The constant mass flow assumption has dominated distributed dispatch of integrated electricity-heat systems (IEHSs), which ensures the simplicity of decomposition while incurring opportunity costs. In contrast, a heat...
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The constant mass flow assumption has dominated distributed dispatch of integrated electricity-heat systems (IEHSs), which ensures the simplicity of decomposition while incurring opportunity costs. In contrast, a heat operation strategy with variable flow and variable temperature (VF-VT) enhances flexibility and optimality. However, VF-VT renders the IEHS dispatch problem into a mixed-integer nonlinear bi-level nested program, which leaves a critical yet unresolved challenge for distributed autonomous dispatch. Therefore, this paper proposes a two-stage alternating procedure embedded with sequential equivalent techniques. A feasible initial point is obtained in the first stage, and the total costs are minimized thereafter. In each iteration, the heat sector optimizes both hydraulic and thermal states based on a surrogate model, and submits the heat equivalent to the electricity sector;the electricity sector solves the reduced IEHS dispatch problem and then updates the boundary. The feasibility is proved theoretically, while numerical tests validate the effectiveness.
This study proposes a mixed-integer nonconvex programming (MINP) model for the winner determination problem (WDP) considering two discount functions in a combinatorial auction to save shipper's transportation cost...
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This study proposes a mixed-integer nonconvex programming (MINP) model for the winner determination problem (WDP) considering two discount functions in a combinatorial auction to save shipper's transportation cost. For the WDP, the shipper allows carriers to submit bids for a bundle of lanes. Then the winning carries are selected by solving the WDP. Specifically, this study considers the shipment distance-based and volume-based discounts for transportation cost, simultaneously. The state-of-the-art linearization technique is available to convert the MINP model into a mixed-integer linear program (MILP) to obtain a global optimum, but the solution time becomes inefficient when the problem size becomes large. To find efficient and effective linearization techniques for large-scale WDP, this study (1) proposes a novel WDP model with discount policies, (2) utilizes superior encoding formulation to avoid the unbalanced branch-and-bound trees in solving MILP, and (3) reduces big-M constraints to speed up the solving time. The proposed method leads to significant savings in computational efforts. Numerical experiments with real-world-sized truckload service procurement problems are solved by the proposed method and further confirmed the drastic reduction in computational time for solving the large-size WDP.
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 mixedinteger second-order cone programming (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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