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Optimised Heat Pump Management for Increasing Photovoltaic Penetration into the Electricity Grid

ENERGIES 2019年第8期12卷 1571页

作者： Sanchez, Cristian Bloch, Lionel Holweger, Jordan Ballif, Christophe Wyrsch, Nicolas EPFL Inst Microengn IMT Photovolta & Thin Film Elect Lab PV LAB Rue Maladiere 71b CH-2000 Neuchatel Switzerland CSEM PV Ctr Rue Jaquet Droz 1 CH-2000 Neuchatel Switzerland

Advanced control of heat pumps with thermal storage and photovoltaics has recently been promoted as a promising solution to help decarbonise the residential sector. Heat pumps and thermal storage offer a valuable flexibilisation mean to integrate stochastic renewable energy sources into the electricity grid. Heat pump energy conversion is nonlinear, leading to a challenging nonlinear optimisation problem. However, issues like global optimum uncertainty and the time-consuming methods of current nonlinear programming solvers draw researchers to linearise heat pump models that are then implemented in faster and globally convergent linear programming solvers. Nevertheless, these linearisations generate some inaccuracies, especially in the calculation of the heat pump's coefficient of performance (COP). In order to solve all of these issues, this paper presents a heuristic control algorithm (HCA) to provide a fast, accurate and near -optimal solution to the original nonlinear optimisation problem for a single-family house with a photovoltaic system, using real consumption data from a typical Swiss house. Results highlight that the HCA solves this optimisation problem up to 1000 times faster, yielding an operation that is up to 49% cheaper and self -consumption rates that are 5% greater than other nonlinear solvers. Comparing the performance of the HCA and the linear solver intlinprog, it is shown that the HCA provides more accurate heat pump control with an increase of up to 9% in system Operating Expense OPEX and a decrease of 8% in self -consumption values.

关键词： photovoltaics demand-side management air-to-water modulated heat pump thermal energy storage nonlinear programming mixed-integer linear programming heuristics optimal control problem

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Multistage Expansion Co-Planning of Integrated Natural Gas and Electricity Distribution Systems

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ENERGIES 2019年第6期12卷 1020-1020页

作者： Jooshaki, Mohammad Abbaspour, Ali Fotuhi-Firuzabad, Mahmud Moeini-Aghtaie, Moein Lehtonen, Matti Sharif Univ Technol Dept Elect Engn Tehran *** Iran Aalto Univ Dept Elect Engn & Automat Espoo 02150 Finland Sharif Univ Technol Energy Engn Dept Tehran *** Iran

This paper focuses on expansion co-planning studies of natural gas and electricity distribution systems. The aim is to develop a mixed-integer linear programming (MILP) model for such problems to guarantee the finite convergence to optimality. To this end, at first the interconnection of electricity and natural gas networks at demand nodes is modelled by the concept of energy hub (EH). Then, mathematical model of expansion studies associated with the natural gas, electricity and EHs are extracted. The optimization models of these three expansion studies incorporate investment and operation costs. Based on these separate planning problems, which are all in the form of mixed-integer nonlinear programming (MINLP), joint expansion model of multi-carrier energy distribution system is attained and linearized to form a MILP optimization formulation. The presented optimization framework is illustratively applied to an energy distribution network and the results are discussed.

关键词： co-planning studies electricity distribution system planning energy hub (EH) mixed-integer linear programming multi-carrier energy distribution systems natural-gas distribution system optimization

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Optimizing wind farm cable routing considering power losses

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第3期270卷 917-930页

作者： Fischetti, Martina Pisinger, David Vattenfall BA Wind Prod Torvet 424 DK-2800 Lyngby Denmark Tech Univ Denmark DTU Management Engn Operat Res Prod Torvet 424 DK-2800 Lyngby Denmark

Wind energy is the fastest growing source of renewable energy, but as wind farms are getting larger and more remotely located, installation and infrastructure costs are rising. It is estimated that the expenses for electrical infrastructures account for 15-30% of the overall initial costs, hence it is important to optimize their design. This paper focuses on offshore inter-array cable routing optimization. The routing should connect all turbines to one (or more) offshore substation(s) while respecting cable capacities, no-cross restrictions, connection-limits at the substation, and obstacles at the site. The objective is to minimize both the capital that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. We present a mixed-integer linear programming approach to optimize the routing using both exact and math-heuristic methods. In the power losses computation, wind scenarios are handled efficiently as part of the preprocessing, resulting in a model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our methods, proving that savings in the order of millions of Euro can be achieved. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Metaheuristics mixed-integer linear programming Matheuristics Wind farm optimization Benchmark instances

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System design and policy suggestion for reducing electricity curtailment in renewable power systems for remote islands

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APPLIED ENERGY 2018年 225卷 195-208页

作者： Song, Jeonghun Oh, Si-Doek Yoo, Yungpil Seo, Seok-Ho Paek, Insu Song, Yuan Song, Seung Jin Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea Blue Econ Strategy Inst Co Ltd Seoul 06721 South Korea Kangwon Natl Univ Dept Mechatron Engn Kangwon Do 24341 South Korea

In renewable power systems for remote islands, a significant amount of electricity is curtailed for power balance. This study examines the effect of reducing electricity curtailment on optimal renewable power system design for remote islands. A mixed-integer linear programming problem for obtaining the optimal design of remote renewable power systems is formulated with an additional constraint which limits the total electricity curtailment. For a parametric study, the problem is solved with various values of electricity curtailment limit, for four cases;two islands - one with a higher and the other with a lower capacity factor of wind turbines - in South Korea, and two renewable power penetrations - 60% and 90% - in the two islands. Variations in the optimal capacities of photovoltaic panels, wind turbines, and batteries for limited total electricity curtailment are examined for every case. Reasons of the variations are explained by an analysis on the temporal operation profiles of the remote renewable power systems. In addition, the appropriate upper limit of total electricity curtailment considering cost increment, normalized by the total electricity demand, is newly suggested as a function of renewable power penetration to guide policy design.

关键词： Renewable power systems Remote islands Electricity curtailment mixed-integer linear programming Optimal design Energy policy

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Market-Oriented Service Network Design When Demand is Sensitive to Congestion

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TRANSPORTATION SCIENCE 2018年第5期52卷 1253-1275页

作者： Schoen, Cornelia Saini, Pratibha Univ Mannheim Chair Serv Operat Management Business Sch D-68131 Mannheim Germany

In this paper, we present a market-oriented service network design model in which the seller's problem is to determine how many facilities to open, where to locate them, and which service capacities and service levels they should have to maximize overall profit. Our model explicitly considers the customers' facility choice as a function of typical choice determinants, such as travel distance and congestion delays (which are endogenously impacted by the seller's decisions) as well as other, exogenous factors such as price level and product variety. We relax the assumption adopted in many related works that the service provider has discretion as to the assignment of customers to facilities;instead, we allow customers to self-select based on their preferences for facility attributes according to an attraction-based choice model. Furthermore, we capture not only the effect of congestion on demand but also the reciprocal impacts of demand on congestion and service level by modeling each facility as an M/G/1 queue with service capacity as a decision variable. The resulting model represents a non-linear mixed-integer problem (MIP);however, we show that this problem can be linearized introducing several new continuous variables and constraints. To solve the linearized MIP to proven optimality or approximately, we develop an exact decomposition approach and heuristics. We report the performance testing of our approach with regard to run times and solution quality in an extensive computational experiment. A case study of the selection of locations for new convenience stores in Heidelberg, Germany illustrates the real-world applicability of the model using empirical market research data. An equivalent problem arises in a number of other applications, particularly in service shop industries such as restaurants and retailers. Surprisingly, profit maximization under customer-choice-driven behavior has rarely been considered as an objective in the related literature.

关键词： service network design customer choice M/G/1 queue mixed-integer linear programming

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Integration of smart grid technologies in stochastic multi-objective unit commitment: An economic emission analysis

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2018年第Sep.期100卷 565-590页

作者： Soltani, Z. Ghaljehei, M. Gharehpetian, G. B. Aalami, H. A. Amirkabir Univ Technol Elect Engn Dept Tehran Iran KN Toosi Univ Technol Elect Engn Dept Tehran Iran Eyvanekey Univ Elect Engn Dept Eyvanki Iran

This paper proposes a stochastic multi-objective unit commitment (SMOUC) problem incorporating smart grid technologies (SGTs), namely, plug-in electric vehicles (PEVs), demand response programs (DRPs), compressed air energy storage (CAES) units, and renewable distributed generations (DGs). An economic emission analysis of the proposed SMOUC problem with the SGTs is carried out to minimize the total expected operation cost and emission using a new mixed-integer linear programming (MILP) method. A two-stage stochastic programming method is used for dealing with the uncertain nature of power generation from the renewable DGs. Lexicographic optimization in combination with hybrid augmented-weighted c-constraint method are employed to obtain Pareto optimal solutions of the SMOUC problem, and a fuzzy decision making is applied to select the most preferred non-dominated solution. Besides, mathematical modeling of responsive loads can help the independent system operator (ISO) to use a conservative and reliable model to have lower error in load curve characteristic estimation, such as variation in peak load. In this regard, this paper also contributes to the existing body of knowledge by developing linear and nonlinear economic models of price responsive loads for time-based DRPs (TBDRPs), as well as voluntary and mandatory incentive-based DRPs (IBDRPs) based on the customer's behavior (CB) concept and price ratio (PR) parameter. Also, new mathematical indices are proposed to choose the most conservative and reliable economic model of price responsive loads. Moreover, different widely used DRPs are analyzed and prioritized using the strategy success index (SSI) from the ISO viewpoint to determine the most effective DRP which has more coordination with the SGTs. The proposed MILP-based SMOUC problem with integrated SGTs, is applied to IEEE 10-unit test system and is implemented in General Algebraic Modeling System (GAMS) environment. Simulation analyses demonstrate the effec

关键词： Unit commitment Multi-objective optimization Two-stage stochastic programming method Uncertainty Smart grid technologies Demand response programs mixed-integer linear programming

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A hybrid MILP and IPM approach for dynamic economic dispatch with valve-point effects

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2018年 97卷 290-298页

作者： Pan, Shanshan Jian, Jinbao Yang, Linfeng Guangxi Univ Coll Elect Engn Nanning 530004 Peoples R China Yulin Normal Univ Guangxi Coll & Univ Key Lab Complex Syst Optimiza Yulin 537000 Peoples R China Guangxi Univ Natl Coll Sci Nanning 530006 Peoples R China Guangxi Univ Coll Comp Elect & Informat Nanning 530004 Peoples R China

Dynamic economic dispatch with valve-point effects (DED-VPE) is a non-convex and non-differentiable optimization problem that is difficult to solve efficiently. In this paper, a hybrid approach combining mixed-integer linear programming (MILP) and the interior point method (IPM), abbreviated as MILP-IPM, is proposed to solve a DED-VPE problem in which complicated transmission loss is also included. Due to the non-differentiable nature of the DED-VPE problem, the classical derivative-based optimization methods can no longer be used. With the help of model reformulation, a differentiable non-linear programming (NLP) formulation that can be directly solved using the IPM is derived. However, if the DED-VPE problem is solved using the IPM in a single step, the optimization can easily become trapped in a poor local optimum due to its non-convex nature and multiple local minima. To obtain a better solution, an MILP method is required to solve the DED-VPE problem without transmission loss, yielding a good initial point for the IPM to improve the quality of the solution. Simulation results demonstrate the validity and effectiveness of the proposed MILP-IPM approach for solving the DED-VPE problem.

关键词： Dynamic economic dispatch Valve-point effects Non-linear programming Interior point method mixed-integer linear programming

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A MILP methodology to optimize sizing of PV - Wind renewable energy systems

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ENERGY 2018年第PartB期165卷 385-398页

作者： Lamedica, Regina Santini, Ezio Ruvio, Alessandro Palagi, Laura Rossetta, Irene SAPIENZA Univ Rome Dept Astronaut Elect & Energy Engn Rome Italy SAPIENZA Univ Rome Dept Comp Control & Management Engn Rome Italy Rete Ferroviaria Italiana SpA Rome Italy

This paper proposes a methodology that is based on mixed-integer linear programming (MILP) to calculate the optimal sizing of a hybrid wind-photovoltaic power plant in an industrial area. The proposed methodology considers the: i) load requirements;ii) physical and geometric constraints for the renewable plants installation;iii) operating and maintenance costs of both wind and PV power plants;and the iv) electric energy absorbed by the public network. The power demand variation associated with the production cycles is considered by using a stochastic simulation tool. To consider both the load and seasonality variability, and to adapt the methodology to the actual operational use of the power plant, the optimization is performed separately for each month of the year. Then, an integrated economic analysis is discussed. The methodology is adopted to analyze an industrial plant in the Rome area used as a train depot and for maintenance purposes. The results, which combine the needs of the plant activity with the availability of renewable energy, enabled the determination of optimal solutions and the relevant savings achievable. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Industrial power plant mixed-integer linear programming Optimization Renewable energy systems

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Scheduling pumpoff operations in onshore oilfields with electric-power constraints and variable cycle time

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COMPUTERS & OPERATIONS RESEARCH 2018年第Mar.期91卷 247-257页

作者： Camponogara, Eduardo Guardini, Luiz Alberto de Assis, Leonardo Salsano Univ Fed Santa Catarina Dept Automat & Syst Engn CxP 476 BR-88040900 Florianopolis SC Brazil

An oilfield is a complex enterprise that requires hefty capital investments and substantial energy resources for its operation. In mature onshore oilfields, sucker-rod pumps are deployed to enable oil production when the reservoir pressure is low. Albeit robust, such an artificial-lifting technique relies on electric-power supply to keep the rotary machines running. Managing a limited source of electric power while, at the same time, maximizing oil production and reducing equipment wear is of paramount importance, particularly so with today's low prices for the oil barrel. To this end, this paper proposes mixed-integer linear formulations for scheduling the operations of sucker-rod pumps, which work according to a control policy that alternates between on and off pumping periods, the so called pumpoff policy. Formulations for scheduling the initial operations and reconfiguring the control policies are developed, implemented, and tested with computational experiments. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Sucker-rod pumping Scheduling Electric-power resource Onshore oilfield mixed-integer linear programming

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Designing and solving a reverse logistics network for polyethylene terephthalate bottles

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JOURNAL OF CLEANER PRODUCTION 2018年 195卷 605-617页

作者： Paydar, Mohammad Mandi Olfati, Marjan Babol Noshirvani Univ Technol Dept Ind Engn Babol Sar Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

In recent years, factors such as lack of valuable resources, economic importance, environmental concerns and increased customers' awareness caused the researchers to consider the design of a reverse logistics network. In this study, the process of collecting and remanufacturing polyethylene terephthalate bottles was considered. A mixed-integer linear programming model for a reverse logistics network was designed. A real case study of polyethylene terephthalate bottles was implemented in one of the northern cities of Iran to show the applicability of the model. The objective function was to minimize the total costs. In the current network model, new collection centers and remanufacturing centers can be opened. Also, the optimal number and location of the facilities along with the flow between them were determined. The obtained results clearly demonstrated that the proposed model is efficient and applicable. Moreover, this paper provided effective and reliable managerial implication solutions for decision makers of polyethylene terephthalate bottle reverse logistics network. Two meta-heuristic algorithms, namely the genetic algorithm and imperialist competitive algorithm, were applied to solve large-scale problems. The efficiency of the two proposed algorithms and the optimum solution of the LINGO software were compared in terms of the CPU time and objective function value. To achieve reliable results from these algorithms, parameter setting was utilized by the Taguchi method. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Reverse logistics Genetic algorithms Imperialist competitive algorithm Polyethylene terephthalate bottle mixed-integer linear programming

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