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The co-optimization of security-constrained unit commitment and dispatchable transmission network is a large-scale and computationally complex optimization problem that brings big challenges for the traditional centralized and/or master–slave based decomposition approaches. This paper proposes a fully parallel approach to achieve an efficient and fast solution while considering post-contingency corrective actions. In this paper, the original co-optimization problem is decomposed into six major solution modules for unit commitment, optimal power flow, and transmission switching in base case and contingencies, respectively. Moreover, each major solution module is further decomposed by unit, period, dispatchable line, and/or contingency to make the proposed approach favorable in a fully parallel computing environment. The effectiveness and efficiency of the proposed fully parallel approach are justified using numerical cases on a high-performance computing (HPC) platform. [ABSTRACT FROM AUTHOR]

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]

Event-triggered control (ETC) is becoming increasingly popular in load frequency control (LFC) operation in power systems. So far, the existing literature has primarily focused on load disturbance rejection in face of communication delay without considering much on networked-induced measurement disturbances and messages sent. In this paper, we study the LFC operation as a problem of networked control system and propose, for the first time, an ETC based switching approach for frequency regulation. We derive delay-dependent conditions to obtain the lower bound on inter-event time during event-trigger mechanism which assures the robust stability under networked induced time-varying delays and measurement disturbance and reduction in the amount of sent measurements. The effectiveness of the proposed approach is verified via numerical examples based on single-, two-area power systems and single-area with electric vehicle (EV) participation. [ABSTRACT FROM AUTHOR]

Optimal power management of shipboard power system for failure mode (OPMSF) is a significant and challenging problem considering the safety of system and person. Many existing works focused on the transient-time recovery without consideration of the operating cost and the voyage plan. In this paper, the OPMSF problem is formulated considering the mid-time scheduling and the faults at bus and generator. Two-side adjustment methods including the load shedding and the reconfiguration are coordinated for reducing the fault effects. To address the formulated non-convex problem, the travel equality constraint and fractional energy efficiency operation indicator limitation are transformed into the convex forms. Then, considering the infeasibility scenario affected by faults, a further relaxation is adopted to formulate a new problem with feasibility guaranteed. Furthermore, a sufficient condition is derived to ensure that the new problem has the same optimal solution as the original one. Because of the mixed-integer nonlinear feature, an optimal management algorithm based on Benders decomposition (BD) is developed to solve the new one. Due to the slow convergence caused by the time-coupled constraints, a low-complexity near-optimal algorithm based on BD is proposed. The results verify the effectivity of the proposed methods and algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we model topology control through transmission switching as a recourse action in the day-ahead operation of power systems with large-scale renewable generation resources. We prove that transmission switching could only reduce the linear objective value of direct current optimal power flow when congestion exists. However, we also show, through a simple example, that unit commitment cost could be reduced by transmission switching even in the absence of congestion. To solve the stochastic unit commitment with topology control within reasonable computational time, we proposed a heuristic that first decomposes a practical system into zones and then solves the problem for each zone in parallel. The benefit of topology control recourse is demonstrated on a network representing the Central European System. We compare the costs of the network with different loading and renewable generation conditions. The cost reduction of the test system can reach 3.34% with heavy load and large-scale renewable generation while in a single zone the cost reduction can be above 7%. [ABSTRACT FROM PUBLISHER]

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly. [ABSTRACT FROM PUBLISHER]

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]

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]

The subsynchronous resonance (SSR) problem may become more serious with the continuous evolvement of a series-compensated power system. Consequently, the existing SSR mitigation scheme might no longer keep the system stable. This issue has been encountered by Shangdu Power Plant, where the deployed supplementary excitation damping controllers (SEDCs) that well stabilized the system before cannot maintain torsional stability after the recent change occurred in the power system. Therefore, a combined mitigation scheme of SEDC and generator terminal subsynchronous damping controller (GTSDC) is proposed in this paper to regain system stability. SEDC provides electrical damping by modulating the excitation voltage at the rotor side. Meanwhile, GTSDC can damp SSR via injecting super-synchronous and subsynchronous currents into the generator stator. Field tests have proven the effectiveness of this combined scheme in addressing the deteriorated SSR issue. Eigenvalue analysis indicates that the combined scheme can provide enough positive damping for the system under any operating condition. Thanks to the low investment of SEDC and the flexibility of GTSDC, this combined scheme provides an economical and scalable solution for SSR mitigation, especially when the target system changes constantly. [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]

This paper considers optimal transmission switching (OTS) to reduce generation cost by removing lines from service. A mixed integer program (MIP) has been proposed to solve the OTS problem, based on the linear direct current optimal power flow (DCOPF) model. Because of excessive computation times for large, real systems, the MIP model has been followed by some heuristics, also based on the DCOPF, to obtain near-optimal solutions quickly. However, the approximations in the DCOPF model may lead to poor choices of lines to remove from service. We assess the quality of line removal recommendations that rely on a previously published, DCOPF-based heuristic, by estimating actual cost reduction with the exact ACOPF model, using the IEEE 118-bus and 300-bus test systems with several demand levels. We also extend this heuristic to be based on the ACOPF and compare the quality of its recommendations to those of the DCOPF-based heuristic. The DCOPF-based heuristic performs very poorly in several cases, even leading to cost increases sometimes. There is a need for approximations to the ACOPF which are accurate enough to produce reliably good results for OTS heuristics, but fast enough for practical use. [ABSTRACT FROM AUTHOR]

This paper introduces load shed recovery actions for transmission networks by presenting the dc optimal load shed recovery with transmission switching model (DCOLSR-TS). The model seeks to reduce the amount of load shed, which may result due to transmission line and/or generator contingencies, by modifying the bulk power system topology. Since solving DCOLSR-TS is computationally difficult, the current work also develops a heuristic (MIP-H), which improves the system topology while specifying the required sequence of switching operations. Experimental results on a list of N-1 and N-2 critical contingencies of the IEEE 118-bus test case demonstrate the advantages of utilizing MIP-H for both online load shed recovery and recurring contingency-response analysis. This is reinforced by the introduction of a parallelized version of the heuristic (Par-MIP-H), which solves the list of critical contingencies close to 5x faster than MIP-H with 8 cores and up to 14x faster with increased computational resources. The current work also tests MIP-H on a real-life, large-scale network in order to measure the computational performance of this tool on a real-world implementation. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage robust optimization approach to solve the N-k contingency-constrained unit commitment (CCUC) problem. In our approach, both generator and transmission line contingencies are considered. Compared to the traditional approach using a given set of components as candidates for possible failures, our approach considers all possible component failure scenarios. We consider the objectives of minimizing the total generation cost under the worst-case contingency scenario and/or the total pre-contingency cost. We formulate CCUC as a two-stage robust optimization problem and develop a decomposition framework to enable tractable computation. In our framework, the master problem makes unit commitment decisions and the subproblem discovers the worst-case contingency scenarios. By using linearization techniques and duality theory, we transform the subproblem into a mixed-integer linear program (MILP). The most violated inequalities generated from the subproblem are fed back into the master problem during each iteration. Our approach guarantees a globally optimal solution in a finite number of iterations. In reported computational experiments, we test both primal and dual decomposition approaches. Our computational results verify the effectiveness of our proposed approach. [ABSTRACT FROM PUBLISHER]

In power system operation, transmission congestion can drastically limit more economical generation units from being dispatched. In this paper, optimal transmission switching as a congestion management tool is utilized to change network topology which, in turn, would lead to higher electricity market efficiency. Transmission switching (TS) is formulated as an optimization problem to determine the most influential lines as candidates for disconnection. In order to relieve congestion without violating voltage security, TS is embedded in an optimal power flow (OPF) problem with AC constraints and binary variables, i.e., a mixed-integer nonlinear programming (MINLP) problem, solved using Benders decomposition. Also, a methodology is presented which provides a guideline to the system operator showing the order of switching manoeuvres that have to be followed in order to relieve congestion. It is also shown that TS based on DC optimal power flow (DCOPF) formulation as used in the literature may jeopardize system security and in some cases result in voltage collapse due to the shortcomings in its simplified models. In order to evaluate the applicability and effectiveness of the proposed method, the IEEE 57-bus and IEEE 300-bus test systems are used. [ABSTRACT FROM PUBLISHER]

In power system reconfiguration, the status (ON/OFF) of switches are optimized such that maximum power is delivered to loads after the occurrence of a fault. The optimized reconfiguration is achieved by prioritizing power delivered to vital loads over semi-vital and nonvital loads. The formulation presented in this paper considers a new balanced hybrid (AC and DC) shipboard power system (SPS). Analysis of the nonconvex reconfiguration formulation is done by an appropriate nonconvex solver and by convex approximation. Unlike the nonconvex solution that is based on branch-and-bound methods, convex approximation significantly reduces complexity. It is shown that for the hybrid SPS reconfiguration problem, low complexity convex approximations are effective in finding optimal solutions. Cumulative distribution function (CDF) of the power delivered to loads is presented to showcase the system robustness against random fault scenarios. A combined objective of maximizing power delivery and minimizing the number of switching actions is included in the analysis. Tradeoff between power delivered and number of switching operations after reconfiguration has been discussed at steady state. A separate analysis is also included to observe the intermediate dynamic switch states while the reconfiguration is in progress to capture the trade-off more prominently. [ABSTRACT FROM PUBLISHER]

Power system voltage security assessment is generally applied by considering the power system loadability surface. For a large power system, the loadability surface is a complicated hyper-surface in parameter space, and local approximations are a necessity for any analysis. Unfortunately, inequality constraints due to for example generator overexitation limiters and higher codimension bifurcations makes the loadability surface nonsmooth. This makes the use of local approximations limited and calls for a method for estimating the distance to a nonsmooth part of the surface. This paper suggests a method for calculating the distance from a point on the loadability surface to the closest point of nonsmoothness of the loadability surface. [ABSTRACT FROM PUBLISHER]

The Shangdu power plant has four 600-MW turbine-generators connected to the North-China Grid through two 500-kV transmissions, which are compensated with 45% fixed series capacitors. Extensive studies conducted on the system model indicate that the system suffers from multimodal subsynchronous resonance (SSR). To solve the problem, a countermeasure is developed by combining the supplementary excitation damping control (SEDC) and the torsional stress relay (TSR). In this paper, the characteristics of the SSR problem are investigated. Then the developed SEDC is presented. To validate the effectiveness of the proposed SEDC as well as the results of model studies, field tests were conducted under various operating conditions. The tests fully exposed the realistic threat of SSR in the system. Meanwhile, it is demonstrated that the developed SEDC can improve torsional damping significantly, and thus solve the multimodal SSR problem effectively. This is the first time in China that practical SEDCs have been developed and their ability to mitigate multimodal SSR has been verified in a real series-compensated system. [ABSTRACT FROM AUTHOR]

The authors discuss an article by M. Lavorato and colleagues on imposing radiality constraints in power distribution system optimization problems. They claim that the paper lacks any reference where an alternative mathematical formulation is proposed to deal with transfer nodes or zero-injection nodes. In their opinion, the possibility for transfer nodes is not realistic, being in opposition to the usual operation of the medium voltage (MV) systems where all the transfer nodes are connected to.