High intermittence of renewable energy resources(RESs)and restriction for greenhouse gas(GHG)emissions have significantly challenged the operations of traditional diesel generator(DG)based *** paper considers an emiss...
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High intermittence of renewable energy resources(RESs)and restriction for greenhouse gas(GHG)emissions have significantly challenged the operations of traditional diesel generator(DG)based *** paper considers an emission-free microgid with hybrid hydrogen-battery energy storage(HHBES)and proposes a coordinated operational strategy to minimize its daily operation *** addition to the electricity purchase costs in the day-ahead market and the operational costs of RESs,the total degradation cost of HHBES is also included in the cost *** proposed operational strategy consists of two coordinated *** the day-ahead stage,the schedule for the tie-line power is exchanged with the main grid,the output power of the fuel cell(FC)and the input power of the electrolysis device(ED)are optimized under the worst case of uncertain power output from RESs and power demand from electricity loads(ELs).At the intra-day stage,the battery power is determined according to the short-term prediction for the power of RESs and *** problem is formulated as a robust optimization model and solved by a two-level column-andconstraint-generation(C&CG)*** simulations using Australian energy market operator(AEMO)data are carried out to validate the effectiveness of the proposed strategy.
In this paper, we study a new approach to horizontal collaboration, the so-called coalition configuration among partnering companies through sharing distribution centers in a network design problem. Horizontal collabo...
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In this paper, we study a new approach to horizontal collaboration, the so-called coalition configuration among partnering companies through sharing distribution centers in a network design problem. Horizontal collaboration is established by making joint decisions and sharing resources among various parties at the same level of the supply chain which improves operational efficiency and competitiveness. In particular, the question we address is which coalition should be formed in each distribution center while the objective function seeks to minimize the total cost in the network. Beyond that, potential uncertainties, i.e., operational and disruption risks, are considered in the collaborative design phase. Thus, this paper studies a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions. A tailored column-and-constraintgenerationalgorithm is utilized to solve the proposed robust model. Extensive numerical experiments have been conducted to analyze solutions obtained by the model in various situations, e.g., when the grand coalition forms, for decisions ranging from fully centralized to fully decentralized settings, for collaborative approaches versus non-collaborative approaches, and under different amounts of uncertainty budgets. The results demonstrate that the coalition formation mechanism proposes some competitive solutions with savings of the grand coalition. We also find that not only does collaboration always increase the flexibility and resilience of the network but also in collaborative approaches, the average price of robustness is comparatively lower than that of non-collaborative approaches.
This paper examines a three-echelon logistics network in which all supply and transshipment nodes are subject to disruption. We use uncertainty sets to describe the possible scenarios without depending on probabilisti...
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This paper examines a three-echelon logistics network in which all supply and transshipment nodes are subject to disruption. We use uncertainty sets to describe the possible scenarios without depending on probabilistic information. We adopt a two-stage robust optimization approach where location decisions are made before and recourse decisions are made after the disruptions are known. We construct three two-stage robust models, which are solved exactly by a column-and-constraint-generation algorithm. Numerical tests demonstrate that the proposed algorithm outperforms the Benders decomposition method in both solution quality and computational time, and that the system's reliability can be improved with only a slight increase in the normal cost. (C) 2018 Elsevier Ltd. All rights reserved.
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