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This paper focuses on the issue of network connectedness (NC) in security-constrained optimal transmission switching problems, which is complicated by branch contingencies and corrective line switching. Two criteria are firstly proposed with the principle of preserving NC as much as possible within reasonable limits. By extending the electrical flow based NC constraints, a proposition is derived to associate different cases of NC with the optimum of a linear program, yielding the mathematical formulation of the NC criteria. By Karush-Kuhn-Tucker conditions, this formulation is further transformed into a tractable version which can be incorporated with existing SCOTS models without affecting the applicability of original solution approaches. Finally, case studies on various networks and SCOTS models demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Boosting the resilience of power systems is one of the core requirements of smart grid. In this paper, an integrated resilience response framework is proposed, which not only links the situational awareness with resilience enhancement, but also provides effective and efficient responses in both preventive and emergency states. The core of the proposed framework is a two-stage robust mixed-integer optimization model, whose mathematical formulation is presented in this paper as well. To solve the above model, an algorithm based on the nested column-and-constraint generation decomposition is provided, and computational efficiency improvement techniques are proposed. Preventive response in this paper considers generator re-dispatch and topology switching, while emergency response includes generator re-dispatch, topology switching and load shedding. Several numerical simulations validate the effectiveness of the proposed framework and the efficiency of the solution methodology. Key findings include the following: 1) in terms of enhancing power grid resilience, the integrated resilience response is preferable to both independent preventive response and independent emergency response; 2) the power grid resilience could be further enhanced by utilizing topology switching in the integrated resilience response. [ABSTRACT FROM PUBLISHER]

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 addresses the incorporation of transmission switching in the contingency-constrained unit commitment problem within the context of co-optimized electricity markets for energy and reserves. The proposed generation scheduling model differs from existing formulations due to the joint consideration of four major complicating factors. First, transmission switching actions are considered both in the pre- and post-contingency states, thereby requiring binary post-contingency variables. Secondly, generation scheduling and transmission switching actions are co-optimized. In addition, the time-coupled operation of generating units is precisely characterized. Finally, practical features of modern power systems, such as uncertain nodal net injections and the operation of energy storage, are also considered. The proposed model is cast as a challenging mixed-integer program for which the off-the-shelf software customarily used for simpler models may lead to intractability even for moderately-sized instances. In order to circumvent this computational issue, this paper presents an enhanced and novel application of an exact nested column-and-constraint generation algorithm featuring the inclusion of valid constraints to improve the overall computational performance. Numerical simulations based on the IEEE 118- and 300-bus systems demonstrate the effective performance of the proposed approach as well as its economic and operational advantages over existing models disregarding post-contingency transmission switching. [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]

This paper presents a methodology for generating restoration sequences in distribution systems and microgrids with emphasis on deriving optimal switching times for remote control switches. Microgrid architecture considered are assumed to be operating in islanded single master mode. Control methods for handling the unbalance inherent in distribution systems using single-phase controlled PQ inverters were developed and incorporated in the proposed method. The problem of considering simultaneously both energy optimization and dynamic stability of the system, which is lacking in existing methods, was addressed by studying the transient behavior of microgrids based on extended electromagnetic transients program (EMTP) simulations and then approximate and incorporate these behaviors into the optimization formulation for restoration. The approach is based on multi-objective optimization of final restored load and total restoration time. The methodology was studied on a modified IEEE 123 node test feeder. An EMTP simulation in PSCAD of the formed microgrids was used to validate the accuracy of the dynamic and steady-state characteristics of the resulting systems. By considering the transient behavior of distributed generators (DGs) during restoration, a better restoration sequence that does not trigger protection relays could be realized. [ABSTRACT FROM AUTHOR]

Intentional controlled islanding (ICI) and black start allocation (BSA) are two examples of problems in the power systems literature that have been formulated as mixed integer programs (MIPs) and allow reconfiguration of the power system topology. A key consideration in both of these problems is that each island that appears after a reconfiguration must have at least one energized generator. In this paper, we examine three alternative MIP formulations for this restriction, show their equivalence, and prove that two of them are stronger in terms of their linear programming relaxation than the formulation most commonly used in the power systems literature. Since the time to solve MIPs can vary significantly between equivalent formulations, we also present computational experiments on the IEEE test systems for the ICI and BSA problems. We observe that a polynomially separable, exponential in size, strong formulation yields the best performance for the BSA problem and exhibits a comparable performance to a linear in size, weak formulation for the ICI problem. [ABSTRACT FROM AUTHOR]

Inadequate frequency response can arise due to a high penetration of wind turbine generators (WTGs) and requires a frequency support function to be integrated in the WTG. The appropriate design for these controllers to ensure adequate response has not been investigated thoroughly. In this paper, a safety supervisory control (SSC) is proposed to synthesize the supportive modes in WTGs to guarantee performance. The concept, region of safety (ROS), is stated for safe switching synthesis. An optimization formula is proposed to calculate the largest ROS. By assuming a polynomial structure, the problem can be solved by a sum of squares program. A feasible result will generate a polynomial, the zero sublevel set of which represents the ROS and is employed as the safety supervisor. A decentralized communication architecture is proposed for small-scale systems. Moreover, a scheduling loop is suggested so that the supervisor updates its boundary with respect to the renewable penetration level to be robust with respect to variations in system inertia. The proposed controller is first verified on a single-machine three-phase nonlinear microgrid, and then implemented on the IEEE 39-bus system. Both results indicate that the proposed framework and control configuration can guarantee adequate response without excessive conservativeness. [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]

In the face of increasing natural disasters and an aging grid, utilities need to optimally choose investments to the existing infrastructure to promote resiliency. This paper presents a new investment decision optimization model to minimize unserved load over the recovery time and improve grid resilience to extreme weather event scenarios. Our optimization model includes a network power flow model which decides generator status and generator dispatch, optimal transmission switching (OTS) during the multi-time period recovery process, and an investment decision model subject to a given budget. Investment decisions include the hardening of transmission lines, generators, and substations. Our model uses a second order cone programming (SOCP) relaxation of the AC power flow model and is compared to the classic DC power flow approximation. A case study is provided on the 73-bus RTS-GMLC test system for various investment budgets and multiple hurricane scenarios to highlight the difference in optimal investment decisions between the SOCP model and the DC model, and demonstrate the advantages of OTS in resiliency settings. Results indicate that the network models yield different optimal investments, unit commitment, and OTS decisions, and an AC feasibility study indicates our SOCP resiliency model is more accurate than the DC model. [ABSTRACT FROM AUTHOR]

This paper proposes a multifunctional control strategy and associated control algorithms for distributed wind-turbine (WT) based nano-grids connected to a distorted utility-grid. The contribution is on a new strategy with innovative control algorithms to coordinate multiple converters for a multitasking operation of the nano-grids. The novelty is on a unique control design with feasibilities: maximizing the generated power from WT, maintaining power quality in both ac- and dc-sides under critical conditions of the power grid, and improving power quality against distortion from local nonlinear loads under a reduced switching frequency. A robust fast-dynamic predictive control method is developed for current controllers to fulfil the multifunction. Unconstrained deadbeat control inputs are derived in twofold targets: ensuring fast dynamic response and significantly reducing both the computation and switching frequency for finite predictive control. The control system is applied on a permanent-magnet synchronous generator (PMSG) WT-based nano-grid connected to a distorted utility-grid. An OPAL-RT-based real-time platform is used for comparative studies among the proportional integration (PI) control, finite predictive control (FS-MPC), and proposed control method. The performance verification exhibits the power quality improvement in both the nano- and utility-grids under critical conditions via high-performed regulation of currents, voltages, reactive power, and rotor-speed of the PMSG-WT. [ABSTRACT FROM AUTHOR]

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]

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible ac transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee optimality, more than 98% of the presented empirical results, based on the IEEE 118-bus and Polish systems, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced. [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]

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]

Due to the significant variability and uncertainty of wind power over short time scales, high penetration of wind power can be problematic in an electric grid. One of the critical issues is how to keep increasing wind penetration without jeopardizing grid security and reliability. This paper explores the possibility of changing transmission network topology, by transmission switching, to accommodate higher utilization of wind power and reduce the generation costs of thermal units. Considering the uncertainty in wind power output, we use chance constraints to ensure that the wind energy utilized exceeds a minimal usage level at a certain probability. We develop a deterministic approximation approach using sample average approximation and provide a strong extended formulation. Numerical results show the potential benefit the proposed model can achieve. [ABSTRACT FROM PUBLISHER]

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]

High congestion costs and new congestion patterns, formed by intermittent renewable generation, demand for more efficient utilization of the transmission system. Transmission switching (TS) and variable-impedance series FACTS devices are two technologies that provide such efficiency gains through controlling the power flows. As the system operators begin to utilize these tools, it is essential to understand the interdependence between them at various stages, such as planning and operation. This paper develops an optimal power flow framework that incorporates both FACTS and TS to study the link between the two power flow control technologies. The simulation results on an RTS 96-bus system suggest that: 1) substantial economic savings can be achieved through utilization of both TS and FACTS, beyond the independent capabilities of each technology; 2) performing TS actions affect the optimal location and set point of FACTS devices; and 3) operation of FACTS devices affect the location and frequency of TS actions. It is, thus, essential to acknowledge the interdependence between the two technologies both at the planning and operation stage. Failure to do so will lead to economic inefficiencies that can be avoided through co-optimization of generation dispatch, TS, and FACTS. [ABSTRACT FROM PUBLISHER]

This paper tackles key industry needs in the scope of the AC Security-Constrained Optimal Power Flow (SCOPF) framework, specifically two major challenging requirements regarding generators’ post-contingency behavior: the (droop-based) frequency response and the voltage control mechanism (including PV/PQ switching). To this end, and to obtain a sufficiently accurate solution with a reasonable computational burden, we propose an approximation approach to SCOPF which extends significantly an existing algorithm with novel modelling elements: a continuous formulation to model generators’ post-contingency responses based on successive approximations, a technique to evaluate the viability of contingencies with respect to the base case set-points, and the complexity reduction of all post-contingency states through network compression and power flow piecewise linearization. All new features are validated both separately and in unison, to monitor the improvement of the solution time and the potential degradation of the solution's quality. The proposed approach is successfully applied to three power system network models, the largest of which consists of 2,000 buses and more than 3,000 contingencies. Finally, the trade-off between the limitations in terms of solution quality and the benefits in terms of computational effort are assessed for all proposed approximations. [ABSTRACT FROM AUTHOR]

In this paper, a flexible optimization-based framework for intentional islanding is presented. The decision is made of which transmission lines to switch in order to split the network while minimizing disruption, the amount of load shed, or grouping coherent generators. The approach uses a piecewise linear model of AC power flow, which allows the voltage and reactive power to be considered directly when designing the islands. Demonstrations on standard test networks show that solution of the problem provides islands that are balanced in real and reactive power, satisfy AC power flow laws, and have a healthy voltage profile. [ABSTRACT FROM PUBLISHER]

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 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]

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]

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]

This paper introduces a new method of removing thermal overloads and voltage limits in an electric power system by means of the Evolution of Corrective and Preventive control Actions (ECPA). The goal is to find the minimum number of control actions that solve the identified limit violations at minimum cost. A recombination operator based on form theory allows the codification of control actions in a natural and simple way. ECPA has been tested on the IEEE 30-bus and the IEEE 118-bus systems. The limit violations are solved at minimum cost and with fewer control actions on average than alternative methods. [ABSTRACT FROM AUTHOR]

In this paper, an efficient methodology is proposed to deal with segmented-time reconfiguration problem of distribution networks coupled with segmented-time reactive power control of distributed generators. The target is to find the optimal dispatching schedule of all controllable switches and distributed generators' reactive powers in order to minimize comprehensive cost. Corresponding constraints, including voltage profile, maximum allowable daily switching operation numbers (MADSON), reactive power limits, and so on, are considered. The strategy of grouping branches is used to simplify the formulated mathematical problem and a hybrid particle swarm optimization (HPSO) method is presented to search the optimal solution. Fuzzy adaptive inference is integrated into basic HPSO method in order to avoid being trapped in local optima. The proposed fuzzy adaptive inference-based hybrid PSO algorithm (FAHPSO) is implemented in VC++ 6.0 program language. A modified version of the typical 70-node distribution network and several real distribution networks are used to test the performance of the proposed method. Numerical results show that the proposed methodology is an efficient method for comprehensive cost minimization in distribution systems with distributed generators. [ABSTRACT FROM PUBLISHER]

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]

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]

This paper presents a hierarchical decentralized agent-based network reconfiguration methodology to minimize power losses for smart distribution systems. A novel formulation of the network reconfiguration problem is given in which the switch states are the decision variables, and a single-loop branch-exchange heuristic algorithm is used to solve the optimization problem. The entire distribution system is decomposed into subsystems based on the connectivity of areas, and an individual agent is assigned to each decomposed subsystem. A two-stage method is defined for coordinating the reconfigurations of decomposed subsystems. The optimal configuration of the entire system results from collaborations of individual agents, and the decentralized approach significantly reduces the computation time. A 118-bus distribution system is used as the example to illustrate the implementation of the method. The development of a demonstration system and more detailed simulation studies are given in Part II to further illustrate the application of the proposed decentralized approach. [ABSTRACT FROM PUBLISHER]

Transmission grid topology control makes power systems more flexible and efficient. However, a line switching action itself may cause transient instability since a large flow disturbance may be involved. In this paper, a critical switching flow (CSF) concept is developed and an associated preventive stabilizing redispatch scheme is proposed to provide control guidelines for line switching actions to prevent instability and enhance transient stability for the system. The CSF is calculated in the day-ahead stage using a two-stage Monte Carlo algorithm, in which the uncertainties of generations and loads are considered and the worst case in the system is identified statistically. The obtained information is then used in the proposed scheme in the operation stage. Selected generators are dispatched before a switching action to ensure system stability. The IEEE reliability test system, the modified IEEE-118 bus system, and the Texas 2000 system are used to demonstrate the effectiveness and scalability of the proposed algorithm and scheme. [ABSTRACT FROM PUBLISHER]

Microgrid formation is a potential solution in postdisaster electric grid recovery efforts. Recent works propose a distribution level microgrid formation model that applies to radial distribution systems characterized by directed power flows. However, with high renewable penetration levels in future power systems, the flows are expected to be undirected even in distribution grids. In this paper, we develop a model to deal with the restoration process of future power systems, embedding some of the characteristics these systems are likely to have. More specifically, our formulation can deal with radial and meshed topologies, and it requires little preprocessing of the input data. Additionally, we extend the model to allow for possible mobile and fixed distributed generation technologies and distributed energy resources, and explicitly include demand responsive loads with a minimum satisfiability constraint. Thus, this extended formulation can be used as an operation and a short term planning tool for the DG scenario-based location problem. We compare our extended formulation results to those obtained for the radial cases found in the literature. Also, we apply the proposed approach to other instances of the problem based on the IEEE 37-bus, 30-bus, and 118-bus systems. [ABSTRACT FROM PUBLISHER]

As the modern transmission control and relay technologies evolve, transmission line switching has become an important option in power system operators’ toolkits to reduce operational cost and improve system reliability. Most recent research has relied on the DC approximation of the power flow model in the optimal transmission switching problem. However, it is known that DC approximation may lead to inaccurate flow solutions and also overlook stability issues. In this paper, we focus on the optimal transmission switching problem with the full AC power flow model, abbreviated as AC optimal transmission switching (AC OTS). We propose a new exact formulation for AC OTS and its mixed-integer second-order cone programming relaxation. We improve this relaxation via several types of strong valid inequalities inspired by the recent development for the closely related AC optimal power flow problem [Kocuk et al., “Strong SOCP relaxations for the optimal power flow problem,” Oper. Res., vol. 64, no. 6, pp. 1177–1196, 2016]. We also propose a practical algorithm to obtain high-quality feasible solutions for the AC OTS problem. Extensive computational experiments show that the proposed formulation and algorithms efficiently solve IEEE standard and congested instances and lead to significant cost benefits with provably tight bounds. [ABSTRACT FROM PUBLISHER]

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 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]

A Rectangular Interval Power Flow (RIPF) method is proposed to improve solutions for intervals of power flow problems due to nondeterministic characteristics of demand loads and output of generators. It is based on affine arithmetic which is a self-validated numerical analysis and serves to improve the interval results through optimization method. Since no approximation is presumed, the RIPF method acquires narrower intervals of voltage phase and active power of branches than Polar Interval Power Flow (PIPF), it is an excellent method raised before. However, as RIPF is no better than that of PIPF for estimating intervals of voltage magnitude, because it relaxes restriction of the voltage equations. Therefore, a Mixed Interval Power Flow (MIPF) method is envisaged and developed in the paper to incorporate merits of RIPF for computing the intervals of voltage phase and active power of branches but not giving the advantage of PIPF for evaluating intervals of voltage magnitude. As a validation of our suggested approach, two case studies are carried out, and results conclude that the MIPF method acquires more accurate power flow intervals than the conventional method. [ABSTRACT FROM AUTHOR]

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]

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]

Following a line outage, the fast corrective operations of transmission line switching might be used to regain N-1 security of the system without generation re-dispatch or load shedding. The problem to find feasible switching operations can be formulated as a constraint satisfaction problem (CSP). Feasibility checking, however, is difficult since changes in load flows caused by line switching operations are discontinuous, and many contingency cases need to be examined. In this paper, DC flow is considered for simplicity, and variables include binary line statuses and continuous phase angles. Security constraints for the base case, N-1, and selected N-2 cases are formulated in a unified way by using a separate set of phase angles for each case. The problem is solved by using constraint programming (CP), and a tree search procedure is developed. Since it is time consuming to handle continuous variables in the tree search, only binary variables are branched on. Once reaching a leaf node where the topology is fixed, the constraints become linear DC flow feasibility conditions and are examined by solving a linear programming problem. Effectiveness of the method is demonstrated on IEEE 30-bus and 118-bus systems. [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.

This letter formulates network connectivity as Miller–Tucker–Zemlin (MTZ) constraints and incorporates them into the mixed-integer linear programming (MILP) model for the optimal transmission switching (OTS) problem. The connectivity constraints are linear and for a power network with $n$ buses, $m$ branches, and $d$ loads in pre-contingency or each post-contingency state there are approximately $\mathcal {O}(n+5m+d)$ constraints, and $\mathcal {O}(n)$ continuous and $\mathcal {O}(\text{2 m})$ binary variables, which is much smaller than those in the existing formulations. The MILP OTS model with the proposed connectivity constraints can be readily solved by well-developed MILP solvers. Case studies on the PJM 5-bus system, IEEE 300-bus system, and French 1888-bus system validate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This research analyses the non-linear and complex effects of drivers of system imbalance prices in the GB electricity market. Unlike day-ahead prices, the balancing settlement prices are comparatively under-researched, yet their importance is growing with greater market risks. The fundamental drivers of these prices are analysed over 2016-2019. The result of a non-linear modelling approach reveals that system imbalance price exhibits a regime-switching behaviour, driven by weather and demand forecast errors, as well as other system effects. Surprisingly, balancing prices are predictable out of sample and a regime switching specification is more accurate than a linear model for prediction. [ABSTRACT FROM AUTHOR]

Among other things, in a detailed analysis of circumstances in power systems of great importance is the knowledge on contribution of individual generators to loads, and to currents and power losses in network elements. This work proposes an efficient method for obtaining these details. The method uses results of a power flow calculation, utilizes specific power system model, and applies the superposition theorem. The method does not contain problematic assumptions or simplifications and it is easy to apply. It allows getting important facts enabling us to establish transparent and non-discriminatory relationships between network operators, electricity producers and consumers. [ABSTRACT FROM AUTHOR]

In recent years, there have been increasing concerns about how geomagnetic disturbances (GMDs) impact electrical power systems. Geomagnetically induced currents (GICs) can saturate transformers, induce hot spot heating, and increase reactive power losses. These effects can potentially cause catastrophic damage to transformers and severely impact the ability of a power system to deliver power. To address this problem, we develop a model of GIC impacts to power systems that includes 1) GIC thermal capacity of transformers as a function of normal alternating current (AC), and 2) reactive power losses as a function of GIC. We use this model to derive an optimization problem that protects power systems from GIC impacts through line switching, generator redispatch, and load shedding. We employ state-of-the-art convex relaxations of AC power flow equations to lower bound the objective. We demonstrate the approach on a modified RTS96 system and the UIUC 150-bus system and show that line switching is an effective means to mitigate GIC impacts. We also provide a sensitivity analysis of optimal switching decisions with respect to GMD direction. [ABSTRACT FROM PUBLISHER]

We propose a stochastic mathematical program for finding the optimal location and compensation level of thyristor-controlled series compensators (TCSCs) and the optimal location of line switches in a transmission network. The combined uncertainty of the load and generation is captured by scenarios. The proposed problem has polynomial constraints, and we use the general linearization technique to linearize those constraints. The model becomes decomposable into a primal master and subprograms solvable by a branch-and-price procedure with the aid of column generation. The numerical results of implementing the model for the IEEE 118-bus test system show that combined investment in TCSCs and switches decreased the cost of energy and increased the penetration of wind energy more than individual investment of TCSCs or switches. [ABSTRACT FROM AUTHOR]

We present a rolling decision-making process for electrical power systems, in which unit commitment, dispatch and reserve policies are co-optimized in order to minimize expected short-run operating costs in the presence of uncertainty arising from demand and renewable infeeds. The uncertainty is assumed to be bounded, with estimated first and second moment statistics available. The rolling “look-ahead” process employs a planning horizon of several hours, with re-optimization taking place each time the first step has been implemented. We present an expected-cost formulation incorporating multi-stage recourse on continuous decision variables—plans for adjusting the dispatch in the light of future information to be discovered at each stage of the optimization horizon. The generic formulation allows the flexibility of devices such as energy storage units to be exploited in the reserve mechanism. We demonstrate using closed-loop numerical tests that significant reductions in the cost of accommodating uncertainty are attainable relative to a time-decoupled reserve mechanism. In contrast to previous results, we show that a time-coupled cost function is not required for this benefit to be observed. In addition, we show that relaxing binary unit commitment decisions after the first step of the horizon brings significant computational speed-ups, and in some cases also reduce closed-loop system operation costs. [ABSTRACT FROM AUTHOR]

Line switching provides the flexibility for an operator to reduce the operation cost by switching some lines. However, the issue of multiple solutions in the existing models has never been explored and addressed. This will make the traditional models fail to determine the best line switching strategy in the context of multiple solutions. In this letter, we demonstrate that the multiple solution issue in line switching is very significant and propose a multi-objective optimization approach to address the multiple solutions of line switching. The simulation results on the IEEE 118-bus and IEEE 300-bus systems verify the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]