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This paper studies the optimal transmission switching (OTS) problem for power systems, where certain lines are fixed (uncontrollable) and the remaining ones are controllable via on/off switches. The goal is to identify a topology of the power grid that minimizes the cost of the system operation while satisfying the physical and operational constraints. Most of the existing methods for the problem are based on first converting the OTS into a mixed-integer linear program (MILP) or mixed-integer quadratic program (MIQP), and then iteratively solving a series of its convex relaxations. The performance of these methods depends heavily on the strength of the MILP or MIQP formulations. In this paper, it is shown that finding the strongest variable upper and lower bounds to be used in an MILP or MIQP formulation of the OTS based on the big- $M$ or McCormick inequalities is NP-hard. Furthermore, it is proven that unless $P=NP$ , there is no constant-factor approximation algorithm for constructing these variable bounds. Despite the inherent difficulty of obtaining the strongest bounds in general, a simple bound strengthening method is presented to strengthen the convex relaxation of the problem when there exists a connected spanning subnetwork of the system with fixed lines. With the proposed bound strengthening method, remarkable improvements in the runtime of the mixed-integer solvers and the optimality gaps of the solutions are achieved for medium- and large-scale real-world systems. [ABSTRACT FROM AUTHOR]

Independent system operators (ISOs) are responsible for the secure and economic operation of the power systems. Accordingly, ISOs should solve an optimal power flow to minimize the operating cost of a system while meeting the system's security constraints. However, transmission congestion could drastically limit more economical generating units from being dispatched in the power system operation. In this paper, a decentralized transmission switching is introduced in the operation of multi-area power systems to manage the congestion both on regional transmission lines and tie lines while considering credible contingencies. Our proposed methodology relies on a decentralized optimization methodology. Thus, regional control centers in areas would be able to locally manage the congestion within their regional networks as well as tie lines connecting them to their neighboring areas. Several testing systems are studied in this paper to test the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

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]

The European Union is targeting a 20% share of energy from renewable resources by 2020, and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators. In this paper, we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the European electricity network. To do this, we co-optimize unit commitment and transmission switching over 24 h, and we use a decomposition scheme to tackle the resulting large-scale problem. Our analysis is conducted on different scenarios of load and renewable power generation. We find that topology control results in significant cost savings within Europe which tend to be inversely related to net load. The robustness of our results is supported by an extensive sensitivity analysis. [ABSTRACT FROM AUTHOR]

Optimal transmission switching (OTS) optimizes simultaneously the generation dispatch and the topology of a power system. It has been shown that taking some transmission lines out of service can significantly reduce the operating cost of the system while respecting the traditional deterministic N-1 security criterion of operational reliability. However, topology modifications could adversely affect probabilistic security metrics. The operational reliability of a power system can be translated into a cost by multiplying the expected energy not served by the value of lost load. This paper therefore explores whether it is possible to maintain a positive economic balance with OTS when considering not only the cost of generation but also the expected socio-economic cost of disruptions in the supply. This is done in two steps: the computation of an N-1 secure OTS and then the calculation of a probabilistic estimate of the operational reliability of the OTS solution. Based on the results obtained with two test systems, it is shown that OTS tends to significantly degrade probabilistic measures of security. It is thus not obvious that OTS can lead to a positive economic balance, even when N-1 security is enforced. Consequently, a probabilistic security analysis should be performed before implementing an OTS solution. [ABSTRACT FROM AUTHOR]

This paper proposes a two-level voltage controller for large-scale power systems. The aim of the controller is to maintain a near-optimal voltage profile in the transmission network by coordinating discrete reactive power (var) control devices in the system. The controller is targeted for implementation in electric power transmission utility companies where most of the voltage controls are coordinated by switching of discrete var devices such as shunt capacitor and reactor banks and transformer banks load tap changers (LTCs). By effectively dividing the controller responsibilities between local substation controls and a central coordinator at control center level, the design is aimed at voltage control of large-scale power systems. At local level, the substation controllers maintain their respective substation bus voltages by local power-flow-like computations using mostly local PMU measurements. The central coordinator computes and provides the voltage set-points to the substation controllers and also coordinates by enabling or disabling the local controllers as needed. The controller is being designed towards prototype implementation in Southern California Edison (SCE), starting with local controllers at specific substations in the first stage. It is tested on real-time dynamic models and large-scale power-flow simulations of SCE transmission network. [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]

This paper proposes a new transmission-constrained unit commitment method that combines the cost-efficient but computationally demanding stochastic optimization and the expensive but tractable interval optimization techniques to manage uncertainty on the expected net load. The proposed hybrid unit commitment approach applies the stochastic formulation to the initial operating hours of the optimization horizon, during which the wind forecasts are more accurate, and then switches to the interval formulation for the remaining hours. The switching time is optimized to balance the cost of unhedged uncertainty from the stochastic unit commitment against the cost of the security premium of the interval unit commitment formulation. These hybrid, stochastic, and interval formulations are compared using Monte Carlo simulations on a modified 24-bus IEEE Reliability Test System. The results demonstrate that the proposed unit commitment formulation results in the least expensive day-ahead schedule among all formulations and can be solved in the same amount of time as a full stochastic unit commitment. However, if the range of the switching time is reduced, the hybrid formulation in the parallel computing implementation outperforms the stochastic formulation in terms of computing time. [ABSTRACT FROM PUBLISHER]