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Application of critical path method to stochastic processes with historical operation data

CHEMICAL ENGINEERING RESEARCH & DESIGN 2019年 149卷 195-208页

作者： Takakura, Yuya Yajima, Tomoyuki Kawajiri, Yoshiaki Hashizume, Susumu Nagoya Univ Dept Mat Proc Engn Nagoya Aichi Japan Georgia Inst Technol Dept Chem & Biomol Engn Atlanta GA 30332 USA Nara Coll Natl Inst Technol Dept Control Engn Nara Japan

The CPM (Critical Path Method) is a network-based approach for project management. This method identifies the longest path, which allows us to find the critical path that must be shortened so that the completion time of the whole project can be shortened. However, considering uncertainty in CPM is not straightforward. In this paper, we consider an optimization problem for stochastic CPM problems, where task durations are expressed as discrete histograms obtained from historical operation data, that maximizes the probability that all tasks are completed within a given completion time by improving the task durations on the critical path. We propose two reformulations of the problem as a mixed-integer linear programming problem: one based on tasks, and the other based on paths. In addition, we propose an iterative method to solve the problem efficiently by reducing the number of binary variables. Finally, we demonstrate efficiency of our proposed methods in some case studies. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Critical path method Project scheduling Time-cost trade off problem Uncertain durations mixed-integer linear programming Historical operation data

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Optimal design and dispatch of a hybrid microgrid system capturing battery fade

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OPTIMIZATION AND ENGINEERING 2019年第1期20卷 179-213页

作者： Goodall, Gavin Scioletti, Michael Zolan, Alex Suthar, Bharatkumar Newman, Alexandra Kohl, Paul Colorado Sch Mines Dept Mech Engn Golden CO 80401 USA Univ Texas Austin Dept Mech Engn Austin TX 78712 USA Georgia Inst Technol Sch Chem & Biomol Engn Atlanta GA 30332 USA

Microgrids provide power to remote communities and at operational sites that are not connected to a grid. We consider such a microgrid that consists of batteries, photovoltaics, and diesel generators, and optimize the components it comprises and a corresponding dispatch strategy at hourly fidelity so as to minimize procurement, operations and maintenance, and fuel costs. The system is governed by constraints such as meeting demand and adhering to component interoperability and capability. Our contribution lies in the introduction to this optimization model of a set of constraints that incorporates capacity fade of a battery and temperature effects. We show, using data from a forward operating base and solving the corresponding instances for a time horizon of 8760h, that higher temperatures decrease resistance, leading to better round-trip energy efficiency, but at the same time increase capacity fade of the battery, resulting in a higher overall operating cost. In some cases, the procurement strategy is robust to the fade of the battery, but fade can influence battery state of charge and power output as the available battery capacity degrades over time and with use.

关键词： Design optimization Dispatch optimization Microgrids Batteries mixed-integer linear programming Systems analysis

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A hybrid time MILP model for the pump scheduling of multi-product pipelines based on the rigorous description of the pipeline hydraulic loss changes

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COMPUTERS & CHEMICAL ENGINEERING 2019年 121卷 174-199页

作者： Zhou, Xingyuan Zhang, Haoran Qiu, Rui Liang, Yongtu Wu, Guangming Xiang, Chengcheng Yan, Xiaohan China Univ Petr Natl Engn Lab Pipeline Safety Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing 102249 Peoples R China Univ Tokyo Ctr Spatial Informat Sci 5-1-5 Kashiwanoha Kashiwa Chiba 2778568 Japan Univ Southern Calif Viterbi Sch Engn 3650 McClintockAve Los Angeles CA 90089 USA Res Inst China Natl Offshore Oil Corp Sun Palace South St 6 Beijing 100027 Peoples R China

As the primary means of transporting refined products, multi-product pipelines play a significant role in ensuring downstream energy supply. The pump scheduling optimization of multi-product pipeline can significantly lower the energy consumption of the pipeline. With the input parameters of pipeline flowrates and batch interface locations, which are determined by a specific detailed schedule, this paper first proposes an innovative method for a rigorous description of pipeline hydraulic loss changes during the multi-batch sequential transportation process. Based on the hybrid time representation, the scheduling horizon is divided into two levels of time windows and a mixed-integer linear programming (MILP) model for the pump scheduling of multi-product pipelines is established according to the proposed method. Various technical and operational constraints are considered. Finally, the established model is successfully applied to a real-world multi-product pipeline, with three operation modes, in China. The superiority, accuracy, and applicability of this model are validated in detail through comparison with a previous model. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Pump scheduling Multi-product pipeline mixed-integer linear programming Hydraulic loss Time continuity

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Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2019年 127卷 237-278页

作者： Zhang, Yongxiang D'Ariano, Andrea He, Bisheng Peng, Qiyuan Southwest Jiaotong Univ Sch Transportat & Logist POB 610031 Chengdu Sichuan Peoples R China Roma Tre Univ Dept Engn Via Vasca Navale 79 I-00146 Rome Italy

This paper addresses the problem of improving the integration between passenger timetabling and track maintenance scheduling. We propose a microscopic optimization model and an iterative algorithm for solving this problem efficiently. Block sections are considered as the basic microscopic elements for train movements in a railway network. A mixed-integer linear programming formulation is proposed for the integrated optimization problem in which train timing, sequencing and routing are the timetabling variables, while timing and sequencing of maintenance tasks are the track maintenance variables. The objective function is to minimize the total train travel time and the maintenance tardiness cost. The constraints proposed in this work address the practical specifications of the INFORMS RAS 2016 Problem Solving Competition (2016 PSC). In this context, the main decision variables are the entrance and exit times of the trains on each block section plus the start and end times of each maintenance task. Since the integrated optimization problem is strongly NP-hard, an iterative algorithm is proposed to compute near-optimal solutions in a short computation time. The algorithm is based on a decomposition of the overall problem into sub-problems related to train scheduling and/or routing with or without track maintenance task scheduling. The connecting information between the two sub-problems concerns the selected train routes plus the start and end times of the maintenance tasks. Computational experiments are performed on a set of realistic railway instances, which were introduced during the 2016 PSC. The iterative algorithm outperforms a standard MILP solver and the first-place team of this competition in terms of both solution quality and time to deliver the new best-known solutions. The scalability of the iterative algorithm is investigated when increasing the number of trains and track maintenance tasks. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Railway scheduling Infrastructure maintenance Integrated optimization mixed-integer linear programming

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Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method

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ENERGY 2019年 184卷 45-57页

作者： Yokoyama, Ryohei Shinano, Yuji Taniguchi, Syusuke Wakui, Tetsuya Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan Zuse Inst Berlin Dept Optimizat Takustr 7 D-14195 Berlin Germany

For the purpose of making a decision in the optimal design of an energy supply system, it is important to investigate not only the optimal solution but also suboptimal ones which follow the optimal one without any omissions, what are called K-best solutions. In this paper, a mixed-integer linear programming method utilizing the hierarchical relationship between design and operation variables proposed previously is extended to search the K-best solutions very efficiently. In addition, methods for updating the incumbents are incorporated into the extended method for three options for the criterion set newly in deriving the K-best solutions. This extended method is implemented into open and commercial MILP solvers, and is applied to illustrative and practical case studies, respectively, on the optimal design of cogeneration systems. Through the studies, it turns out that the proposed method is much superior in terms of solution optimality and computation efficiency to a conventional method, and that the computation efficiency to derive one of the K-best solutions by the proposed method increases with the number of K-best solutions. In addition, features of the K-best solutions in the value of objective function are clarified. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Energy supply systems Optimal design and operation mixed-integer linear programming K-best solutions Branch and bound method Hierarchical approach

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Optimal Coordination of Water Distribution Energy Flexibility With Power Systems Operation

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IEEE TRANSACTIONS ON SMART GRID 2019年第1期10卷 1101-1110页

作者： Oikonomou, Konstantinos Parvania, Masood Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA

This paper proposes a model for optimizing the energy flexibility of water distribution systems (WDSs) in day-ahead power systems operation. The water distribution system operators (W-DSOs) are considered as energy-conscious entities, who run the proposed WDS operation model to optimize the operation of pumps and tanks for minimizing the operation cost of local WDSs, given the expected water demand and electricity prices of the next day. A WDS energy flexibility model is proposed that is used by W-DSOs in order to calculate and offer the feasible flexible energy capacity to the power system operator. The proposed WDS operation model takes into account the hydraulic operating constraints of water networks, thus ensuring deliverability of the WDS energy flexibility. Further, a network-constrained unit commitment model is proposed that integrates and optimizes the energy flexibility of WDSs in the day-ahead operation of power systems. The proposed model is implemented on a 15-node WDS that is powered by a 6-bus power system and the results are presented to study the impacts of optimized WDS energy flexibility on power and water systems operation.

关键词： Water distribution systems energy flexibility mixed-integer linear programming unit commitment demand response water-energy nexus

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Flexibility Scheduling for Large Customers

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IEEE TRANSACTIONS ON SMART GRID 2019年第1期10卷 371-379页

作者： Angizeh, Farhad Parvania, Masood Fotuhi-Firuzabad, Mahmud Rajabi-Ghahnavieh, Abbas Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Sharif Univ Technol Ctr Excellence Power Syst Control & Management Elect Engn Dept Tehran 11369363 Iran Sharif Univ Technol Dept Energy Engn Tehran 11369363 Iran

Large customers are considered as major flexible electricity demands which can reduce their electricity casts by choosing appropriate strategies to participate in demand response programs. However, practical methods to aid the large customers for handling the complex decision making process for participating in the programs have remained scarce. This paper proposes a novel decision-making tool for enabling large customers to determine how they adjust their electricity usage from normal consumption patterns in expectation of gaining profit in response to changes in prices and incentive payments offered by the system operators. The proposed model, formulated as a mixed-integer linear programming problem, simultaneously determines the optimal integration of the flexibility options including flexible load rescheduling and utilizing onsite generation and energy storage systems, along with energy procurement from the grid that allows the large customers to optimize their energy portfolio from different sources including bilateral contracts and the market. The characteristics of the proposed integrated flexibility scheduling and energy procurement model and its benefits are investigated through several case studies conducted on a test large industrial load.

关键词： Demand response flexible load energy storage systems onsite generation energy procurement large customers mixed-integer linear programming

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Techno-economic feasibility assessment of grid-defection

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 109卷 403-412页

作者： Liu, Hangyue Azuatalam, Donald Chapman, Archie C. Verbic, Gregor Univ Sydney Sch Elect & Informat Engn Sydney NSW Australia

The interest in off-grid solar PV system has grown significantly in recent years. The price of suitable batteries started to decline following the price trajectory of solar PV, the curtailment of solar feed-in-tariff in many countries and the increasing electricity price. These are some important factors for grid defection trends. In this paper, we analyse the reliability and levelised cost of electricity (LCOE) of residential off-grid customers' PV-battery systems in order to carry out a techno-economic feasibility study of grid-defection. In more detail, this study demonstrates how off-grid customers can trade-off reliability for LCOE of their PV-battery systems, taking into consideration the priority/user-preference of different load types in a household. Consequently, we propose a novel decision making tool to improve the performance of a dynamic home energy management system (HEMS). The HEMS is set up as a mixed-integer linear optimization (MILP) problem which is solved using a rolling-horizon approach for weekly and yearly simulations. Weekly simulations were first performed in order to investigate the optimal range of PV and battery size combinations based on reliability and LCOE, using a week with the lowest solar PV output and the highest demand. Given the optimal PV-battery size combinations, yearly simulations were performed to assess the reliability and LCOE of PV-battery systems of randomly selected residential households in the Ausgrid Solar Home Electricity Data. Simulation results over the critical time period of the year indicate that an off-grid PV-battery system is relatively feasible for customers who are willing to compromize lower reliability in exchange for a lower cost. The result however indicates that the cost is still higher compared with a grid-connected system.

关键词： Grid-defection Home energy management system Off-grid PV-battery system mixed-integer linear programming Battery storage Rooftop photovoltaic

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An affine arithmetic-model predictive control approach for optimal economic dispatch of combined heat and power microgrids

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APPLIED ENERGY 2019年 242卷 1436-1447页

作者： Romero-Quete, David Rosero Garcia, Javier Univ Nacl Colombia Bogota Colombia

This paper presents a novel approach for the optimal economic dispatch of Combined Heat and Power (CHP) Microgrids (MGs), which incorporates an Affine Arithmetic-based Economic Dispatch (AAED) problem into a Model Predictive Control (MPC) framework. The proposed algorithm solves an AAED problem each At minutes (e.g. 15 min) with time steps of Delta t minutes over a time horizon T (e.g. 24 h). It uses the available forecast and the current state of the system to provide the schedule and the affine forms that represent the operation intervals of the generators and Energy Storage Systems (ESS) for the next time interval [t, t + Delta t]. Online set points for generators and ESS are then obtained by computing the noise symbols values of the affine forms, based on the most updated information of electricity and heat demands and available renewable energy power. A theoretical CHP-based MG, comprising PVs, a gas boiler, a CHP unit, a battery, and a thermal tank, is used to assess the performance of the AA-MPC approach in both connected and isolated operation modes. The method is also compared with a deterministic MPC approach. Results show the ability of the method to better address forecasting errors, resulting in more cost-effective solutions without considerably affecting the computation performance.

关键词： Affine arithmetic Combined heat and power Microgrid mixed-integer linear programming Model predictive control Uncertainties

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Incorporating Wind Energy in Power System Restoration Planning

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IEEE TRANSACTIONS ON SMART GRID 2019年第1期10卷 16-28页

作者： Golshani, Amir Sun, Wei Zhou, Qun Zheng, Qipeng P. Hou, Yunhe Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA Univ Cent Florida Dept Ind Engn & Management Syst Orlando FL 32816 USA Univ Hong Kong Elect & Elect Engn Dept Hong Kong Peoples R China

Wind energy is rapidly growing. While wind brings us clean and inexpensive energy, its inherent variability and uncertainty present challenges for the power grid. In particular, employing wind energy for power system restoration is very challenging. A fast and reliable restoration plays a vital role to achieve the self-healing power grid. This paper develops a novel offline restoration planning tool for harnessing wind energy to enhance grid resilience. The wind-for-restoration problem is formulated as a stochastic mixed-integer linear programming problem with generated wind energy scenarios. The problem is then decomposed into two stages and solved with the integer L-shaped algorithm. Numerical experiments have been conducted through different case studies using the modified IEEE 57-bus system. The developed tool can provide the scheduled wind power at each restoration time. The impact of wind energy is investigated from the aspects of location and inertia capability, as well as wind penetration, fluctuation, and uncertainty. Moreover, a dynamic response validation tool is developed to validate the results of optimization problem in a dynamic simulation software. Simulation results demonstrate that the optimal wind harnessing strategy can help improve system restoration process and enhance system resilience.

关键词： integer L-shaped algorithm mixed-integer linear programming power system restoration stochastic optimization wind uncertainty

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