Hybrid Time Formulation for Diesel Blending and Distribution Scheduling

Neiro, Sérgio Mauro da Silva; Murata, V. V.; Pinto, José M.

doi:10.1021/ie5009103

Cited by 14 publications

(13 citation statements)

References 21 publications

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“…Relvas et al (2013) have improved the model and make it easier to determine feasible time intervals or the number of pumping batches. Neiro et al (2014) focused on the scheduling of an in-line diesel blending and distribution subsystem of an oil refinery, considering crude oil unloading, mixing, and inventory control, production unit scheduling, and finished product blending and shipping. However, these models are not comprehensive enough.…”

Section: Related Workmentioning

confidence: 99%

An MILP approach for detailed scheduling of oil depots along a multi-product pipeline

et al. 2017

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Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets. The operating costs of oil depots account for a large proportion of the total system's operating costs. Meanwhile, oil depots and pipelines form an entire system, and each operation in a single oil depot may have influence on others. It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration. So far, studies simultaneously considering operating constraints and contaminated oil issues are rare. Aiming at making a scheduling plan with the lowest operating costs, the paper establishes a mixed-integer linear programming model, considering a sequence of operations, such as delivery, export, blending, fractionating and exchanging operations, and batch property differences of the same oil as well as influence of batch migration on contaminated volume. Moreover, the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction. Finally, the model is successfully applied to one of the product pipelines in China and proved to be practical.

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Section: Related Workmentioning

confidence: 99%

An MILP approach for detailed scheduling of oil depots along a multi-product pipeline

et al. 2017

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“…The hybrid time representations take advantage of the flexibility of the continuous time representation and the management of events that can take place in fixed points, although these formulations require more computational effort than the discrete time formulations. In this field, Neiro et al [11] proposed a hybrid time formulation to minimize the total cost for diesel and distribution blending and distribution scheduling. This formulation involves time slots of variable length, in which the number of events within a period of time (i.e., a day), must be prespecified, since the number of time slots must be established.…”

Section: State Of the Artmentioning

confidence: 99%

Improved time representation model for the simultaneous energy supply and demand management in microgrids

Silvente

Aguirre

Zamarripa

et al. 2015

Energy

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This paper analyses the operational decision making procedures required to address the simultaneous management of energy supplies and requests in a microgrid scenario, in order to best accommodate arbitrary energy availability profiles resulting from an intensive use of renewable energy sources, and to extensively exploit the eventual flexibility of the energy requirements to be fulfilled. The optimization of the resulting short term scheduling problem in deterministic scenarios is addressed through a Mixed-Integer Linear Programming (MILP) mathematical model, which includes a new hybrid time formulation developed to take profit of the advantages of the procedures based on discrete time representations, while maintaining the ability to identify solutions requiring a continuous time representation, which might be qualitatively different to the ones constrained to consider a fixed time grid for decision-making. The performance of this new time representation has been studied, taking into account the granularity of the model and analyzing the associated trade-offs in front of other alternatives. The promising results obtained with this new formulation encourage further research regarding the development of decision-making tools for the enhanced operation of microgrids. Storage energy cost [m.u./kWh] Span of the time interval [h], Duration of consumption [h], Minimum power supply of source at interval [kW], Maximum power supply of source at interval [kW], Energy price to be sold to power grid at interval [m.u./kWh] , Minimum electricity storage of system at interval [kWh] , Maximum electricity storage of system at interval [kWh] , Initial storage level of system at interval [kWh] , , Period of time in which consumption is active at interval [h], Maximum initial time of consumption [h], Target initial time of consumption [h]  Binary variable indicating if consumption is active at interval t

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“…The receipt and delivery of the tank farm in the refinery are similar to the loading and unloading operations of transfer hub with multiple farms, respectively. Some researchers 19 have explored the diesel blending and distribution scheduling problem. The time horizon is partitioned into periods of equal intervals, representing the days on which points demand may be incurred.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Only a few studies have been conducted − on the scheduling of the third subsystem shipping of refinery, which is similar to the considered problem addressed in this paper. The tank farm receives products from the blending units and delivers them to the local markets.…”

Section: Introductionmentioning

confidence: 99%

Operation Scheduling Optimization of a Transfer Hub with Multiple Tank Farms Based on a New Continuous Time Representation

Wang

Huang

et al. 2018

Ind. Eng. Chem. Res.

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This study addresses the operation-scheduling problem of a transfer hub with multiple tank farms (M-TH) connected to a multiproduct pipeline network. As part of the pipeline network, the THs serve as links that receive, store, and deliver oil products. Previous scheduling optimization works on pipeline networks with oil products largely focused on the batch plans of each pipeline, without considering the operation schedule of the THs. In this study, the main task is to optimize the loading and unloading scheduling operations of the tanks in the M-TH, which are subjected to given schedules of upstream/downstream pipelines. The schedules of pipelines that carry different types of products can be decomposed into several independent single product scenarios. A mixed-integer linear programming (MILP) formulation is presented. The proposed formulation takes into account the capacities of the tanks, operational rules of the tanks and tank farms, structural constraints, and settling time after the loading operation, while minimizing the switch operations between the tanks and switchovers between the tank farms. Moreover, the MILP formulation can be solved for one separate products at one time as there is no interference among the single-product scheduling problems within the transfer hub. The formulation is based on a new continuous time representation with static and dynamic time slots. The scheduling horizon is partitioned into several static time slots on the basis of the time points of batches arriving at and leaving from the M-TH or the flow rate changed. Each static time slot is divided into several dynamic time slots, whose duration and starting/ending points are determined by the optimization process. The proposed formulation is validated using the optimal results of a real-world case. A time horizon partitioning strategy is employed to deal with the long-term horizon scenario. The results help verify that we can substantially save computational time and obtain a satisfactory solution; however, the optimality is compromised.

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Hybrid Time Formulation for Diesel Blending and Distribution Scheduling

Cited by 14 publications

References 21 publications

An MILP approach for detailed scheduling of oil depots along a multi-product pipeline

An MILP approach for detailed scheduling of oil depots along a multi-product pipeline

Improved time representation model for the simultaneous energy supply and demand management in microgrids

Operation Scheduling Optimization of a Transfer Hub with Multiple Tank Farms Based on a New Continuous Time Representation

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