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Robust Scheduling of Smart Appliances in Active Apartments With User Behavior Uncertainty

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2016年第1期13卷 247-259页

作者： Paridari, Kaveh Parisio, Alessandra Sandberg, Henrik Johansson, Karl Henrik KTH Royal Inst Technol ACCESS Linnaeus Ctr S-10044 Stockholm Sweden KTH Royal Inst Technol Sch Elect Engn Dept Automat Control S-10044 Stockholm Sweden Univ Manchester Sch Elect & Elect Engn Elect Energy & Power Syst Grp Manchester M13 9PL Lancs England

In this paper, we propose a robust approach for scheduling of smart appliances and electrical energy storages (EESs) in active apartments with the aim of reducing both the electricity bill and the CO2 emissions. The proposed robust formulation takes the user behavior uncertainty into account so that the optimal appliances schedule is less sensitive to unpredictable changes in user preferences. The user behavior uncertainty is modeled as uncertainty in the cost function coefficients. In order to reduce the level of conservativeness of the robust solution, we introduce a parameter allowing to achieve a trade-off between the price of robustness and the protection against uncertainty. Mathematically, the robust scheduling problem is posed as a multi-objective mixed integer linear programming (MILP), which is solved by using standard algorithms. The numerical results show effectiveness of the proposed approach to increase both the electricity bill and CO2 emissions savings, in the presence of user behavior uncertainties. Mathematical insights into the robust formulation are illustrated and the sensitivity of the optimum cost in the presence of uncertainties is investigated. Although home appliances and EESs are considered in this work, we point out that the proposed scheduling framework is generally applicable to many use cases, e.g., charging and discharging of electrical vehicles in an effective way. In addition, it is applicable to various scenarios considering different uncertainty sources, different storage technologies and generic programmable electrical loads, as well as different optimization criteria.

关键词： Demand response mixed-integer linear programming multi-objective robust optimization robust scheduling of smart appliances user behavior uncertainty

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Hydro Unit Commitment With a Head-Sensitive Reservoir and Multiple Vibration Zones Using MILP

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第6期31卷 4842-4852页

作者： Cheng, Chuntian Wang, Jiayang Wu, Xinyu Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China

A batch of huge hydropower plants with multiple vibration zones have been developed in China. These vibration zones varying with net head, i.e., head-sensitive, seriously challenge the hydro unit commitment (HUC). This paper presents a MILP model for HUC with a head-sensitive reservoir and multiple vibration zones. The focus of the study is mainly on two net head related constraints, namely the unit performance curves and multiple vibration zones. These constraints are linearized through the use of binary 0-1 integer variables. The practical behavior of the MILP model is demonstrated using real-world case studies. The results demonstrate that the proposed model is computationally efficient and suitable for large hydropower plants with multiple vibration zones, showing its potential practicability and validity for solving the HUC problem.

关键词： Hydro unit commitment hydropower head effect mixed-integer linear programming multiple vibration zones

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An adjustable robust optimization approach to scheduling of continuous industrial processes providing interruptible load

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COMPUTERS & CHEMICAL ENGINEERING 2016年 86卷 106-119页

作者： Zhang, Qi Morari, Michael F. Grossmann, Ignacio E. Sundaramoorthy, Arul Pinto, Jose M. Carnegie Mellon Univ Dept Chem Engn Ctr Adv Proc Decis Making Pittsburgh PA 15213 USA Swiss Fed Inst Technol Zurich ETHZ Dept Chem & Bioengn CH-8092 Zurich Switzerland Praxair Inc Business & Supply Chain Optimizat R&D Tonawanda NY 14150 USA Praxair Inc Business & Supply Chain Optimizat R&D Danbury CT 06810 USA

To ensure the stability of the power grid, backup capacities are called upon when electricity supply does not meet demand due to unexpected changes in the grid. As part of the demand response efforts in recent years, large electricity consumers are encouraged by financial incentives to provide such operating reserve in the form of load reduction capacities (interruptible load). However, a major challenge lies in the uncertainty that one does not know in advance when load reduction will be requested. In this work, we develop a scheduling model for continuous industrial processes providing interruptible load. An adjustable robust optimization approach, which incorporates recourse decisions using linear decision rules, is applied to model the uncertainty. The proposed model is applied to an illustrative example as well as a real-world air separation case. The results show the benefits from selling interruptible load and the value of considering recourse in the decision-making. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Production scheduling Demand response Interruptible load Adjustable robust optimization mixed-integer linear programming

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Optimal Restoration of Distribution Systems with Active Participation of Volatile Renewable Generators

Optimal Restoration of Distribution Systems with Active Part...

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IEEE Manchester PowerTech

作者： Raoofsheibani, Davood Hinkel, Philipp Ostermann, Martin Wellssow, Wolfram H. Nemati, Mohsen Neisius, Hans-Theo Univ Kaiserslautern Inst Energy Syst & Energy Management Kaiserslautern Germany Siemens AG Digital Grid Software & Solut Energy Management Div Nurnberg Germany

ISBN: (纸本)9781509042371

A strategy for a secure power system restoration (PSR) at distribution levels with active participation of volatile but remotely-controllable (RC) renewable energy source (RES) generators is proposed. It is based on an Awareness Tool as well as a Decision-Support Tool to assist distribution system operators (DSO) in their decision-making process during PSR. The Awareness Tool determines the active power peaks at and after the instant of re-energization for each and every substation of a distribution grid where loads and volatile RES generations are fully mixed. The Decision-Support Tool utilizes the mixed-integer linear programming (MILP) technique to determine network clusters with the help of the Awareness Tool results. The objective is to create different load-dominant areas (load clusters) at the DSO level which consume smooth active powers from the transmission levels for a specific forward-looking time horizon.

关键词： Control center applications distribution system operator mixed-integer linear programming power system restoration renewable energy source

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Unit Commitment With Continuous-Time Generation and Ramping Trajectory Models

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第4期31卷 3169-3178页

作者： Parvania, Masood Scaglione, Anna Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Arizona State Univ Sch Elect Comp & Energy Engn Tempe AZ 85287 USA

There is increasing evidence of shortage of ramping resources in the real-time operation of power systems. To explain and remedy this problem systematically, in this paper we take a novel look at the way the day-ahead unit commitment (UC) problem represents the information about load, generation and ramping constraints. We specifically investigate the approximation error made in mapping of the original problem, that would decide the continuous-time generation and ramping trajectories of the committed generating units, onto the discrete-time problem that is solved in practice. We first show that current practice amounts to approximating the trajectories with linear splines. We then offer a different representation through cubic splines that provides physically feasible schedules and increases the accuracy of the continuous-time generation and ramping trajectories by capturing sub-hourly variations and ramping of load in the day-ahead power system operation. The corresponding day-ahead UC model is formulated as an instance of mixed-integer linear programming (MILP), with the same number of binary variables as the traditional UC formulation. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day-ahead and real-time operation cost, and the number of events of ramping scarcity in the real-time operations.

关键词： Continuous-time function space generation trajectory mixed-integer linear programming ramping trajectory unit commitment

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Short-term scheduling of multiple source pipelines with simultaneous injections and deliveries

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COMPUTERS & OPERATIONS RESEARCH 2016年 73卷 27-42页

作者： Mostafaei, Hossein Castro, Pedro M. Ghaffari-Hadigheh, Alireza Azarbaijan Shahid Madani Univ Dept Appl Math Tabriz Iran Univ Lisbon Ctr Matemat Aplicacooes Fundamentais & Invest Ope Fac Ciencias P-1749016 Lisbon Portugal

This paper addresses the optimal scheduling of straight pipelines featuring multiple intermediate nodes acting as dual-purpose stations, with a continuous-time mixed-integer linear programming formulation partly derived from Generalized Disjunctive programming. The new model allows for an intermediate station to act as an output and input terminal at the same time so as to reduce the number of segment switches between active and idle, and consequently decrease operating costs. Contrary to previous approaches, decisions related to batch sizing, batch sequencing and timing are determined in a single step. Several examples of growing complexity are solved to illustrate the effectiveness and computational advantage of the proposed model in both solution quality and CPU time. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Mathematical modeling mixed-integer linear programming Generalized disjunctive programming Multiproduct pipelines

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Arterial traffic signal optimization: A person-based approach

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2016年 66卷 27-47页

作者： Christofa, Eleni Ampountolas, Konstantinos Skabardonis, Alexander Univ Massachusetts Dept Civil & Environm Engn Amherst MA 01003 USA Univ Glasgow Sch Engn Glasgow G12 8LT Lanark Scotland Univ Calif Berkeley Inst Transportat Studies Berkeley CA 94720 USA

This paper presents a real-time signal control system that optimizes signal settings based on minimization of person delay on arterials. The system's underlying mixed integer linear program minimizes person delay by explicitly accounting for the passenger occupancy of autos and transit vehicles. This way it can provide signal priority to transit vehicles in an efficient way even when they travel in conflicting directions. Furthermore, it recognizes the importance of schedule adherence for reliable transit operations and accounts for it by assigning an additional weighting factor on transit delays. This introduces another criterion for resolving the issue of assigning priority to conflicting transit routes. At the same time, the system maintains auto vehicle progression by introducing the appropriate delays associated with interruptions of platoons. In addition to the fact that it utilizes readily available technologies to obtain the inputs for the optimization, the system's feasibility in real-world settings is enhanced by its low computation time. The proposed signal control system is tested on a four-intersection segment of San Pablo Avenue arterial located in Berkeley, California. The findings show the system's capability to outperform pretimed (i.e., fixed-time) optimal signal settings by reducing total person delay. They have also demonstrated its success in reducing bus person delay by efficiently providing priority to transit vehicles even when they travel in conflicting directions. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Person-based traffic signal control Transit signal priority Person delay mixed-integer linear programming Conflicting transit routes Pairwise signal optimization

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Decomposition algorithms for optimizing multi-server appointment scheduling with chance constraints

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MATHEMATICAL programming 2016年第1期157卷 245-276页

作者： Deng, Yan Shen, Siqian Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

This paper investigates a problem of scheduling appointments with random service durations on multiple servers with operating time limits. We minimize the cost of operating servers and serving appointments, subject to a joint chance constraint limiting the risk of server running overtime. With finite samples of random service time, we consider a mixed-integer linear programming extended formulation and propose a two-stage decomposition framework with cutting planes. The first stage considers a relaxed master problem as a variant of the chance-constrained binary packing problem discussed in Song et al. (INFORMS J Comput 26(4):735-747, 2014), which packs appointments into servers under chance-constrained server overtime. Given appointment-to-server assignments, the second stage seeks feasible schedules on individual servers. We propose strengthening, bounding, and branch-and-cut methods for computing problems in both stages. Via testing instances with diverse sizes, we compare different decomposition schemes. In particular, we demonstrate the efficacy of our branch-and-cut algorithm that incorporates server-based decomposition for optimizing the problem.

关键词： Chance-constrained programming Service scheduling mixed-integer linear programming Decomposition Branch-and-cut

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A Three-phase Unsymmetrical Distribution Power Flow Solution Based on Symmetrical Component Theory

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JOURNAL OF ELECTRICAL SYSTEMS 2017年第4期13卷 742-751页

作者： Li, Hongwei Xiang, Meiling Jiang, Jiayan Shen, Xie Southwest Petr Univ Sch Elect Informat Engn Chengdu 610500 Sichuan Peoples R China

Aiming at the three-phase unsymmetrical distribution network, this paper proposed a three-sequence components decoupled power flow method based on the node-branch incidence matrix. The three-sequence decoupled models were established based on symmetrical component theory by utilizing the weakly coupling feature of three-phase unsymmetrical distribution networks. The algorithm simplifies the complexity of the distribution network and reduces the dimensions of the matrix, so the calculation process is relatively simple. Moreover, a new approach deal with the PV nodes was developed based on the assumption that the positive-sequence voltage magnitude of PV node is sustained at a given fixed value. The formula to calculate the reactive power increment for each PV node was derived based on Thevenin equivalent circuit theory. The test results show that the proposed method and PV nodes processing approach have better convergence and faster calculating speed.

关键词： Electricity spot market bilateral contracts thermal unit commitment mixed-integer linear programming

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Operation management of residential energy-supplying networks based on optimization approaches

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APPLIED ENERGY 2016年 183卷 340-357页

作者： Wakui, Tetsuya Kawayoshi, Hiroki Yokoyama, Ryohei Aki, Hirohisa Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan Natl Inst Adv Ind Sci & Technol Res Inst Sci Safety & Sustainabil 1-1-1 Umezono Tsukuba Ibaraki 3058568 Japan

An operation management system for residential energy-supplying networks using multiple cogeneration units was developed by hierarchically integrating energy demand prediction, operational planning, and operational control, using optimization approaches. The energy demand for multiple dwellings was predicted by support vector regression with information on occupant behavior as well as forecasted weather and energy demand history. mixed-integer linear programming was employed for the operational planning of the cogeneration units to the predicted energy demand. The energy demand prediction and operational planning were updated using a variable frequency receding horizon approach. This was done to limit the unnecessary shutdown and start-up of the cogeneration units and to reduce the influences of prediction errors for energy demand. Regarding the operational control, the actual on-off schedule of the cogeneration units conformed to the operational planning result. Additionally, the power and heat outputs of the cogeneration units and the heat supply from the storage tanks were modulated in response to the actual energy demand, based on predefined rules. The developed operation management system was applied to annual operation simulation of a residential energy-supplying network consisting of four cogeneration units using fuel cells in a housing complex. For comparative analysis, history-based approaches for energy demand prediction and separate operation of each cogeneration unit were also considered. The results revealed the effectiveness of the developed operation management system as well as the high energy-saving performance of the residential energy-supplying network. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Energy management Microgrid Cogeneration Model predictive control Support vector regression mixed-integer linear programming

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