Electrical distribution systems (EDSs) should be prepared to cope with demand growth in order to provide a quality service. The future increase in electric vehicles (EVs) represents a challenge for the planning of the...
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Electrical distribution systems (EDSs) should be prepared to cope with demand growth in order to provide a quality service. The future increase in electric vehicles (EVs) represents a challenge for the planning of the EDS due to the corresponding increase in the load. Therefore, methods to support the planning of the EDS, considering the uncertainties of conventional loads and EV demand, should be developed. This paper proposes a mixed-integer linear programming (MILP) model to solve the robust multistage joint expansion planning of EDSs and the allocation of EV charging stations (EVCSs). Chance constraints are used in the proposed robust formulation to deal with load uncertainties, guaranteeing the fulfillment of the substation capacity within a specified confidence level. The expansion planning method considers the construction/reinforcement of substations, EVCSs, and circuits, as well as the allocation of distributed generation units and capacitor banks along the different stages in which the planning horizon is divided. The proposed MILP model guarantees optimality by applying classical optimization techniques. The effectiveness and robustness of the proposed method is verified via two distribution systems with 18 and 54 nodes. Additionally, Monte Carlo simulations are carried out, aiming to verify the compliance of the proposed chance constraint.
A new timetable must be calculated in real-time when train operations are perturbed. Although energy consumption is becoming a central issue both from the environmental and economic perspective, it is usually neglecte...
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A new timetable must be calculated in real-time when train operations are perturbed. Although energy consumption is becoming a central issue both from the environmental and economic perspective, it is usually neglected in the timetable recalculation. In this paper, we formalize the real-time Energy Consumption Minimization Problem (rtECMP). It finds in real-time the driving regime combination for each train that minimizes energy consumption, respecting given routing and precedences between trains. In the possible driving regime combinations, train routes are split in subsections for which one of the regimes resulting from the Pontryagin's Maximum Principle is to be chosen. We model the trade-off between minimizing energy consumption and total delay by considering as objective function their weighted sum. We propose an algorithm to solve the rtECMP, based on the solution of a mixed-integer linear programming model. We test this algorithm on the Pierrefitte-Gonesse control area, which is a critical area in France with dense mixed traffic. The results show that the problem is tractable and an optimal solution of the model tackled can often be found in real-time for most instances.
Models and optimisation approaches are developed for a flexible job shop scheduling problem with lot streaming and lot sizing of the variable sublots. A two-stage optimisation procedure is proposed. First, the makespa...
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Models and optimisation approaches are developed for a flexible job shop scheduling problem with lot streaming and lot sizing of the variable sublots. A two-stage optimisation procedure is proposed. First, the makespan value is minimised with the smallest sublots defined for the problem instance. This makes it possible to shorten the makespan significantly, because each sublot is transferred separately to the next operation of a job. In the second stage, the sizes of the sublots are maximised without increasing the obtained makespan value. In this way, the quantity of sublots and transport activities is limited together with the related manufacturing cost. Two objectives are defined for the second stage. The first one is the maximisation of the sum of the sublot sizes of all operations, the second one is the maximisation of the number of the operations which do not need to be split at all. mixed-integer linear programming, constraint programming and graph-based models are implemented for the problem. Two optimisation approaches are developed and compared in computational experiments for each stage and objective, one approach is based on a third-party solver, and the second one on an independent own implementation, namely a tabu search and a greedy constructive heuristic.
mixed-model assembly lines are product-oriented production layouts often employed for large scale manufacturing of similar products. The unpaced variant of these lines employs a conveyor to discretely move pieces betw...
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mixed-model assembly lines are product-oriented production layouts often employed for large scale manufacturing of similar products. The unpaced variant of these lines employs a conveyor to discretely move pieces between stations either synchronously or asynchronously. Workload balancing and product sequencing are common optimization problems associated with these lines. While many works detail balancing and sequencing separately, few explicitly combine these degrees of freedom. Furthermore, hybrid (i.e. partly synchronous and partly asynchronous) lines are not explicitly described by previous optimization models. This paper presents a mixed-integer linear programming model capable of representing such unpaced lines and explicitly combine balancing, sequencing and cyclical scheduling. The application of the proposed method to a new dataset demonstrates the advantages of simultaneously balancing and sequencing lines, generating more efficient solutions than previously described models for 238 out of 240 instances. These results implied, however, in greater computational costs required to combine the degrees of freedom. Furthermore, a direct performance comparison study between synchronous, asynchronous, and hybrid lines is conducted. This allows line designers and managers to explicitly evaluate economical trade-offs between these line types.
Pipeline networks in oil fields, including gathering pipeline networks (GPNs) and water injection pipeline networks (WIPNs), are characterized by varied and complex structures and large investments. Optimizing the des...
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Pipeline networks in oil fields, including gathering pipeline networks (GPNs) and water injection pipeline networks (WIPNs), are characterized by varied and complex structures and large investments. Optimizing the design of these networks is the key to reducing the development costs of oilfields. In the development method of cyclic water injection, some pipelines can be used for both production gathering and water injection;thus, GPN and WIPN can be designed simultaneously. Currently, separate designs do not form a unified scheme, and the cost is high. In view of these shortages, the integrated network should be considered. Based on mass and energy balance equations for networks, this paper proposes a mixedintegerlinearprogramming (MILP) model that takes the minimum construction investment as the objective function. The piecewise method is used to deal with the nonlinear terms in this model. Two common connection structures of pipeline networks, stellated pipeline networks (SPNs) and cascade dendritic pipeline networks (CDPNs) can be calculated by adjusting several constraints. Decision variables for the optimal locations of the central processing facility (CPF) and manifolds, detailed topological structure, diameter and route of each pipeline, pipeline flow and node pressure are obtained integrally by solving this model with the Gurobi solver. Two cases are studied to verify the effectiveness of the model. The results illustrate that the model can satisfy the needs of the designers in the actual design process, avoiding a qualitative or univariate decision in the comparison of different schemes. Comparing the results with those of the separated design scheme, the proposed model is proved to achieve lower investment costs. Therefore, the proposed model is feasible and practical.
This paper presents a new hybrid system to reduce wind curtailment and improve scheduling flexibility. This hybrid system includes a wind farm, a concentrated solar power plant with thermal energy storage, and an elec...
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This paper presents a new hybrid system to reduce wind curtailment and improve scheduling flexibility. This hybrid system includes a wind farm, a concentrated solar power plant with thermal energy storage, and an electric heater. The major role of the electric heater is to convert the redundant wind power into thermal energy, and the thermal energy is stored in the thermal energy storage of the concentrated solar power plant. The optimal scheduling of this hybrid system is formulated as a mixed-integer linear programming problem to maximize the profit subjected to technical constraints. The effects of the electric heater on the system are studied under different weather conditions. The test results show that the electric heater is helpful for reduction of the both deviation from generation plan and wind curtailment. The maximum relative deviation falls from 5.15% to 0% during the clear sky day, and 47.49% to 31.74% during the partial cloudy day. The wind curtailment rate decreases by 52.59% and 100% for clear and partial cloudy days, respectively. An annual simulation for the system shows that the overall daily cumulative deviations of the new system are significantly decreased, and the wind curtailment can be reduced by greater than 90% for 151 days, validating the effectiveness of the proposed system.
In sports tournaments, an occurrence of a difference in the rest periods of opponent teams in a game, which we refer to as a rest mismatch, will disadvantage the less rested team. Thus, it is only fair to expect oppos...
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In sports tournaments, an occurrence of a difference in the rest periods of opponent teams in a game, which we refer to as a rest mismatch, will disadvantage the less rested team. Thus, it is only fair to expect opposing teams to have rested equally before their game. In this work, we introduce and study the Rest Mismatch Problem where the goal is to minimize the number of rest mismatches in a round robin tournament. Two integerlinear formulations and a constraint programming formulation are provided, and their computational performances are compared for several problem instances. Moreover, a heuristic algorithm is developed which finds a single round robin schedule with zero mismatches when the number of teams in the tournament is a multiple of 8, and four mismatches when it is a multiple of 4 but not 8. (C) 2018 Elsevier Ltd. All rights reserved.
In this paper, we present an analysis of the strength of sparse cutting planes for mixedintegerlinear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems...
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In this paper, we present an analysis of the strength of sparse cutting planes for mixedintegerlinear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems, and more general MILPs with the only assumption that the objective function is nonnegative. Given an MILP instance of one of these three types, assume that we decide on the support of cutting planes to be used and the strongest inequalities on these supports are added to the linearprogramming relaxation. We present bounds on the ratio of optimal value of the LP relaxation after adding cuts and the optimal value of the MILP that depends only on the sparsity structure of the constraint matrix and the support of sparse cuts selected, that is, these bounds are completely data independent. These results also shed light on the strength of single-scenario cuts for two-stage stochastic MILPs.
This paper proposes a system-wide optimal coordinated energy dispatch method for a multi-energy microgrid in both the grid-connected and islanded modes. The studied microgrid consists of multiple energy carriers cover...
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This paper proposes a system-wide optimal coordinated energy dispatch method for a multi-energy microgrid in both the grid-connected and islanded modes. The studied microgrid consists of multiple energy carriers covering the controllable generation units (fuel cell, electric boiler, combined cooling, heat and power plant and electric chiller), uncontrollable generation units (wind turbine and photovoltaic cell) and energy storage devices (battery storage, heat storage tank and ice storage tank). The proposed energy dispatch method aims to minimize the microgrid net operating cost and enhance the dispatch flexibility in supplying power, heat and cooling in the day-ahead energy market. For both the grid-connected and islanded microgrid, their dispatch models are formulated as the mixed-integer linear programming problems, which can be efficiently solved by the commercial solvers. Comprehensive case studies are performed to evaluate the effectiveness of the proposed method and then compared with the traditional dispatch methods which supply power and heat/cooling energies separately. Simulation results demonstrate that the proposed method can achieve much higher operating efficiency.
Many EU countries aim at reducing fossil fuels in the near future, hence an efficient production of green energy is very important to reach this goal. In this article, we address the optimization of cable connections ...
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Many EU countries aim at reducing fossil fuels in the near future, hence an efficient production of green energy is very important to reach this goal. In this article, we address the optimization of cable connections between turbines in an offshore wind park. Different versions of the problem have been studied in the recent literature. As turbines are becoming still more customized, it is important to be able to evaluate the impact of new technologies with a flexible optimization tool for scenario evaluation. In a previous joint project with Vattenfall BA Wind (a global leader in energy production) we have studied and modeled the main constraints arising in practical cases. Building on that model, in the present article, we address new technological features that have been recently proposed by Vattenfall's experts. We show how some new features can be modeled and solved using a mixed-integer linear programming paradigm. We report and discuss computational results on the performance of our new models on a set of real-world instances provided by Vattenfall.
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