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This paper develops an effective model for microgrid optimal scheduling with dynamic network reconfiguration. Network reconfiguration can effectively alter local power flow and thus provide an opportunity to reduce microgrid distribution network losses during grid-connected operation (supporting microgrid economic objectives) and to reduce potential load curtailments during the islanded operation (supporting microgrid reliability objectives). The proposed optimal scheduling model is decomposed into a grid-connected operation master problem and an islanded operation subproblem. A novel and highly accurate dynamic linear power flow model, with the ability of line switching, is developed and included in both problems. The optimal schedule determined in the master problem is assessed to meet the microgrid islanding feasibility in the subproblem. If infeasible, the decision variables are amended using the islanding cuts, which will accordingly revise the network reconfiguration, as well as the schedule of dispatchable units, energy storage, and adjustable loads. The simulation results on a test microgrid demonstrate the effectiveness and satisfying performance of the proposed model. [ABSTRACT FROM AUTHOR]

In power system operation, network topology optimization (NTO) based on bus-branch model and opening/closing transmission lines has been previously proposed and utilized as a congestion mitigating tool to reduce operation cost. The bus-branch model cannot provide a detailed picture of all substation switching actions (e.g., bus splitting) that are well known to operators. In this paper, an NTO model based on substation and node-breaker modeling is presented to relieve congestion and consequently reduce cost. The substation reconfiguration provides a practical and realistic picture of switching actions, while having a higher flexibility in switching actions. However, due to introducing more number of nodes and binary variables associated with breakers, solving an NTO model would be challenging. Therefore, some tightening bounds are presented to maintain the reliability and accelerate the computations. Furthermore, using sensitivity analysis of substations, a method to cluster the network to congestion zones is then employed to determine suitable candidate substations for reconfiguration, thus significantly reducing the number of binary variables associated with breaker switchings. The results of applying the NTO model to the IEEE 118-bus test system demonstrate the effectiveness of the proposed method to remove congestion, while utilizing less number of switching actions compared to bus-branch switching. [ABSTRACT FROM AUTHOR]

Economic transmission switching has been proposed as a new control paradigm to improve the economics of electric power systems. In practice, the transmission switching operation itself is a disruptive action to the system. Frequently switching lines into or out of service can create undesirable effects on the security and reliability of power systems and may require new investments in the automation and control systems. In this paper, we formulate an economic seasonal transmission switching model where transmission switching occurs once at the beginning of a time period (season) and then the transmission topology remains unchanged during that period. The proposed seasonal transmission switching model is a large-scale mixed integer programming problem. The objective of the optimization model is to minimize the total energy generation cost over the season subject to loads and N-1 reliability requirements. We develop a novel decomposition method that decomposes the seasonal problem into one-hour problems which are then solved efficiently. We demonstrate our model and the decomposition approach on the 14-bus, 39-bus, and 118-bus power systems and show potential cost savings in each case. [ABSTRACT FROM PUBLISHER]