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Optimal switchable load sizing and scheduling for standalone renewable energy systems

SOLAR ENERGY 2017年 144卷 707-720页

作者： Habib, Abdulelah H. Disfani, Vahid R. Kleissl, Jan de Callafon, Raymond A. Univ Calif San Diego Dept Mech & Aerosp Engn 9500 Gilman Dr MC 0411 La Jolla CA 92093 USA

The variability of solar energy in off-grid systems dictates the sizing of energy storage systems along with the sizing and scheduling of loads present in the off-grid system. Unfortunately, energy storage may be costly, while frequent switching of loads in the absence of an energy storage system causes wear and tear and should be avoided. Yet, the amount of solar energy utilized should be maximized and the problem of finding the optimal static load size of a finite number of discrete electric loads on the basis of a load response optimization is considered in this paper. The objective of the optimization is to maximize solar energy utilization without the need for costly energy storage systems in an off-grid system. Conceptual and real data for solar photovoltaic power production provides the power input to the off-grid system. Given the number of units, the following analytical solutions and computational algorithms are proposed to compute the optimal load size of each unit: mixed-integer linear programming and constrained least squares. Based on the available solar power profile, the algorithms select the optimal on/off switch times and maximize solar energy utilization by computing the optimal static load sizes. The effectiveness of the algorithms is compared using one year of solar power data from San Diego, California and Thuwal, Saudi Arabia. It is shown that the annual system solar energy utilization is optimized to 73% when using two loads and can be boosted up to 98% using a six load configuration. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Inequality-constrained least square Load management mixed-integer linear programming Off-grid solar energy

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Two-phase decomposition method for the last train departure time choice in subway networks

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2017年第Oct.期104卷 568-582页

作者： Kang, Liujiang Meng, Qiang Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

An urban subway network with a number of service lines forms the backbone of the public transport system for a large city of high population, such as Singapore, Hong Kong and Beijing. Passengers in these large cities heavily rely on urban subway networks for their daily life. The departure times of the last trains running on different lines of an urban subway network should be well coordinated in order to serve more passengers who can successfully transfer from one line to another, which is referred to as the last train departure time choice problem. This study aims to develop a global optimization method that can solve the last train departure time choice problem for large-scale urban subway networks. To do so, it first formulates a mixed-integer linear programming (MILP) model by introducing auxiliary binary and integer decision variables. For the real-life and large-scale instances, however, the formulated MILP model cannot be solved directly by the global optimization methods such as branch-and-bound algorithm invoked by CPLEX one of the powerful optimization solvers because of the instance sizes. An effective two-phase decomposition method is thus proposed to globally solve the large-scale problems by decomposing the original MILP into two MILP models with small sizes. Finally, a real case study from the Beijing subway network is conducted to assess the efficiency and applicability of the two-phase decomposition method and perform the necessary sensitivity analysis of the operational parameters involved in the last train departure time choice problem. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Urban subway networks Last train departure time choice mixed-integer linear programming Global optimization method Two-phase decomposition method

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Head Dependence of Pump-Storage-Unit Model Applied to Generation Scheduling

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IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第4期32卷 2869-2877页

作者： Chen, Cheng-Hung Chen, Nanming Luh, Peter B. Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 10607 Taiwan Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

This paper presents a head-dependent model for pump storage units (PSUs) in a power system for short-term generation scheduling over one week. A hydraulic system with upper and lower reservoirs, each having their own in and out river flows, is considered. Hydraulic conditions, as well as head effects, are explicitly modeled for both generation and pumping modes of the PSUs. The problem is solved by the branch-and-cut method to obtain a near-optimal solution. Test results of an hourly generation schedule, including comparisons of pump efficiencies, hydraulic conditions, and operating costs of the PSUs for a real power system, are presented.

关键词： Discharge generation scheduling head effect mixed-integer linear programming pump storage unit reservoir

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Optimal shale oil and gas investments in the United States

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ENERGY 2017年 141卷 398-422页

作者： Tan, Siah Hong Barton, Paul I. MIT Proc Syst Engn Lab 77 Massachusetts Ave Cambridge MA 02139 USA

We present a comprehensive supply chain optimization model to determine optimal shale oil and gas infrastructure investments in the United States. The model encompasses multiple shale plays, commodities, plant locations, conversion technologies, transportation modes and both local and foreign markets. The dynamic evolution of supply, demand and price parameters and the uncertainty in parameter realizations are fully taken into account. Imposing two different scenario sets over a time horizon of twenty-five years, the model maximizes the expected net present value of the entire undertaking. We analyze the features of the optimal infrastructure investments and associated operating decisions, perform case studies which highlight the importance of incorporating uncertainty into the model and analyze the stability of the stochastic solutions as the degree of uncertainty changes. The overall opportunity set of investments is sparse, and there is a tendency for over-investment in new liquefied natural gas capacity when the uncertainties in future oil prices are not taken fully into account. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Shale oil and gas Infrastructure investments Supply chain optimization Stochastic programming mixed-integer linear programming

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Dynamic Ramping Model Including Intraperiod Ramp-Rate Changes in Unit Commitment

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2017年第1期8卷 43-50页

作者： Correa-Posada, Carlos M. Morales-Espana, German Duenas, Pablo Sanchez-Martin, Pedro XM Medellin 55422 Colombia Delft Univ Technol Dept Software & Comp Technol NL-2628 CD Delft Netherlands MIT 77 Massachusetts Ave Cambridge MA 02139 USA Comillas Pontifical Univ ICAI Sch Engn Technol Res Inst Madrid 28015 Spain

The growing increase of renewable generation worldwide is posing new challenges for a secure, reliable, and economic operation of power systems. In order to face the uncertain and intermittent production of renewable sources, operating reserves must be allocated efficiently and accurately. Nowadays, these reserves are mainly assigned to thermal units, especially gas-fired generators, due to their operation flexibility and fast response. However, the ramping capabilities of these units define the grade of flexibility offered to the system operation. In practical applications, ramping limits are dynamic, i.e., they are a function of the unit's generating output. Omitting this feature leads to suboptimal or even infeasible reserve allocations, thus increasing not only operating reserve requirements but also transactions in real-time balancing markets needed to back up deviations of renewable generation. This paper contributes with a mixed-integer linear programming model for units' dynamic ramping allowing intraperiod changes in the unit commitment problem. As a result, operating reserves are better allocated and the units' flexibility is managed more efficiently than traditional ramping models found in the literature. Different case studies illustrate the functioning and benefits of the proposed formulation.

关键词： Dynamic ramping mixed-integer linear programming reserves unit commitment thermal units

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A multi-lateral trading model for coupled gas-heat-power energy networks

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APPLIED ENERGY 2017年 200卷 180-191页

作者： Chen, Yue Wei, Wei Liu, Feng Mei, Shengwei Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

The proliferation of cogeneration technology and the need for more resilient energy utilization inspire the emerging trend of integration of multi-resource energy systems, in which natural gas, heat, and electricity are produced, delivered, converted, and distributed more efficiently and flexibly. The increasing interactions and interdependencies across heterogenous physical networks impose remarkable challenges on the operation and market organization. This paper envisions the market trading scheme in the network-coupled natural gas system, district heating system, and power system. Based on the physical energy flow models of each system and their interdependency, a multi-lateral trading gas-heat-power (MLT-GHP) model is suggested, and a mixed-integer linear programming based two-phase algorithm is developed to find the market equilibrium. Case studies on two testing systems demonstrate the effectiveness of the proposed model and method, showing that the multi-lateral trading essentially results in market competition that orientates reasonable energy prices. Some prospects for future researches are also summarized. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Integrated energy networks Market equilibrium mixed-integer linear programming Multi-resource energy market

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Optimal dynamic logistic planning of the supply chain of a gas condensate stabilization plant

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THEORETICAL FOUNDATIONS OF CHEMICAL ENGINEERING 2017年第4期51卷 392-403页

作者： Meshalkin, V. P. Rakitina, O. V. Russian Acad Sci Kurnakov Inst Gen & Inorgan Chem Leninskii Pr 31 Moscow 119991 Russia Mendeleev Russian Univ Chem Technol Miusskaya Pl 9 Moscow 125047 Russia

The management of the economy and the mathematical formulation of the problem of optimal dynamic (multiperiod) logistic planning of the initial and modified supply chain of a gas condensate stabilization plant has been suggested in the form of a multidimensional mixed-integer linear programming problem. An interactive procedure for solving this problem has been developed using the Oracle Strategic Network Optimization software suite. Optimal logistic planning parameters have been calculated for the new modified supply chain with the commissioning of a new plant for processing a wide fraction of light hydrocarbons.

关键词： gas condensate logistic planning mathematical problem formulation multiperiod (dynamic) planning optimization processing of hydrocarbons natural gas mixed-integer linear programming supply chain

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Partitioning of Intelligent Buildings for Distributed Contaminant Detection and Isolation

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2017年第2期1卷 72-86页

作者： Kyriacou, Alexis Timotheou, Stelios Michaelides, Michalis P. Panayiotou, Christos Polycarpou, Marios Univ Cyprus KIOS Res Ctr Intelligent Syst & Networks Dept Elect & Comp Engn CY-1678 Nicosia Cyprus Cyprus Univ Technol Dept Elect Engn Comp Engn & Informat CY-3036 Limassol Cyprus

Intelligent buildings are responsible for ensuring indoor air quality for their occupants under normal operation as well as under possibly harmful contaminant events. An emerging environmental application involves the monitoring of intelligent buildings against harmful events by incorporating various sensing technologies and using sophisticated algorithms to detect and isolate such events. In this context, both centralized and distributed approaches have been proposed, with the latter having significant benefits in terms of complexity, scalability, reliability, and performance. This paper considers the automatic partitioning of the building into subsystems, which enables the distributed simulation, modeling, analysis, and management of the intelligent building while ensuring the effective detection and isolation of contaminants in the building interior. Specifically, we develop both a high-quality heuristic algorithm and an optimal mixed integer linear programming (MILP) formulation for the building partitioning problem. The MILP formulation is based on graph partitioning techniques, while the heuristic is based on matrix clustering techniques. Both approaches partition the building into subsystems while ensuring 1) maximum decoupling between the various subsystems, 2) strong connectivity between the zones of each subsystem, and 3) control of the size of the subsystems with respect to the number of allocated zones. A combination of the two approaches is also proposed for reconfiguring an initial partitioning composition in real time in order to accommodate partitioning needs that arise from dynamic system changes.

关键词： Building partitioning contaminant detection and isolation distributed monitoring algorithms mixed-integer linear programming matrix reordering techniques online optimization

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Real-time airport surface movement planning: Minimizing aircraft emissions

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2017年 79卷 224-241页

作者： Evertse, C. Visser, H. G. Delft Univ Technol Fac Aerosp Engn Delft Netherlands

This paper presents a study towards the development of a real-time taxi movement planning system that seeks to optimize the timed taxiing routes of all aircraft on an airport surface, by minimizing the emissions that result from taxiing aircraft operations. To resolve this online planning problem, one of the most commonly employed operations research methods for large-scale problems has been successfully used, viz., mixed-integer linear programming (MILP). The MILP formulation implemented herein permits the planning system to update the total taxi planning every 15 s, allowing to respond to unforeseen disturbances in the traffic flow. Extensive numerical experiments involving a realistic (hub) airport environment bear out that an estimated environmental benefit of 1-3 percent per emission product can be obtained. This research effort clearly demonstrates that a surface movement planning system capable of minimizing the emissions in conjunction with the total taxiing time can be beneficial for airports that face dense surface traffic and stringent environmental requirements. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Airport surface movement planning Emissions mixed-integer linear programming

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RETRACTED: Optimal transmission switching in the stochastic linearised SCUC for uncertainty management of the wind power generation and equipment failures (Retracted Article)

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第10期11卷 2664-2676页

作者： Nikoobakht, Ahmad Aghaei, Jamshid Mardaneh, Mohammad Higher Educ Ctr Eghlid Eghlid Iran Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

This study recommends a stochastic optimisation model for the security-constrained unit commitment (SCUC), which incorporates the optimal transmission switching (OTS) for managing the uncertainty of wind power generation and equipment failures, i.e. outage unit/line. Also, this study presents a technique in stochastic SCUC model with the OTS action using the AC optimal power flow (AC-OPF). The AC-OPF provides a more accurate picture of power flow in the power system compared to the DC optimal power flow that is usually considered in the literature for the stochastic SCUC models and OTS action. While the stochastic SCUC model with the OTS action based on the AC-OPF is a mixed-integer non-linear programming model, this study transforms it into a mixed-integer linear programming (MILP) model. The MILP approach uses a piecewise linear model of the AC-OPF, which allows the reactive power and voltage to be considered directly in power flow model. This transformation guarantees achievement of a global optimal solution by the existing software and algorithms. The proposed stochastic SCUC problem is evaluated on the 6-bus and IEEE 118-bus test systems in pre- and post-transmission switching action. Obtained results demonstrate the effectiveness of the proposed model.

关键词： load flow IEEE 118-bus test systems uncertainty management OTS equipment failures piecewise linear model optimal transmission switching power generation dispatch wind power generation integer programming IEEE 6-bus test systems linear programming reactive voltage post-transmission switching action reactive power pre-transmission switching action stochastic optimisation model MILP security-constrained unit commitment wind power mixed-integer nonlinear programming nonlinear programming piecewise linear techniques stochastic linearised SCUC AC optimal power flow power generation scheduling mixed-integer linear programming AC-OPF

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