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Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm

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ENERGY 2021年 235卷 121171-121171页

作者： AkbaiZadeh, MohammadReza Niknam, Taher Kavousi-Fard, Abdollah Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

This paper describes the energy management of energy hubs connected to electricity, gas, and heating networks in which the hub is incorporated as a coordination framework between distributed generations and energy storage systems. The deterministic model of the proposed scheme minimizes the total operating cost of these energy networks in the presence of energy hubs constrained to the optimal power flow equations of different networks and the formulation of hubs with sources and storages. The problem is subject to uncertainties of load, energy prices, renewable sources, and consumption energy of mobile storages. Additionally, the scheme inherently is a non-convex mixed-integer nonlinear pro-gramming framework. Adaptive robust optimization is used to model these uncertainties, which is based on a hybrid metaheuristic algorithm due to the nonlinear and non-convex nature of the proposed problem. Hence, a combination of Ant-lion Optimizer and Krill herd Optimization algorithm has been employed, which provides a robust optimal solution with approximate unique response conditions in the worst-case scenario. Eventually, the numerical results obtained by implementing the proposed scheme on a sample test system confirm the capability of the mentioned scheme in improving the operation condition of different energy networks in the worst-case scenario. Consequently, the total energy loss in all mentioned networks and maximum voltage and temperature drop decrease by roughly 8%, 44%, and 74% with respect to power flow analysis in this scenario. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Adaptive robust optimization Energy management Energy networks Grid-connected energy hub Hybrid metaheuristic algorithm mixed integer non-linear programming

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Energy management considering simultaneous presence of demand responses and electric vehicles in smart industrial grids

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2021年 45卷 101127-101127页

作者： Azimi, Zahra Hooshmand, Rahmat-Allah Soleymani, Soodabeh Islamic Azad Univ Sci & Res Branch Dept Elect Engn Tehran Iran Univ Isfahan Dept Elect Engn POB 81746-73441 Esfahan Iran

Due to a growing trend in electricity consumption and limitations in expanding the capacity of power plants, the issue of privatizing and restructuring the electricity industry has come to the fore. In this regard, with the emergence of competitive markets, drawing upon responsive programs and electric vehicles in planning smart networks has become an intense topic of research. This paper presents a new method for programming industrial virtual power plants (IVPP) considering synchronous presence of demand response programs and electric vehicles. The proposed algorithm aims at maximizing the proceeds from industrial networks through demand response planning and managing the energy consumption of electrical vehicles. The algorithm is implemented in Zone 2 of the modified version of the IEEE Reliability Test System. The simulation results show that the presence of electric vehicles in the parked position will increase the storage capacity of the IVPPs, whereupon the consumption load on IVPPs is reduced. Using demand response programs in this regard and selecting the best program for each IVPP at different times of the day cuts back on both network operating costs and high consumption peaks, whereby an improvement in the efficiency of electric vehicles parking schemes is obtained.

关键词： Industrial virtual power plant Stochastic energy management Demand response programs Electric vehicles mixed integer non-linear programming

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Optimal Access Point Power Management for Green IEEE 802.11 Networks

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SENSORS 2021年第6期21卷 2076-2076页

作者： Garroppo, Rosario G. Nencioni, Gianfranco Tavanti, Luca Gendron, Bernard Scutella, Maria Grazia Univ Pisa Dept Ingn Informaz I-56122 Pisa Italy Univ Stavanger Dept Elect Engn & Comp Sci N-4021 Stavanger Norway CUBIT Consortium Ubiquitous Technol I-56021 Cascina Italy Univ Montreal CIRRELT Montreal PQ H3T 1N8 Canada Univ Montreal DIRO Montreal PQ H3T 1N8 Canada Univ Pisa Dept Informat I-56127 Pisa Italy

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise Wireless Local Area Networks (WLANs) during periods of low user activity. We act on two network management aspects: powering off some Access Points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieving this goal. The approach has been formulated as an integer programming problem with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN. This general problem formulation has two implications: the formulation is widely applicable, but the nonlinearity makes it NP-hard. To solve this problem to optimality, we devised an exact algorithm based on a customised version of Benders' decomposition method. The computational results proved the ability to obtain remarkable power savings. In addition, the good performance of our algorithm in terms of solving times paves the way for its future deployment in real WLANs.

关键词： wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking network management

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A swarm intelligence graph-based pathfinding algorithm (SIGPA) for multi-objective route planning

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COMPUTERS & OPERATIONS RESEARCH 2021年 133卷 105358-105358页

作者： Ntakolia, Charis Iakovidis, Dimitris K. Univ Thessaly Sch Sci Dept Comp Sci & Biomed Informat Volos Greece

Personalized tourist route planning (TRP) and navigation are online or real-time applications whose mathematical modeling leads to complex optimization problems. These problems are usually formulated with mathematical programming and can be described as NP hard problems. Moreover, the state-of-the-art (SOA) path search algorithms do not perform efficiently in solving multi-objective optimization (MO) problems making them inappropriate for real-time processing. To address the above limitations and the need for online processing, a swarm intelligence graph-based pathfinding algorithm (SIGPA) for MO route planning was developed. SIGPA generates a population whose individuals move in a greedy approach based on A* algorithm to search the solution space from different directions. It can be used to find an optimal path for every graph-based problem under various objectives. To test SIGPA, a generic MOTRP formulation is proposed. A generic TRP formulation remains a challenge since it has not been studied thoroughly in the literature. To this end, a novel mixed binary quadratic programming model is proposed for generating personalized TRP based on multi-objective criteria and user preferences, supporting, also, electric vehicles or sensitive social groups in outdoor cultural environments. The model targets to optimize the route under various factors that the user can choose, such as travelled distance, smoothness of route without multiple deviations, safety and cultural interest. The proposed model was compared to five SOA models for addressing TRP problems in 120 various scenarios solved with CPLEX solver and SIGPA. SIGPA was also tested in real scenarios with A* algorithm. The results proved the effectiveness of our model in terms of optimality but also the efficiency of SIGPA in terms of computing time. The convergence and the fitness landscape analysis showed that SIGPA achieved quality solutions with stable convergence.

关键词： mixed integer non-linear programming Swarm intelligence algorithm Path search algorithm Convergence analysis Tourist route planning

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Energy-efficient resource allocation in wireless LANs under non-linear capacity constraints 25

Energy-efficient resource allocation in wireless LANs under ...

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25th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD)

作者： Garroppo, Rosario G. Nencioni, Gianfranco Tavanti, Luca Gendron, Bernard Scutella, Maria Grazia Univ Pisa Dept Ingn Informaz Pisa Italy Univ Stavanger Dept Elect Engn & Comp Sci Stavanger Norway Consortium Ubiquitous Technol CUBIT Cascina PI Italy Univ Montreal CIRRELT Montreal PQ Canada Univ Montreal DIRO Montreal PQ Canada Univ Pisa Dept Informat Pisa Italy

ISBN: (数字)9781728163390

ISBN: (纸本)9781728163390

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise wireless LANs during periods of low user activity. We act on two network management aspects: powering off some access points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieve this goal. The approach has been shaped as an integer programming model with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN system. To solve this model to optimality we present an algorithm named Benders' Decomposition-based Algorithm (BDA). The computational results in realistic scenarios proved the possibility to obtain remarkable power savings.

关键词： Wireless LAN energy efficiency resource allocation optimisation mixed integer non-linear programming green networking network management

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Robust Coordinated Operational Planning of Power Distribution Systems Considering Electric Vehicle Aggregators 6

Robust Coordinated Operational Planning of Power Distributio...

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6th IEEE International Energy Conference (IEEE ENERGYCON) - Energy Transition for Developing Smart Sustainable Cities

作者： Fotopoulou, Maria C. Evangelopoulos, Vasileios A. Georgilakis, Paylos S. Natl Tech Univ Athens NTUA Sch Elect & Comp Engn Athens Greece

ISBN: (纸本)9781728129563

This paper proposes a robust model that optimizes the joint cooperation between the distribution system operator (DSO) and the electric vehicle aggregators (EVAs) considering the forecasting uncertainties. The developed cooperation model considers electric vehicles (EVs) in a vehicle-to-grid operation, fuel-based distributed generators, and wind generators. The purpose of the proposed model is to optimize the operational planning that simultaneously minimizes the DSO's energy cost and maximizes the revenue of each EVA. The proposed model is applied to a 14-bus distribution system to verify its effectiveness and robustness.

关键词： distribution systems electric vehicles electric vehicle aggregators mixed integer non-linear programming robust optimization

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An Adapted Derivative-Free Optimization Method for an Optimal Design Application with mixed Binary and Continuous Variables 6th

An Adapted Derivative-Free Optimization Method for an Optima...

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6th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Tran, Thi-Thoi Sinoquet, Delphine Da Veiga, Sebastien Mongeau, Marcel IFP Energies Nouvelles Rueil Malmaison France Safran Magny Les Hameaux France Univ Toulouse III ENAC Toulouse France

ISBN: (纸本)9783030383640;9783030383633

Numerous optimal design applications are black-box mixed integer nonlinear optimization problems: with objective function and constraints that are outputs of a black-box simulator involving mixed continuous and integer (discrete) variables. In this paper, we address an optimal design application for bladed disks of turbo-machines in aircraft. We discuss the formulation of an appropriate distance with respect to discrete variables which can deal with the cyclic symmetry property of the system under study. The necklace concept is introduced to characterize similar blade configurations and an adapted distance is proposed for discrete space exploration of a derivative-free optimization method. The results obtained with this method on a simplified industrial application are compared with results of state-of-the-art black-box optimization methods.

关键词： mixed integer non-linear programming Black-box simulation Derivative free trust region method Necklace distance

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mixed integer quadratically-constrained programming model to solve the irregular strip packing problem with continuous rotations

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第1期72卷 89-107页

作者： Cherri, Luiz H. Cherri, Adriana C. Soler, Edilaine M. Univ Sao Paulo Av Trabalhador Sao Carlense 400 BR-13566590 Sao Carlos SP Brazil Univ Estadual Paulista Av Eng Luiz Edmundo Carrijo Coube 14-01 BR-17033360 Bauru SP Brazil ODM Rua Alfredo Lopes 1717Sala E10 BR-13560460 Sao Carlos SP Brazil

The irregular strip packing problem consists of cutting a set of convex and non-convex two-dimensional polygonal pieces from a board with a fixed height and infinite length. Owing to the importance of this problem, a large number of mathematical models and solution methods have been proposed. However, only few papers consider that the pieces can be rotated at any angle in order to reduce the board length used. Furthermore, the solution methods proposed in the literature are mostly heuristic. This paper proposes a novel mixed integer quadratically-constrained programming model for the irregular strip packing problem considering continuous rotations for the pieces. In the model, the pieces are allocated on the board using a reference point and its allocation is given by the translation and rotation of the pieces. To reduce the number of symmetric solutions for the model, sets of symmetry-breaking constraints are proposed. Computational experiments were performed on the model with and without symmetry-breaking constraints, showing that symmetry elimination improves the quality of solutions found by the solution methods. Tests were performed with instances from the literature. For two instances, it was possible to compare the solutions with a previous model from the literature and show that the proposed model is able to obtain numerically accurate solutions in competitive computational times.

关键词： mixed integer non-linear programming Nesting problems Irregular pieces Continuous rotations

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Capacitated facility location-allocation problem for wastewater treatment in an industrial cluster

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COMPUTERS & OPERATIONS RESEARCH 2021年 132卷 105338-105338页

作者： Chandra, Saurabh Sarkhel, Manish Vatsa, Amit Kumar Indian Inst Management Operat Management & Quantitat Tech Indore 453556 Madhya Pradesh India TA Pai Management Inst Operat & Decis Sci Manipal 576104 Karnataka India

We present a location-allocation problem for wastewater treatment in a cluster of processing units. The problem involves installing wastewater treatment plants of appropriate capacities at suitable locations and allocating processing units to these plants. The operational cost of treatment plants is a nonconvex function of wastewater volume and pollutant concentration. This problem is formulated as a non-convex mixed integer nonlinear programming (MINLP) problem. For the general class of this problem, solution strategies based on adapted McCormick envelopes and also piece-wise linear approximation are presented. For a special case of this problem, an exact convexification strategy is proposed and an outer approximation based branch-and-cut approach is presented as an exact solution method. For solving larger instances, we present a matheuristic solution method based on multi-start neighborhood search incorporated into a MINLP solution approach. A real-world case study is presented to illustrate the results of the model along with a multi-objective analysis.

关键词： Shared wastewater management Facility location mixed integer non-linear programming Outer approximation Multi-start neighborhood search McCormick envelopes

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An integration of algal biofuel production planning, scheduling, and order-based inventory distribution control systems

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BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR 2019年第4期13卷 920-935页

作者： Nugroho, Yohanes K. Zhu, Liandong Wuhan Univ Sch Resource & Environm Sci 129 Luoyu Rd Wuhan 430079 Hubei Peoples R China Wuhan Univ Hubei Biomass Resource Chem & Environm Biotechnol 129 Luoyu Rd Wuhan 430079 Hubei Peoples R China

This paper studies an integration model of production planning, scheduling, and order- based inventory distribution control systems. It models supply-chain and production dynamics and employs process control to supply-chain operations and the production process and scheduling. It embeds generalized disjunctive programming (GDP) and branch-and-reduce algorithms to obtain an optimal solution. Generalized disjunctive programming reformulates the original mixed integer nonlinear programming (MINLP) model and solves the new model with a lower number of integer variables. Afterwards, the branch and reduce algorithm, which is strengthened with outer approximation (OA) cutting planes, is able to find optimal solutions with permissible optimality gaps. The results show that supply network size does not affect forecast accuracy;there is a forecast error rate of 12.9%. Similar figures are also shown for the inventory level, which is expected to be 32% of demand level, production changeover time at 0.58 days, inventory ramp-up period to meet the expected raw materials and final products inventory at 0.02 and 0.04 days respectively, and extra delivery time to meet a certain level of demand change at 1.1 days. The results show that the model is capable of controlling demand forecast, inventory level, and delivery quantity, so that the supply chain can avoid stock out at a minimal level of inventory, regardless of the size of supply-chain networks. (c) 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

关键词： production planning scheduling process control branch and reduce generalized disjunctive programming mixed integer non-linear programming

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