during operation. Therefore, we developed a method to minimize the total battery usage by considering the battery capacity and charging time. Based on experiments using actual data, guidelines were be developed to introduce EVs in existing bus networks. Our numerical experiments demonstrated the effectiveness of the proposed method. © 2022 IEEE.

关键词： stochastic programming

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stochastic programming APPROACH TO HYDRAULIC FRACTURE DESIGN FOR THE LOWER TERTIARY GULF OF MEXICO

STOCHASTIC PROGRAMMING APPROACH TO HYDRAULIC FRACTURE DESIGN...

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作者： SETH PODHORETZ Texas A&M University

学位级别：硕士

In this work, we present methodologies for optimization of hydraulic fracturing design under uncertainty specifically with reference to the thick and anisotropic reservoirs in the Lower Tertiary Gulf of Mexico. In this analysis we apply a stochastic programming framework for optimization under uncertainty and apply a utility framework for risk analysis. For a vertical well, we developed a methodology for making the strategic decisions regarding number and dimensions of hydraulic fractures in a high-cost, high-risk offshore development. Uncertainty is associated with the characteristics of the reservoir, the economics of the fracturing cost, and the fracture height growth. The method developed is applicable to vertical wells with multiple, partially penetrating fractures in an anisotropic formation. The method applies the utility framework to account for financial risk. For a horizontal well, we developed a methodology for making the strategic decisions regarding lateral length, number and dimensions of transverse hydraulic fractures in a high-cost, high-risk offshore development, under uncertainty associated with the characteristics of the reservoir. The problem is formulated as a mixed-integer, nonlinear, stochastic program and solved by a tailored Branch and Bound algorithm. The method developed is applicable to partially penetrating horizontal wells with multiple, partially penetrating fractures in an anisotropic formation.

关键词： stochastic programming Hydraulic Fracturing Offshore Thesis

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A stochastic optimization algorithm for the supply vessel planning problem under uncertain demand and uncertain weather conditions

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OCEAN ENGINEERING 2023年 278卷

作者： Santos, A. M. P. Fagerholt, K. Soares, C. Guedes Univ Lisbon Inst Super Tecn Ctr Marine Technol & Ocean Engn CENTEC Lisbon Portugal NTNU Dept Ind Econ & Technol Management Alfred Getz Veg 3 NO-7491 Trondheim Norway

The Supply Vessel Planning Problem (SVPP) with stochastic demands and uncertain weather conditions is a transportation problem occurring in offshore oil and gas logistics. A fleet of supply vessels based at an onshore depot delivers supplies to a set of offshore oil platforms in a weekly sailing schedule. However, the schedules are frequently disrupted due to adverse weather conditions and uncertain demand for cargo from the oil platforms. The two sources of uncertainty are generally addressed in separate, most often through the use of two-phased methods, where simulation is combined with an optimization algorithm. The most common approach to incorporate robustness in the constructed schedules is to use a subjective penalized cost for non-robust voyages, with explicit modelling of recourse actions. In contrast, this paper proposes a two-stage stochastic programming algorithm accounting for both uncertain demand and uncertain weather conditions, allowing for the incorpo-ration of the cost of recourse in the objective function. The cost of each solution is approximated through the use of discrete event simulation within a genetic algorithm. For the tested problem instances, the potential benefit from solving the stochastic program over solving the corresponding deterministic version leads to average relative annual cost savings of approximately 12%.

关键词： Supply vessel planning problem stochastic programming stochastic demand Uncertain weather conditions

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Designing profitable and responsive supply chains under uncertainty

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第1期59卷 213-225页

作者： Azaron, Amir Venkatadri, Uday Farhang Doost, Alireza Kwantlen Polytech Univ Sch Business Vancouver BC Canada Univ British Columbia Sauder Sch Business Vancouver BC Canada Dalhousie Univ Dept Ind Engn Halifax NS Canada

In this paper, we develop a multi-objective two-stage stochastic programming model, which takes into account the selection of warehouse and retailer sites and the decision about production levels, inventory levels, and shipping quantities among the entities of the supply chain network. The first objective function is to maximise the chain's total profit over multiple periods, and the second objective function is to minimise the total travel times for unsatisfied customers, whose demands must be met by retailers which have been established in other markets, to maximise the chain's responsiveness. Demands, selling prices and productions times at manufacturing sites are all considered as uncertain parameters. The two objective functions are in conflict with each other, and we use epsilon-constraint method to generate a set of Pareto optimal solutions for the proposed multi-objective problem. We then generalise the case and assume the uncertain parameters are continuously distributed random variables and use a simulation approach called sample average approximation (SAA) scheme to compute near optimal solutions to the stochastic model with potentially infinite number of scenarios. A computational study involving hypothetical networks of different sizes and a real supply chain network are presented to highlight the efficiency of the proposed solution methodology.

关键词： Supply chain management multiple objective decision making stochastic programming sampling risk management

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