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Possibility of the most cost efficient choice: A divided process approach to method and location selection for municipal solid waste management

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WASTE MANAGEMENT & RESEARCH 2014年第11期32卷 1073-1082页

作者： Korucu, M. Kemal Cihan, Ahmet Alkan, Atakan Ozbay, Ismail Karademir, Aykan Aladag, Zerrin Kocaeli Univ Dept Environm Engn TR-41380 Kocaeli Turkey Kocaeli Univ Dept Ind Engn TR-41380 Kocaeli Turkey

As studies on municipal solid waste management increased in recent years, many new mathematical models and approaches with a focus on determining the best treatment and disposal scenario were developed and applied. In this study, a mixed integer linear programming model was developed to be used as a facilitative tool for the cost minimisation of municipal solid waste management practices. Since municipal solid waste mass is a mixed composition of various types of waste components with different physical and chemical properties, the model was designed to include all the suitable treatment and disposal methods for these different waste components. The method alternatives with multiple waste inputs, such as aerobic biological treatment and the thermal processes, were divided into a number of inputs to remove their non-linear structures. This way, linear programming could be used, and the linear cost function could be minimised over a set of linear constraints with integer variables. The model was applied to the city of Kocaeli, which will require a new waste management application in the future, beginning from 2015. The results obtained for different haul distance constraints in the study area were presented and assessed. The results showed that all the information required for a comprehensive management task could be modelled by a linear optimisation model with a divided processes approach easily.

关键词： Divided process approach decision making mixed integer linear programming method selection municipal solid wastes

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Optimizing cable harvesting layout when using variable-length cable roads in central Europe

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CANADIAN JOURNAL OF FOREST RESEARCH 2014年第8期44卷 949-960页

作者： Bont, Leo Heinimann, Hans Rudolf Church, Richard L. Swiss Fed Inst Technol Inst Terr Ecosyst CH-8092 Zurich Switzerland Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93106 USA

One of the classic operations problems in forest management is the layout of a harvesting system. This paper addresses the design of a harvesting system in areas characterized by steep slopes requiring cable-based harvesting. Layout optimization often involves numerous potential cable alignments and a small number of potential landings. In this paper we develop a model that addresses steep slope conditions found in central Europe that involve a large number of potential landings and cable alignments. In addition we extend existing work by considering variable-length alternatives for each feasible cable alignment. We construct three models, one for single-length cable options and two for variable-length alternatives and test their efficacy in solving 18 different harvesting area problems. We show that one of the variable-length alternative models can be solved in computer times that are competitive with the single-length option model. Overall, the savings that can be attributed to variable-length options are modest, but the alignments found by the variable-length options models are more realistic from forest engineers' points of view, which will aid in its use and adoption.

关键词： forest harvesting cable layout optimization multi-length cable alternatives mixed integer linear programming alpine forests

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Flexible Operation Scheduling of a Power Plant Integrated with PCC Processes under Market Dynamics

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2014年第19期53卷 8132-8146页

作者： Khalilpour, Rajab Univ Sydney Sch Chem & Biomol Engn Sydney NSW 2006 Australia

Operation scheduling of a power plant under market dynamics is a complex problem. It becomes more sophisticated once the plant is integrated with carbon-capture processes as well as the carbon market. This article addresses the problem of a Rankine power plant integrated with one or more solvent-based postcombustion carbon-capture (PCC) process train(s). The company desires to know when and how to operate the installed PCC process trains(s) along with the power plant under the projected carbon, and electricity prices while satisfying the emissions-reduction requirements. We have developed a multiperiod mixed-integer linear program (MILP) with the objective of maximizing the total income. The model is capable of defining the optimal operating capacities of PCC train(s) and power plant at each period over the planning horizon. The PCC trains are, however, allowed to shut down at any time if the market conditions favor it. The model suggests buying or selling carbon permits over the planning horizon when either is more economical. This decision-support program enables the company to implement the most efficient electricity-generation and carbon-management strategy while achieving the goal of maximum income.

关键词： CARBON sequestration POWER plants PRODUCTION scheduling COMBUSTION mixed integer linear programming DECISION support systems

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A General Modeling Framework for the Long-Term Scheduling of Multiproduct Pipelines with Delivery Constraints

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2014年第17期53卷 7029-7042页

作者： Mostafaei, Hossein Hadigheh, Alireza Ghaffari Azarbiajan Shahid Madani Univ Dept Appl Math Tabriz Iran

Common carrier pipelines are one of the most economic modes for transportation of petroleum refined products over land, especially when huge amounts of these products have to be pumped toward long-distance terminals. This paper introduces a novel mixed integer linear programming (MILP)-based approach for the long-term scheduling of a real world multiproduct pipeline connecting a unique refinery to several distribution centers. This approach allows consideration of multiple due dates for demands at period ends, flow rate limitation on pipeline segments, and simultaneous deliveries at distribution centers. The proposed model results in substantial reduction in pump operation and maintenance costs in comparison with the available models. Computational results and data are reported.

关键词： COMPUTER simulation PIPELINES PETROLEUM -- Transportation mixed integer linear programming WAREHOUSES COST effectiveness COMPARATIVE studies

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Share-of-Surplus Product Line Optimisation with Price Levels

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-8页

作者： Luo, X. G. Zhang, Z. C. Kwong, C. K. Tang, J. F. Northeastern Univ State Key Lab Synthet Automat Proc Ind Dept Syst Engn Shenyang 110004 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Kowloon 999077 Hong Kong Peoples R China

Kraus and Yano ( 2003) established the share-of-surplus product line optimisation model and developed a heuristic procedure for this nonlinear mixed-integer optimisation model. In their model, price of a product is defined as a continuous decision variable. However, because product line optimisation is a planning process in the early stage of product development, pricing decisions usually are not very precise. In this research, a nonlinear integer programming share-of-surplus product line optimization model that allows the selection of candidate price levels for products is established. The model is further transformed into an equivalent linear mixed-integer optimisation model by applying linearisation techniques. Experimental results in different market scenarios show that the computation time of the transformed model is much less than that of the original model.

关键词： PRODUCT lines MATHEMATICAL optimization PRICE levels HEURISTIC algorithms NEW product development mixed integer linear programming

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An Optimal Energy Storage Control Strategy for Grid-connected Microgrids

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IEEE TRANSACTIONS ON SMART GRID 2014年第4期5卷 1785-1796页

作者： Malysz, Pawel Sirouspour, Shahin Emadi, Ali McMaster Univ McMaster Inst Automot Res & Technol MacAUTO Hamilton ON L8S 4K1 Canada McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada McMaster Univ Dept Mech Engn Hamilton ON L8S 4K1 Canada

This paper presents an online optimal energy/power control method for the operation of energy storage in grid-connected electricity microgrids. The approach is based on a mixed-integer-linear-program optimization formulated over a rolling horizon window, considering predicted future electricity usage and renewable energy generation. Performance objectives include electricity usage cost, battery operation costs, and utility oriented goals related to the peak demand and load smoothing. A robust counterpart formulation of the optimization problem is also proposed to handle uncertainty in energy demand/generation prediction in a computationally efficient way. Further reduction in the computations is achieved by employing variable time steps and relaxing binary constraints. A series of simulations demonstrate the effectiveness of various features of the proposed energy/power management methodology in different scenarios.

关键词： Adaptive control battery energy management microgrid mixed integer linear programming robust optimization rolling horizon smartgrid solar power wind power

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A Spatial multi-period long-term energy planning model: A case study of the Greek power system

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APPLIED ENERGY 2014年 115卷 456-482页

作者： Koltsaklis, Nikolaos E. Dagoumas, Athanasios S. Kopanos, Georgios M. Pistikopoulos, Efstratios N. Georgiadis, Michael C. Aristotle Univ Thessaloniki Dept Chem Engn Thessaloniki 54124 Greece Elect Market Operator SA Piraeus 18545 Greece Univ Piraeus Dept Int & European Studies Piraeus 18534 Greece Univ London Imperial Coll Sci Technol & Med Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England

This paper presents a mixed-integer linear programming (MILP) model for the optimal long-term energy planning of a (national) power generation system. In order to capture more accurately the spatial and technical characteristics of the problem, the underlying geographical area (country) is divided into a number of individual networks that interact with each other. The proposed model determines the optimal planning of the power generation system, the selection of the power generation technologies, the type of fuels and the plant locations so as to meet the expected electricity demand, while satisfying environmental constraints in terms of CO2 emissions. Furthermore, the suggested model determines the electricity imports from neighbouring countries, the electricity transmission as well as the transportation of primary energy resources between domestic networks. A real case study concerning the Greek energy planning problem demonstrates the applicability of the proposed approach, which can provide policy makers with a systematic computer-aided tool to analyse various scenarios and technology options. Finally, a sensitivity analysis was conducted in order to capture the influence of some key parameters such as electricity demand, natural gas and CO2 emission price as well as wind power investment cost. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： mixed integer linear programming Energy systems engineering Generation expansion planning Power sector Carbon emissions

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Reliability assessment of incentive- and priced-based demand response programs in restructured power systems

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 56卷 83-96页

作者： Nikzad, Mehdi Mozafari, Babak Islamic Azad Univ Dept Elect Engn Islamshahr Branch Tehran Iran Islamic Azad Univ Dept Elect & Comp Engn Sci & Res Branch Tehran Iran

Fostering demand response (DR) through incentive-based and priced-based programs has always great impact on improvement of efficiency and reliability of the power systems. The use of DR lowers undesirable effects of failures that usually impose financial costs and inconveniences to the customers. Hence, quantifying the impact of demand response programs (DRPs) on reliability improvement of the restructured power systems is an important challenge for the independent system operators and the regional transmission organizations. In this paper, the DR model which treats consistently the main characteristics of the demand curve is developed for modeling. In proposed model, some penalties for customers in case of no responding to load reduction and incentives for customers who respond to reducing their loads are considered. In order to make analytical evaluation of the reliability, a mixed integer DC optimal power flow is proposed by which load curtailments and generation re-dispatches for each contingency state are determined. Both transmission and generation failures are considered in contingency enumeration. The proposed technique is modeled in the GAMS software and solved using CPLEX as a powerful mixed integer linear programming (MILP) solver. Both supply-side reliability for generation companies and demand-side reliability for customers are calculated using this technique. In order to simulate customers' behavior to different DRPs in a real power network, the proposed DR model is used and evaluated over Iranian power network. In order to investigate the reliability effects of DRPs based on proposed reliability method. DRPs based on the DR model are implemented over the IEEE RTS 24-bus test system, and reliability indices for generation companies, transmission network and customers are calculated. Using proposed performance index, the priority of the DRPs are determined from view point of customers, generation companies, transmission network and the whole system in I

关键词： Demand response programs Analytical reliability evaluation techniques mixed integer linear programming Expected energy not supplied Expected interruption cost

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Transportation Network Design considering Morning and Evening Peak-Hour Demands

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-10页

作者： Wang, Hua Xiao, Gui-Yuan Zhang, Li-Ye Ji, Yangbeibei Tongji Univ Sch Econ & Management Shanghai 200096 Peoples R China Guilin Univ Technol Coll Civil & Architectural Engn Guilin 541004 Peoples R China Changsha Univ Sci & Technol Sch Traff & Transportat Engn Changsha 410076 Hunan Peoples R China Shanghai Univ Sch Management Shanghai 200444 Peoples R China

Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

关键词： TRANSPORTATION SUPPLY & demand PROBLEM solving mixed integer linear programming TRAFFIC patterns

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A framework for home energy management and its experimental validation

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ENERGY EFFICIENCY 2014年第6期7卷 1013-1052页

作者： Barbato, Antimo Capone, Antonio Carello, Giuliana Delfanti, Maurizio Falabretti, Davide Merlo, Marco Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy Politecn Milan Dipartimento Energia I-20133 Milan Italy

With the Smart Grid revolution and the increasing interest in renewable energy sources, the management of the electricity consumption and production of individual households and small residential communities is becoming an essential element of new power systems. The electric energy chain can greatly benefit from a flexible interaction with end-users based on the optimization of load profiles and the exploitation of local generation and energy storage. This paper proposes a framework for the development of a complete energy management system for individual residential units and small communities of domestic users, taking into account both the power system and the final users' perspectives. All the main elements of the framework are considered, and contributions are provided on the users' habits profiling, electricity generation forecast, energy load, and storage optimization. Specifically, we propose a linear regression model to predict the photovoltaic panels production, a stochastic method to forecast the home appliances usage, and two optimization models to optimize the electricity management of residential users with the goal of minimizing their bills. The study shows that it is possible to reduce the energy bill of residential users through the electricity optimization driven by dynamic energy prices. Moreover, remarkable improvements of the electric grid efficiency can be achieved with the cooperation among users, confirming that services for the coordination of the demand of groups of users allow huge benefits on the power system performance.

关键词： Smart grids Demand side management linear regression modeling Users profiling mixed integer linear programming Final user's awareness

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