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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]

System operators are required to serve the load in the most cost-effective way while maintaining the integrity of the system and heeding reliability requirements. In the day-ahead market, operators acquire reserves in an attempt to guarantee N-1 reliability; yet, reserve deliverability is not guaranteed. Prior research has shown that the use of transmission switching, or topology control, may help improve reserve deliverability. In this paper, transmission switching is used as a corrective mechanism to help the system achieve N-1-1 reliability, where not only has the system lost a single element, but also it experiences the loss of a second major element after an adjustment period. In an attempt to preserve N-1-1 reliability, for this paper, a day-ahead unit commitment model that acquires supplementary reserves is solved. The day-ahead market solution is then tested for N-1-1 reliability using contingency analysis models with and without transmission switching. The methodology can be employed at the day-ahead time stage to ensure the system has acquired sufficient supplemental reserves. The results demonstrate that not only can corrective transmission switching be beneficial post-contingency without inhibiting the ability to return to N-1 reliability, but it can also help obtain an N-1-1 reliable solution. [ABSTRACT FROM AUTHOR]

This paper formulates a block-layer method for the reliability assessment of distribution systems. The characteristics of the method include: 1) identifying the impact of distribution component reliability on the system and load points using a block-layer structured assessment; 2) incorporating time-dependent failure parameters; and 3) taking account of the topological, seasonal, and meteorological features of the distribution systems under analysis. The proposed method first identifies the three critical parts of the distribution system: main supply, feeder, and secondary substation. It can also include reserve connections and distributed generation. Second, the method frames these parts into the layered structure, each corresponding to the zone of total load curtailment. To verify this reliability technique, this paper simulates distribution feeders assembled in a number of topologies and compares them with the state sampling technique. Data provided by the local utility company are processed to model the equipment and load for the base year. The results show that the proposed method can provide a wide range of partial and system indices. These values assist in the identification of parts of the distribution system and scenarios with low reliability and to determine possible remedial actions. [ABSTRACT FROM AUTHOR]

There is currently a national push to create a smarter grid. Currently, the full control of transmission assets is not built in network optimization models. With more sophisticated modeling of transmission assets, it is possible to better utilize the current infrastructure to improve the social welfare. Co-optimizing the generation with the network topology has been shown to reduce the total dispatch cost. In this paper, we propose the concept of just-in-time transmission. This concept is predicated on the fact that transmission that is a detriment to network efficiency can be kept offline when not needed and, with the proper smart grid/advanced technology, can be switched back into service once there is a disturbance. We determine which lines to have offline based on the optimal transmission switching model previously proposed. A secondary topic of this paper focuses on flowgate bidding. Approved by the Federal Energy Regulatory Commission and implemented within the SPP and NYISO networks, flowgate bidding is defined as allowing a line's flow to exceed its rated capacity for a short period of time for a set penalty, i.e., price. We demonstrate the effectiveness of these models by testing them on large-scale ISO network models. [ABSTRACT FROM AUTHOR]

In this paper, a novel solution method is proposed for the optimal topology control problem in AC framework with N-1 reliability. The resultant new topology of the proposed method is guaranteed to yield a better objective function value than the global solution of the problem with the original topology. In order to prove our statement, semi-definite programming relaxation is formulated to find a lower bound to the objective function value of the problem. The proposed method is favorable for parallelization to increase the computational efficiency, and the parallel computing flowchart is presented. Computational time of the algorithm for IEEE test cases is reported. An in-house power market simulator is developed to simulate a market environment complete with optimal topology control mechanism. Simulations held by participating human subjects are analyzed under the subtitles of the total operating cost, real power losses, and locational marginal price (LMP) variance. A simple example is illustrated to show that the resultant network topology may increase the real power losses while still providing a lower operating system cost than that of the original topology. [ABSTRACT FROM PUBLISHER]