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A Novel Load Scheduling Mechanism Using Artificial Neural Network Based Customer Profiles in Smart Grid

ENERGIES 2020年第5期13卷

作者： Khalid, Zubair Abbas, Ghulam Awais, Muhammad Alquthami, Thamer Rasheed, Muhammad Babar Univ Lahore Dept Technol Lahore 54000 Pakistan Univ Lahore Dept Elect Engn Lahore 54000 Pakistan King Abdulaziz Univ Elect & Comp Engn Dept Jeddah 21589 Saudi Arabia Univ Lahore Dept Elect & Elect Syst Lahore 54000 Pakistan

In most demand response (DR) based residential load management systems, shifting a considerable amount of load in low price intervals reduces end user cost, however, it may create rebound peaks and user dissatisfaction. To overcome these problems, this work presents a novel approach to optimizing load demand and storage management in response to dynamic pricing using machine learning and optimization algorithms. Unlike traditional load scheduling mechanisms, the proposed algorithm is based on finding suggested low tariff area using artificial neural network (ANN). Where the historical load demand individualized power consumption profiles of all users and real time pricing (RTP) signal are used as input parameters for a forecasting module for training and validating the network. In a response, the ANN module provides a suggested low tariff area to all users such that the electricity tariff below the low tariff area is market based. While the users are charged high prices on the basis of a proposed load based pricing policy (LBPP) if they violate low tariff area, which is based on RTP and inclining block rate (IBR). However, we first developed the mathematical models of load, pricing and energy storage systems (ESS), which are an integral part of the optimization problem. Then, based on suggested low tariff area, the problem is formulated as a linear programming (LP) optimization problem and is solved by using both deterministic and heuristic algorithms. The proposed mechanism is validated via extensive simulations and results show the effectiveness in terms of minimizing the electricity bill as well as intercepting the creation of minimal-price peaks. Therefore, the proposed energy management scheme is beneficial to both end user and utility company.

关键词： demand side management mixed integer linear programming artificial neural network Inclining block rate rebound peaks

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An iterative graph expansion approach for the scheduling and routing of airplanes

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COMPUTERS & OPERATIONS RESEARCH 2020年 114卷

作者： Gnegel, Fabian Fuegenschuh, Armin Brandenburg Univ Technol Cottbus Senftenberg Pl Deutsch Einheit 1 D-03046 Cottbus Germany

A tourism company that offers fly-in safaris is faced with the challenge to route and schedule its fleet of airplanes in an optimal way. Over the course of a given time horizon several groups of tourists have to be picked up at airports and flown to their destinations within a certain time-window. Furthermore, the number of available seats, the consumption of fuel, the maximal takeoff weight, and restrictions on the detour of the individual groups have to be taken into account. The task of optimally scheduling the airplanes and tour groups belongs to the class of vehicle routing problems with pickup and delivery and time-windows. A flow-over-flow formulation on the time expanded graph of the airports was used in the literature in order to model this problem as a mixed integer linear program. Most of the benchmark problems, however, could not be solved within a time limit of three hours, which was overcome by what they call the time-free approach (TFA). In the TFA they formulate the problem for a simplified (time-free) graph and use an incumbent callback to check for feasibility in the original graph. While this approach led to very good results for instances, where few time-free solutions were infeasible for the original problem, some instances remained unsolved. In order to overcome this problem, we derive two new exact formulations that include time as variables. Although these formulations by themselves are not always better than the approach from the literature, they allow for an effective construction of graphs which can be interpreted as intermediate graphs between the graph of airports and the expanded graph with vertices for each visit. Using similar relaxation techniques to the TFA and constructing these graphs based on solutions of the relaxations guarantees that only critical airports are expanded. A computational study was performed in order to compare the new formulations to the methods from the literature. Within a time limit of 3 hours, the new approa

关键词： mixed integer linear programming Vehicle routing problem Time-Dependent airplane routing Dynamic graph expansion

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Evaluating and Optimizing Opportunity Fast-Charging Schedules in Transit Battery Electric Bus Networks

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TRANSPORTATION SCIENCE 2020年第6期54卷 1601-1615页

作者： Abdelwahed, Ayman van den Berg, Pieter L. Brandt, Tobias Collins, John Ketter, Wolfgang Erasmus Univ Rotterdam Sch Management NL-3062 PA Rotterdam Netherlands Univ Minnesota Coll Sci & Engn Minneapolis MN 55455 USA Univ Cologne Fac Management Econ & Social Sci Cologne Inst Informat Syst D-50969 Cologne Germany Univ Cologne Inst Energy Econ D-50969 Cologne Germany

Public transport operators (PTOs) increasingly face a challenging problem in switching from conventional diesel to more sustainable battery electric buses (BEBs). In this study, we optimize the opportunity fast-charging schedule of transit BEB networks in order to minimize the charging costs and the impact on the grid. Two mixed-integer linear programming (MILP) formulations that use different discretization approaches are developed and compared. Discrete-Time Optimization (DTO) resembles a time-expanded network that discretizes the time and decisions to equal discrete slots. Discrete-Event Optimization (DEO) discretizes the time and decisions into nonuniform slots based on arrival and departure events in the network. In addition to the DEO's higher practicability, the comparative computational study carried out on the transit-bus network in the city of Rotterdam, Netherlands, shows that the DEO is superior to the DTO in terms of computational performance. To show the potential benefits of the optimal schedule, it is compared with two reference common-sense greedy strategies: First-in-First-Served and Lowest-Charge-Highest-Priority.

关键词： transit electric bus networks charging schedule mixed integer linear programming

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Planning the decarbonisation of energy systems: The importance of applying time series clustering to long-term models

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ENERGY CONVERSION AND MANAGEMENT-X 2022年 15卷

作者： Novo, Riccardo Marocco, Paolo Giorgi, Giuseppe Lanzini, Andrea Santarelli, Massimo Mattiazzo, Giuliana Politecn Torino Dipartimento Ingn Meccan & Aerosp I-10129 Turin Italy Politecn Torino Dipartimento Energia Galileo Ferraris I-10129 Turin Italy Politecn Torino MOREnergy Lab I-10129 Turin Italy Politecn Torino Energy Ctr Lab I-10129 Turin Italy

The study of future energy scenarios with high shares of variable renewable energy sources (VRES) requires an accurate representation of VRES variability and storage capacity. However, long-term optimal expansion models, which are typically used to prescribe the evolution of energy systems, make use of coarse time series to limit computational effort. This weakness can entail an incorrect sizing of VRES plants and storage facilities. In this work, a novel method is proposed to mitigate the current limitations and enable accurate long-term planning of high-VRES decarbonisation pathways. Clustering methods are applied to time series, preserving the possibility of having inter-day and intra-day energy storage. To this end, the temporal framework of an open-source energy system model, OSeMOSYS, is modified to allow the implementation of interconnected, clustered representative days. Traditional and novel approaches are compared and benchmarked for a reference case study, i.e., a remote island. The results show that time series clustering can significantly improve the evaluation of the overall system cost, leading to a relative error of-5% (novel approach) instead of-35% (traditional approach) when 24 representative days are considered. Similarly, the new approach improves the sizing of VRES and storage fa-cilities. The new technique is found to require three orders of magnitude less computation time than the traditional technique to achieve a comparable level of accuracy.

关键词： Energy systems Renewable energy mixed integer linear programming Energy modelling Time series clustering

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Distribution network model using big data in an international environment

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SCIENCE OF THE TOTAL ENVIRONMENT 2020年 707卷 135549页

作者： Mishra, Shraddha Singh, Surya Prakash Indian Inst Technol Delhi Dept Management Studies Delhi India

This paper proposes dynamic mixed integer facility location model to design an international manufacturing network (IMN). The proposed model considers a broad facility network linking production and distribution facilities located internationally. The proposed model discussed in the paper assumes significance over the traditional manufacturing model as it provides a country specific analysis making it more convenient for the decision maker to devise country specific strategies within an international ecosystem. Therefore, the model considers import export cost, loan subsidies along with depreciation expense and other operating costs applicable to specific country. The objective of the model is to identify optimal facility locations and the production distribution in the entire network to meet the demand of global markets. The proposed model is illustrated and computationally tested using two cases. Model parameters are mapped using 3Vs of Big Data viz. Volume, Velocity and Variety. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Distribution network Facility location Big data Import export cost mixed integer linear programming

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Optimization of Electricity Distribution in Latin America by Using Embedded Systems

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IEEE LATIN AMERICA TRANSACTIONS 2020年第2期18卷 351-359页

作者： Alvarez, G. Sarli, J. INGAR CONICET UTN Inst Desarrollo & Diseno Avellaneda 3657 Santa Fe Argentina

The processes regarding the generation, transmission and distribution of electricity are gaining interest at global level, due to the constant trend in increasing consumption. Because of this, significant sums are allocated for investments to improve the efficiency of these processes. However, there are a significant number of companies which, by virtue of their small scale and the problems inherent in Latin American economies, have serious difficulties in obtaining several types of equipment, necessary to improve their efficiency. In this context, this paper presents a methodology to operate optimally a small-scale electricity grid. To achieve this goal, two stages are organized;each has its own characteristics and hardware. The first is the resolution of a Master Problem, which solves the problem of committing generators and pre-dispatching loads through a PC. The second stage is the resolution of a Slave Problem, which is responsible for determining the most convenient form of transmission, advocating the maintenance of the system. In this stage the command and operation of the system are also organized;as a consequence, an Embedded System is used that allows the coordination of system actuators. In order to test the method, a system composed of 6 buses and 8 lines is resolved. The results indicate that this proposal operates in efficient times;this allows reducing investment costs due the implemented technology. The application of this methodology in small and medium networks will continue to increase, as new sources of generation increase their participation in these electrical systems.

关键词： Transmission Constraints mixed integer linear programming Power System Scheduling Embedded Systems Interoperability Software Engineering

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Multi-objective optimal sizing of grid connected photovoltaic batteryless system minimizing the total life cycle cost and the grid energy

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RENEWABLE ENERGY 2020年 148卷 1256-1265页

作者： Ndwali, Kasereka Njiri, Jackson G. Wanjiru, Evan M. Jomo Kenyatta Univ Agr & Technol Dept Mechatron Engn Juja Kenya

The increasing demand of electricity has led to drastic use of renewable energy resources because of the scarcity and environmental effects of fossil fuel. Photovoltaic energy is one of renewable energy sources that emerges exponentially due to its environmentally friendly, operating and maintenance free, among other benefits. However, the main drawback of photovoltaic energy is its unreliability due to unpredictable nature of solar. Thus, this paper tackles a novel optimization technique based on multi-objective sizing of grid connected photovoltaic without energy storage systems. The objective aims at minimizing the total life cycle cost (TLCC) and energy purchased from utility grid while maximizing the reliability. In this study, the microgrid system reliability is expressed by the loss of power supply probability (LPSP). mixed integer linear programming has been used to determine the decision variables which are the optimal number of photovoltaic panels and the hourly powers from utility grid. A case study has been done based on daily power demand of Engineering workshops at Jomo Kenyatta University of Agriculture and Technology (JKUAT). From the results obtained, the optimal number is 354 photovoltaic arrays, 0.6022 kWh is purchased from the grid from 7:00 h to 18:00 h, and the total life cycle cost of the project is found to be 191630$. The daily potential energy saving is up to 64.16%. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Islanding mode Levelized cost of energy Loss of power supply probability mixed integer linear programming Stand-alone

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Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization

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IEEE TRANSACTIONS ON SMART GRID 2020年第1期11卷 644-654页

作者： Khatami, Roohallah Parvania, Masood Narayan, Akil Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA Univ Utah Dept Math Salt Lake City UT 84112 USA

This paper defines flexibility reserve trajectory as a single reserve product that not only supplies the energy imbalance in real-time operation but also the resulting ramping requirements by embedding the flexible ramping trajectories as time derivative of the reserve trajectories. Further, a stochastic optimization model is proposed for multi-fidelity co-optimization of energy and flexibility reserve in day-ahead power systems operation. The proposed model integrates operation decisions with different levels of modeling fidelity in a single stochastic optimization problem. More specifically, day-ahead energy trajectories, day-ahead flexibility reserve capacity trajectories, and real-time flexibility reserve deployment trajectories are modeled by Bernstein polynomials with different degrees as required to match the load and renewable generation with different levels of variability in day-ahead and real-time operations. The proposed model is implemented on the IEEE reliability test system using load and solar generation data of California ISO, where the numerical results demonstrate that the proposed model schedules a reserve capacity that more accurately matches the real-time energy imbalance and ramping requirements of net-load, while reducing the total operation cost of the system.

关键词： NOMA Unmanned aerial vehicles Resource management Wireless networks Optimization Quality of service Continuous-time unit commitment stochastic optimization flexibility reserve uncertainty characterization mixed integer linear programming

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On Track Procession Assignment Problem at the Railway Network Sections

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AUTOMATION AND REMOTE CONTROL 2020年第6期81卷 967-977页

作者： Gainanov, D. N. Ignatov, A. N. Naumov, A. V. Rasskazova, V. A. Moscow Inst Aviat Technol Moscow Russia

We consider the problem of assigning a "track procession," i.e., the time for railway network maintenance, when train movements are forbidden. The railway network is presented in the form of an undirected multigraph. Movements along this multigraph are carried out with a set of conflict-free subslots, where each "subslot" is a five-tuple of the arrival and departure vertices, number of the edge used for movement, and arrival and departure times. In this work, we construct a mathematical model for carrying out transportations plan with accounting for constraints on time when trains are for departure as well as constraints on arrival time. An optimization problem on time selection for track processions assignment and trains schedule corresponds to a mixed integer linear programming problem with a criteria of the minimization of total time spend by trains in run. An applied implementation of the proposed approach was performed using ILOG CPLEX software. We present the results of a numerical experiment.

关键词： "track procession" railway network multigraph subslot mixed integer linear programming

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Optimal Switch Placement in Distribution Systems: A High-Accuracy MILP Formulation

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IEEE TRANSACTIONS ON SMART GRID 2020年第6期11卷 5009-5018页

作者： Shahbazian, Abbas Fereidunian, Alireza Manshadi, Saeed D. KN Toosi Univ Technol Fac Elect Engn Tehran 163171419 Iran San Diego State Univ Dept Elect & Comp Engn San Diego CA 92182 USA

A new solution method is introduced to the problem of optimally deploying manual and automatic switches in distribution systems, where the product of two continuous variables and the inverse of a continuous variable are reformulated as a linear relation. This leads to a (mixed integer linear problem) MILP power flow formulation too. The objective function includes cost and reliability. The cost term itself includes capital investment, installation, and maintenance costs (MC) as well as customer interruption cost (CIC);while the reliability term is represented by system average interruption duration index (SAIDI). The problem is formulated as a MILP, which guarantees a global optimal solution. The effectiveness of the proposed method is validated through various case studies and sensitivity analyses on the RBTS4, followed by a comprehensive discussion and analysis of results. The proposed MILP formulation prescribes fewer switches while achieving lower SAIDI, compared to that of a previous MINLP formulation.

关键词： Switches Reliability Circuit faults Manuals Load flow Indexes linear programming Distribution automation system reliability evaluations switch placement linear Power flow product of two continuous variable mixed integer linear programming

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