This paper proposes a controller placement model that takes into account the load-dependent sojourn time at each controller while considering controller failures in a software-defined network. The sojourn time is expr...
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This paper proposes a controller placement model that takes into account the load-dependent sojourn time at each controller while considering controller failures in a software-defined network. The sojourn time is expressed by the queuing theory. The sojourn time varies depending on the amount of load arriving at each controller in the proposed model. The proposed model is formulated as a mixedintegersecond-orderconeprogramming (MISOCP) problem. The controller placement problem studied in this paper is proven to be NP-hard. We develop a heuristic algorithm for the case where the solution to an optimization problem of the proposed model cannot be obtained in practical time. The proposed model is compared with two baseline models presented in the previous research. In the baseline models, the sojourn time does not depend on the amount of load arriving at each controller. Numerical results show that the number of placed controllers becomes smaller in the proposed model than in the baseline models. We also compare results obtained by solving the MISOCP problem to those of the heuristic algorithm. Numerical results show that the heuristic algorithm reduces the computation time required to determine the controller placement, whereas the difference between the number of controllers determined by the heuristic algorithm and the optimal value is at most 4.84%. The number of controllers placed by the heuristic algorithm tends to decrease by considering network centrality.
This paper proposes a controller placement model that takes into account the load-dependent sojourn time at each controller while considering controller failures. The sojourn time is expressed by the queuing theory. T...
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ISBN:
(纸本)9781665406949
This paper proposes a controller placement model that takes into account the load-dependent sojourn time at each controller while considering controller failures. The sojourn time is expressed by the queuing theory. The sojourn time varies depending on the amount of load arriving at each controller in the proposed model. The proposed model is formulated as a mixed integer second-order cone programming problem. The proposed model is compared with two baseline models presented in the previous research. In the baseline models, the sojourn time does not depend on the amount of load arriving at each controller. Numerical results show that the number of placed controllers becomes smaller in the proposed model than in the baseline models. This indicates that, since the sojourn time in the proposed model varies according to the amount of load at a controller, the effect of the load-dependent sojourn time at a controller tends not to become dominant over that of the propagation delay, which enables a switch to connect to more distant controller than that in the baseline models.
Resiliently designed and constructed integrated gas-electric distribution networks (GEDNs) against natural disasters are crucial to social welfare. In this study, a two-stage robust optimisation-based co-expansion pla...
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Resiliently designed and constructed integrated gas-electric distribution networks (GEDNs) against natural disasters are crucial to social welfare. In this study, a two-stage robust optimisation-based co-expansion planning model is proposed to attain an integrated GEDN with a given resilience level, by optimising the investment strategies of hardening and selective expansion of power distribution feeders and natural gas pipelines, as well as the location and capacity of natural-gas-fired distributed generation. In the first stage, the overall annual investment and operation cost is minimised under normal operation conditions while in the second stage, the feasibility of the investment decisions under the identified worst-case natural disaster scenario is checked with an adjustable load shedding cost criterion. The proposed model is formulated as a mixed integer second-order cone programming problem with the column and constraint generation algorithm employed to seek the optimal solution. Case studies on two integrated GEDNs demonstrate the performance of the proposed methodology.
Notable benefit can be brought by combined operation of coupled electricity-heat system (CEHS) and be enhanced by introducing independent thermal energy storage (ITES). With prevalent constant-flow variable temperatur...
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Notable benefit can be brought by combined operation of coupled electricity-heat system (CEHS) and be enhanced by introducing independent thermal energy storage (ITES). With prevalent constant-flow variable temperature (CF-VT) control strategy of heat network, explicitly formulating CEHS with ITES leads to mixed-integer non-convex programming. Although the problem can be reformulated as a mixedintegersecond-orderconeprogramming (MISOCP) problem and solved by commercial solvers, improving the computation efficiency still needs more effort. Here, several alternative solution techniques, based on either reformulation or approximation methods, are studied and compared with the original MISOCP formulation. The computation efficiencies as well as on the solution accuracies of various solution techniques or a combination of them are investigated and analysed based on two constructed systems. Simulation results reveal that appropriately selecting formulations of electric and heat networks can effectively improve the performance of solving the original problem.
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