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11th IEEE-PES Innovative Smart Grid Technologies Europe (IEEE-PES ISGT Europe)

作者： Ahsan, Syed M. Khan, Hassan A. Ayyadi, Soumia Arif, Syed M. Lie, Tek-Tjing Naveed-ul-Hassan Lahore Univ Management Sci Dept Elect Engn LUMS Lahore Pakistan Muhammad V Univ Rabat Morocco Auckland Univ Technol Elect & Elect Engn Dept Sch Engn Comp & Math Sci Auckland New Zealand

ISBN: (纸本)9781665448758

Integrating renewable energy resources with dedicated energy storage systems in building regimes is becoming viable with numerous well-documented advantages. Multiple buildings, i.e., primary building(s) (with solar & storage) and secondary building(s) (ordinary building dependent entirely on the grid), have bilateral contracts with each other, resulting in an optimized exchange bilaterally and with the grid to reduce grid costs. Further, the allowance of electric vehicles (EVs) in these buildings enable added options to optimize the power flows, focusing on cost reduction. In this work, a mixed-integer linear program (MILP) is formulated to maximize the primary building's profits, along with the financial gains to secondary buildings and a fleet of EVs. The charging infrastructure at the primary building also facilitates the EVs' load by accounting for factors such as feeder time-of-use (TOU) tariffs, contracted rates between the buildings, and EV charging prices. Results for actual load profiles for buildings in Auckland, New Zealand show that primary buildings earn up to 87 % of daily profits along with the 10-41 % daily cost savings for secondary buildings. The insights presented in this work can benefit local aggregators with options to maximize local profits lowering the grid dependence.

关键词： Energy Storage System Electric Vehicles mixed integer linear programming Buildings Bilateral Contracts

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Aggregate production planning considering organizational learning with case based analysis

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AIN SHAMS ENGINEERING JOURNAL 2022年第2期13卷

作者： Attia, El-Awady Megahed, Ashraf AlArjani, Ali Elbetar, Ahmed Duquenne, Philippe Prince Sattam Bin Abdulaziz Univ Coll Engn Al Kharj Ind Engn Dept Al Kharj 16273 Saudi Arabia Benha Univ Shoubra Fac Engn Mech Engn Dept Cairo 11672 Egypt Elaraby Grp Qalubia Governorate Egypt Benha Univ Fac Engn Benha Mech Engn Dept Banha Egypt Toulouse Univ Ind Engn Dept INPT ENSIACET Toulouse France

Responding rapidly to customer needs is one of the main targets of industrial organizations that want to survive in the current market competition. This objective can be attained through robust planning. Workforce productivity is considered one of the important entities in production planning. However, it has a dynamic nature, i.e. the productivity growths thanks to on-job training or learning phenomenon. Considering this fact in manufacturing planning enhances the robustness of the developed plans. The present paper presents a mathematical model for medium-range production planning that is used to find the optimal aggregate production plan. The model aims to optimize the total production costs while respecting most of the operational constraints and considering the process of organizational learning. The presented model is constructed relying on the real industrial practices;the outcome is a mixed-integer linear program. The model was validated and checked using real data collected from an Egyptian factory that produces electric motors for home appliances. The proposed mathematical model was optimally solved using "ILOG-CPLEX 12.6". By comparing the results obtained versus that of the method adopted in the factory, a cost reduction of 6.3% is achieved for the presented data set. A set of managerial aspects are concluded after the model analysis. Moreover, the impact of using detailed learning rates on the production cost is discussed. (c) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Aggregate production planning Learning curves Organizational learning mixed integer linear programming Manufacturing of electric motors

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Maximizing financial benefits of investment tax allowances in renewable energy portfolios

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ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY 2022年第1期17卷

作者： Castillo-Ramirez, Alejandro Mejia-Giraldo, Diego Univ Antioquia Grp Efficient Energy Management Medellin Colombia Univ Antioquia Dept Elect Engn Medellin Colombia

Policy makers offer fiscal incentives to encourage companies to invest in renewable technologies. This work considers generation companies that take advantage of fiscal incentives to minimize income tax. Thus, a novel mixed-integer linear optimization model that minimizes total tax payments of a company owning a portfolio of energy projects is designed. The model strategically manages depreciation, tax loss carryforward, and tax incentive use for minimizing discounted income tax. A set of revenue scenarios was employed to analyze model results. The proposed model yields tax savings between 8.2% and 19.2% of the company's taxes. Tax savings are significantly larger for companies with a large generation portfolio;which represents a clear advantage over small generation companies. The proposed model can also be employed by policy makers to adjust future ITA policies by taking advantage of the anticipative knowledge of the optimal tax strategies implemented by generation companies.

关键词： Depreciation tax optimization investment tax allowances tax loss carryforward renewable energy investments mixed integer linear programming

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An exact microgrid formation model for load restoration in resilient distribution system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 116卷

作者： Zhu, Junpeng Yuan, Yue Wang, Weisheng Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Jiangsu Peoples R China China Elect Power Res Inst State Key Lab Operat & Control Renewable Energy & Beijing 100192 Peoples R China

The increase in extreme weather affects the distribution system, leading to system collapse and interruption power supply to loads. Microgrid formation and operation in island mode is a resilient solution when major faults happen in the distribution system. This paper proposes a novel microgrid formation model considering power loss and voltage constraints in the power balance and operation feasibility. The introduction of binary variables to represent the reconfigured network and the adoption of non-linear equations to represent the exact power flow will lead the microgrid formation model to be a mixed integer nonlinear program (MINLP). This paper proposes an iteration based linear approximation of the MINLP, the exactness of which can be guaranteed by the convergence of the iteration process. Numerical results based on IEEE 33 and PE&G 69 bus standard distribution systems demonstrate the effectiveness of the developed method.

关键词： Microgrid formation Load restoration Resilient distribution system mixed integer linear programming linear approximation

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A Multi-Trip Customized Bus Network Design Model

A Multi-Trip Customized Bus Network Design Model

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IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Qi Wang Peng Wu School of Economics & Management Fuzhou University Fuzhou P. R. China

ISBN: (数字)9798350314212

ISBN: (纸本)9798350314229

Customized bus services offer irreplaceable advantages in meeting passengers' diverse travel needs and promoting eco-friendly transportation. It is essential to undertake a scientifically planned and strategically laid-out customized bus operation network to achieve the efficient operation of customized buses. In this study, we address a new multi-trip customized bus network design problem with considering passenger time windows, walking limitations, bus capacity, multi-trip, and stop location decisions to simultaneously minimize customized bus operational cost and maximize the number of passengers served. We formulate it as a mixed-integer linear programming model. Computational results for a case based on the well-known Sioux Falls network verify the effectiveness and efficiency of the model.

关键词： Legged locomotion Costs Computational modeling Transportation mixed integer linear programming Computational efficiency

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A multi-objective model for the analysis of investments to achieve an electricity cleaner production. The case of the Argentinean system

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ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY 2022年第1期41卷

作者： Alvarez, Gonzalo E. INGAR CONICET UTN Inst Desarrollo & Diseno Santa Fe Argentina

The electric power systems are in a transition to forms of generation that achieve cleaner production. In this regard, a new multi-objective model that helps with the problem of cleaner production investments is presented. The model can obtain convenient solutions where actors with opposed interests are participating. The novelty is the model considers more points of view than the classical approaches of the literature, which only consider a maximum of two actors involved in this field (the new model considers investment costs, greenhouse emissions, and operating costs). Another key contribution is that the real procedures of the generation and transmission stages and the dependences between electrical-natural gas systems are carefully represented and included in the model. It allows obtaining solutions in concordance with the real conditions. The model is applied to the energy system of Argentina by using an epsilon-constraint approach and mixed integer linear programming formulations. The test system supplies electricity to over 40 million people and neighboring countries. Besides, there is interdependency with the Argentinean Natural Gas system that operates in one of the most extended territories in Latin America. Results indicate that the solutions that are more convenient for all actors represent a mix between renewables and non-renewables technologies. Consequently, this proposal is differentiated from other ones that only consider the expansion concerning renewables technologies. The study reveals decreases in emissions up to 39% and the reduction in production costs up to 12% in comparison with the solution without investments.

关键词： CO2 emissions electric power systems mixed integer linear programming natural gas transportation Pareto optimality

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Wasserstein metric-based two-stage distributionally robust optimization model for optimal daily peak shaving dispatch of cascade hydroplants under renewable energy uncertainties

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ENERGY 2022年 260卷

作者： Jin, Xiaoyu Liu, Benxi Liao, Shengli Cheng, Chuntian Zhang, Yi Zhao, Zhipeng Lu, Jia Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Dalian Univ Technol Sch Elect Engn Dalian 116024 Peoples R China China Yangtze Power Co Ltd Yichang 443133 Peoples R China

The integration of large-scale weather-dependent renewable energy (RE) changes how power grids operate, particularly for peak shaving dispatch. This paper uses flexible hydropower to buffer the volatility and the randomness of RE sources and aid peak shaving in response to the transition towards sustainability. Thus, a Wasserstein metric-based two-stage distributionally robust optimization model for the regional power grid's daily peak shaving dispatch is constructed. Peak shaving dispatch, minimizing the maximum residual load, focuses on the first stage, whilst integrating various operational constraints. In the second stage, for hedging against random RE sources' interference, hydropower is adjusted based on the principle of minimum water consumption adjustment. A reformation approach based on strong dual theory and linearization technology is employed to transform the proposed model into a mixed-integer linear programming (MILP) framework. Case studies for a provincial power grid in Southwest China are being conducted. Results show that the proposed model can conduct peak shaving effectively and compensate for RE randomness and volatility by taking full advantage of hydropower's flexible regulation ability. Furthermore, simulation results demonstrate that the proposed model outperforms the benchmark models in most cases and provides flexibility for decision-makers to weigh the trade-off between operational reliability and economy.

关键词： Hydro -based hybrid energy system Peak shaving Distributionally robust optimization Wasserstein metric mixed integer linear programming

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Site-specific optimization of bus stop locations and designs over a corridor

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2022年 599卷

作者： Jin, Hui Liu, Yue Wu, Telan Zhang, Yanpei Soochow Univ Sch Rail Transportat 8 Jixue Rd Suzhou Jiangsu Peoples R China Univ Wisconsin Milwaukee Dept Civil & Environm Engn POB 784 Milwaukee WI 53201 USA

Bus stops, interfacing passenger demand with route design and traffic dynamics, play a critical role in improving bus operation efficiency. This study proposes a two-lane based link-node cell transmission model referring to bus stop length, for the optimization of bus stop locations and designs against car and bus demand as well as bus dwell time, along a corridor with sequent links of specific length, which are connected with signalized intersections and inserted with sparse or dense stops. Thus the effect on total travel time can be exploited of the complex relationship between traffic dynamics and continuous stops. The nonlinear modeling is then converted to mixed integer linear programming, which is solvable to optimality. Numerical analyses validate that the proposed stop configuration reduces total travel time under all cases, averaged to be 20.5% and 7.1% for the corridor with short and long links, respectively. The proposed scheme combines harbor-style and curb-side stops which may be far-side, mid-block, or near-side to coordinate bus and car flow, where MLC is reduced up to 32% on some links to alleviate capacity drop especially for the corridor with short links and dense stops, and DLC is increased up to 25% to enhance road utilization especially for the corridor with long links. This research provides insights on the designs and locations of bus stops along urban streets, to alleviate the conflicts between buses and cars for efficient and attractive bus service. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： Bus stop mixed traffic flow Lane changing Two-lane cell transmission model mixed integer linear programming

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Learning to branch with Tree-aware Branching Transformers

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KNOWLEDGE-BASED SYSTEMS 2022年 252卷

作者： Lin, Jiacheng Zhu, Jialin Wang, Huangang Zhang, Tao Tsinghua Univ Dept Automat Beijing Peoples R China

Machine learning techniques have attracted increasing attention in learning Branch-and-Bound (B&B) variable selection policies, but most of the existing methods lack extensions to heterogeneous problems. Though parameterizing search trees has recently shown a promising alternative for het-erogeneous scenarios, it remains challenging to maintain good performance when generalizing to instances comparatively harder to solve than those seen during training. To fill this gap, we propose a tree-aware transformer-based branching framework for branching efficiently and effectively. Specifically, the transformer-based branching is conducted, in which the mutual connections between candidate variables can be evaluated by the self-attention mechanism. Then, we novelly encode the empirical data in the search tree, i.e., branching history, with a binary tree representation. In this way, we can fully utilize features exploited from the parameterized B&B search trees and stronger branching policies can be attained thereby. The proposed models are evaluated on multiple benchmark instances and achieve a significant boost on performance, in terms of smaller B&B search trees and lower primal-dual integrals and gaps for harder problems within a given time limit. Ablation studies further validate the effectiveness of our method. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Branch and Bound Machine learning Branching strategies mixed integer linear programming

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Operation Scheduling for Multiple HVAC Systems under Power Constraints

Operation Scheduling for Multiple HVAC Systems under Power C...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Theint Theint Thu Kenshiro Kato Dafang Zhao Hiroki Nishikawa Ittetsu Taniguchi Takao Onoye Graduate School of Information Science and Technology Osaka University Suita Japan

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper proposes operation scheduling for multiple HVAC systems. Uncoordinated scheduling of multiple HVAC systems can lead to a significant power imbalance and increase energy consumption. To minimize the total energy consumption of HVAC systems, we propose a coordinated load scheduling for multiple HVAC systems, considering thermal comfort under power constraints. This work is based on mixed integer linear programming and employs model predictive control (MPC). The simulation results highlight that our scheduling problem reduces the total energy consumption by 5.7 kWh (8.7%) on average with satisfying thermal comfort compared to a state-of-the-art one.

关键词： Energy consumption Schedules HVAC Simulation Heuristic algorithms mixed integer linear programming Thermal loading

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