Search

This paper proposes an optimization approach for day-ahead reactive power planning to improve voltage security in transmission networks. The problem is formulated as a voltage-secure multi-period optimal reactive power dispatch (MP-ORPD) problem. The optimization approach searches for optimal set-points of dynamic and static reactive power (var) resources. Specifically, the output includes set-points for switching shunts, transformer taps, and voltage magnitudes at the regulated buses. The primary goal is to maximize the dynamic reactive power reserve of the system, by minimizing the reactive power supplied by synchronous generators. As the size of the MP-ORPD problem increases significantly with increasing number of contingencies and time periods, efficiency is crucial for practical applications. In this paper, a decomposition technique based on consensus and alternating optimization, where integer variable targets are obtained via MILP, is used to partition the MP-ORPD problem into a set of subproblems, which can be solved in parallel to reduce the computation time. The proposed MP-ORPD problem and its solution algorithm are integrated into the EPRI-VCA software. The results of various power networks of large electric utilities in the Eastern interconnection demonstrate the effectiveness of the proposed algorithm in providing preventive control schedules. [ABSTRACT FROM AUTHOR]

Severe geomagnetic disturbances (GMDs) increase the magnitude of the electric field on the Earth’s surface (E-field) and drive geomagnetically-induced currents (GICs) along the transmission lines in electric grids. These additional currents can pose severe risks, such as current distortions, transformer saturation and increased reactive power losses, each of which can lead to system unreliability. Several mitigation actions (e.g., changing grid topology) exist that can reduce the harmful GIC effects on the grids. Making such decisions can be challenging, however, because the magnitude and direction of the E-field are uncertain and non-stationary. In this paper, we model uncertain E-fields using the distributionally robust optimization (DRO) approach that determines optimal transmission grid operations such that the worst-case expectation of the system cost is minimized. We also capture the effect of GICs on the nonlinear AC power flow equations. For solution approaches, we develop an accelerated column-and-constraint generation (CCG) algorithm by exploiting a special structure of the support set of uncertain parameters representing the E-field. Extensive numerical experiments based on “epri-21” and “uiuc-150” systems, designed for GMD studies, demonstrate (i) the computational performance of the accelerated CCG algorithm, (ii) the superior performance of distributionally robust grid operations that satisfy nonlinear, nonconvex AC power flow equations and GIC constraints, in comparison with standard stochastic programming-based methods during the out-of-sample testing. [ABSTRACT FROM AUTHOR]

Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. In this paper, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice. [ABSTRACT FROM AUTHOR]

Since the wide application of virtual synchronous generators (VSGs), the power grid faces great challenges in the safe and stable operation due to their limited thermal capacity and weak anti-disturbance ability. During transient period, for example, a fault occurs in the transmission line, the VSG may lose the transient angle stability and provoke the current hard limit. Even if the fault is cleared by tripping of line, it still faces the problem of instability and voltage dips. To address this problem, in this paper, the post-fault large-signal model of VSG is derived first via the travelling waves based fault information acquisition. Subsequently, with the effect of both active and reactive power loops taken into account, a two-stage simultaneous control scheme is proposed for improving the transient stability of VSG, while considering the current limitation during fault state and voltage support after fault clearance. This method is fulfilled by mode switching and an additional feedback control based on the fault signal. Finally, the effectiveness of the proposed method under both symmetrical and asymmetrical faults is verified. Moreover, the application of the proposed method in a multiple VSGs system is also verified. Besides, the robustness to parameter mismatch and the feasible operating region for the method are discussed. [ABSTRACT FROM AUTHOR]

Volt/VAr Optimization (VVO) is becoming increasingly crucial in distribution management systems with renewable sources that require setting their reactive power in coordination with legacy voltage and reactive power control devices. This paper presents a VVO method that operates in complex variables based on the Wirtinger calculus; it employs a penalty method that keeps voltage magnitudes and controller parameters within limits together with a probabilistic rounding technique for handling switched device variables. The complex variable implementation permits using the compensation technique when solving the Karush-Kuhn Tucker (KKT) system, thus achieving a significant speedup due to limiting the number of linear system factorizations. The proposed method is contrasted with a classical VVO implementation employing discrete coordinate search from the current operating point and an enhanced version that uses sensitivity information. Numerical results on distribution networks having up to 3147 nodes show that the proposed method is significantly faster than classical methods and gives operating points free of voltage magnitude violations and lower power loss. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage energy management scheme (EMS) for AC–DC hybrid smart distribution systems (DSs). The proposed EMS is formulated as a multi-objective optimization problem to minimize the DS operation costs and energy losses. The proposed EMS is achieved in two stages. In the first stage, a network reconfiguration algorithm determines the optimal day-ahead reconfiguration schedule for a hybrid DS. In the second stage, a real-time optimal power flow algorithm determines the real-time operational schedule of the energy resources. This paper also introduces a new linearized power flow model for AC–DC hybrid DSs. This new model facilitates the formulation of the first-stage algorithm as a mixed-integer linear programming problem and the formulation of the second-stage algorithm as a linear programming problem. The proposed two-stage EMS was tested on a case study of a hybrid DS that included different types of loads and distributed generators. The results demonstrate the efficacy of the proposed EMS: the optimal day-ahead reconfiguration schedule was successfully obtained in the first stage, and the proper and optimal real-time operation was achieved in the second stage. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme. [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]

In this paper, a methodology to solve the optimal reactive power dispatch (ORPD) in electric power systems (EPS), considering discrete controllers, is proposed. Discrete controllers, such as the tap position of on-load tap changing (OLTC) transformers and switchable reactive shunt compensation, are optimized by the proposed method. A semidefinite relaxation (SDR) of the ORPD problem and a branch-and-bound (B&B) algorithm have been fully deployed. A new formulation is presented for the OLTC transformers to obtain a connected structure of the semidefinite programming (SDP) matrices. The customized B&B algorithm deals with the discrete nature of the binary control variables. Moreover, in order to enhance the convexification, valid inequalities called lifted nonlinear cuts (NLC) are implemented in the SDR. Additionally, a chordal decomposition technique is used to improve the computational performance. Finally, the B&B algorithm is used to solve the mixed-integer semidefinite programming problem. Several benchmarks have been used to show the accuracy and scalability of the proposed method, and convergence analysis shows that near-global optimal solutions are generated with small relaxation gaps. [ABSTRACT FROM AUTHOR]

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale-separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). The resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications.Simulation based analysis on IEEE distribution feeders validates the approach. [ABSTRACT FROM AUTHOR]

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]

Topology control has garnered recent consideration for its value in leveraging the flexiblity of the power system. However, using even the latest technology, the AC optimal transmission switching (ACOTS) problem remains intractable. As such, most research addressing optimal topology control is based on the DCOPF, which has been shown to be particularly inaccurate for transmission switching decisions in the AC power system. This paper accelerates an existing mixed-integer linear power flow model which has been shown to be very accurate in approximating AC power flows. The aim of the new model is to identify transmission switching candidates to prevent load shed caused by contingency events. The methodology was tested on the IEEE 118-bus test case system and presents promising results. The model proposed herein was found to almost always identify AC optimal switching actions while significantly reducing the necessary solution time in comparison with the base model. [ABSTRACT FROM AUTHOR]

This paper summarizes simulation based technical feasibility and cost benefit analyses of a range of off-the-shelf electrical losses reduction intervention solutions in the Isle of Wight (IoW) 11 kV distribution network in the United Kingdom (UK), assessed over a period of 45 years. Based on presented results, the paper provides a brief commentary on the merits, drawbacks, risks and recommendations associated with each considered network intervention. Among considered network interventions, the transformer auto stop-start scheme, where one of the transformers among a pair at a primary substation would be switched depending on the substation's varying load, was found to be the optimal solution, i.e., in reducing technical losses significantly and may also have a reasonable Net Present Value (NPV) with a good rate of Return on Investment (RoI) when fully implemented. [ABSTRACT FROM PUBLISHER]

The new IEEE 1547-2018 standard includes dynamic Volt/VAr control for photovoltaic (PV) smart inverters. While recent research has addressed the problem of optimal inverter dispatch, the interaction between inverters and the classical Volt/VAr control (VVC) regulation system needs further study. This paper proposes an approach that builds on the classical VVC solution with PVs, by computing for each inverter a rule that modulates the smart inverter reactive power in function of its real power. Two approaches are presented for computing the inverter's reactive power equation slope: the first approach is based on the robust minimization of the absolute voltage magnitude deviation via a linear program, whereas the second approach yields closed-form solutions inspired from distributionally robust chance constraints. Numerical results are presented on weakly meshed distribution networks having up to 3146 nodes; they demonstrate that the voltage violations due to intermittent real power variations are significantly reduced by the decision rules as compared to maintaining the last computed VVC set-points, even when the inverters operate at constant power factor or with default Volt/VAr settings proposed in the literature; additionally, the reactive power decision rules maintain a network loss level that is close to the average from a centralized solution. [ABSTRACT FROM AUTHOR]

The ever-increasing utilization of sensitive loads in the industrial, commercial, and residential areas in distribution networks requires enhanced reliability and quality of supply. This can be achieved, thanks to self-healing features of smart grids that already include the control technologies necessary for the restoration strategy in case of a fault. In this paper, an analytical and global optimization model is proposed for the restoration problem. A novel mathematical formulation is presented for the reconfiguration problem reducing the number of required binary variables while covering more practical scenarios compared to the existing models. The considered self-healing actions besides the network reconfiguration are the nodal load-rejection, the tap setting modification of voltage regulation devices (incl. OLTCs, SVR, and CBs), and the active/reactive power dispatch of DGs. The voltage dependency of loads is also considered. Thus, the proposed optimization problem determines the most efficient restoration plan minimizing the number of de-energized nodes with the minimum number of self-healing actions. The problem is formulated as a Mixed-Integer Second Order Cone Programming (MISOCP) and solved using the Gurobi solver via the MATLAB interface YALMIP. A real 83–node distribution network is used to test and verify the presented methodology. [ABSTRACT FROM AUTHOR]

To solve the coordinated dispatch and time-space coupling problem in the distribution network with distributed generations (DGs), a novel two-stage (Heuristic search and Variable correction) dynamic reactive power dispatch strategy is proposed in this paper. Meanwhile, according to the analysis of Gauss-type and Z-type membership function, a new objective function is put forward to achieve the balance between network loss and voltage deviation. First, the pre-optimization is made in Niche genetic algorithm to coordinate on-load tap changer (OLTC), capacitor banks (CBs), and DGs. Second, the sequential fuzzy c-means (SFCM) based on artificial bee colony (ABC) algorithm is proposed and then the Heuristic search based on this method is used to formulate the day-ahead plans of OLTC and CBs. Finally, the dispatch plans of OLTC and CBs are applied to recalibrate the day-ahead dispatch plans of DGs. Comparing with existing schemes, strategies and optimization approaches based on diverse evaluation indicators, optimization results on IEEE 33-bus, IEEE 14-bus, and PG&E 69-bus test systems verify the practicality and efficiency of the proposed method. In addition, the effects on the optimization results with different adjustment step and action time of the discrete adjust devices are discussed by the IEEE 33-bus test system. [ABSTRACT FROM AUTHOR]

Smart inverters provide additional control capability to help optimize the operation of distribution systems. This paper proposes a framework for exact optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and voltage regulators in large multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV active power curtailment, and operations of capacitors and voltage regulators, in addition to elimination of voltage violations and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem. Effective computational strategies are proposed to allow the application of predictor-corrector primal-dual interior point method to solve optimization problems in real-time with a large number of constraints and variables, including discrete variables corresponding to switched capacitors and voltage regulators. The accuracy of the numerical solution and the ability to implement the proposed framework are validated using the unbalanced multi-phase IEEE 34-bus and EPRI 2,998-bus distribution systems with 15-minute load and PV data. The results show a significant loss reduction and elimination of both voltage violations and reverse power flow. [ABSTRACT FROM AUTHOR]

Geomagnetically induced currents (GICs) can increase the reactive power loss in transformers and potentially cause permanent damage due to overheating. This paper considers line switching as a remedial action to protect transformers from geomagnetic disturbances. The algorithm uses linear sensitivity analysis to find an effective switching strategy, which minimizes the number of opened lines subject to satisfying the transformer thermal limits. To reduce the computational complexity for large-scale power systems, the critical lines are identified through sensitivity analysis and the optimization is performed on the reduced system. Furthermore, the effect of GICs on the ac power flow solution is modeled and heuristic techniques are developed to provide sufficient security measures in terms of both GIC flows and ac analysis. Finally, a multiaction solution with an alternating schedule is developed for severe storms when the losses are significant and a single switching action cannot remove the stress from all transformers at a time. The actions are obtained through a recursive algorithm, which divides the original problem into smaller subproblems with fewer constraints and solves them recursively. The effectiveness of the proposed algorithm is demonstrated through numerical results using a 150-bus and a 2000-bus system. [ABSTRACT FROM AUTHOR]

This paper considers line switching as a remedial action to mitigate the geomagnetically induced currents (GICs) in large-scale power syste-kazerooni-2753840ms. The algorithm uses linear sensitivity analysis to find the best switching strategy which minimizes the GIC-saturated reactive power loss. Furthermore, the coupling between the ac power flow solution and the GIC flows is modeled and heuristic strategies are designed to maintain the system security measures in terms of both GICs and ac power flow. Finally, the computational complexity of the algorithm is analyzed for large-system implementations. To reduce the complexity, the critical lines are identified through the sensitivity analysis and the calculations are performed only on the reduced system. The effectiveness of the proposed algorithm is demonstrated through numerical results using a small 20-bus test case as well as large power systems. [ABSTRACT FROM PUBLISHER]

Estimation-based indirect dc-voltage control in MMCs interacts with circulating current control methods. This paper proposes an estimation-based indirect dc-voltage control method for MMC-HVDC systems and analyzes its performance compared to alternative estimations. The interactions between estimation-based indirect dc-voltage control and circulating current control methods, active/reactive power regulation are also investigated. The proposed method delivers similar performance to measurement-based direct dc-voltage control, regardless of the circulating current control method. Steady-state and transient performance is demonstrated using a benchmark MMC-HVDC transmission system, implemented in a real-time digital simulator. The results verify the theoretical evaluations and illustrate the operation and performance of the proposed indirect dc-voltage control method. [ABSTRACT FROM PUBLISHER]

Voltage instability occurs when a power system is unable to meet the reactive power demand, and is typically corrected by switching on additional reactive power devices such as capacitor banks. Real-time monitoring and communication technologies can potentially improve voltage stability by enabling the rapid detection of low voltages and the implementation of corrective actions. These corrective actions, however, will only be effective in restoring stability if they are chosen in a timely, scalable manner. In this paper, we propose a submodular optimization approach for designing a control strategy that prevents voltage instability. Our key insight is that the voltage deviation from the desired level is a supermodular function of the set of reactive power injections that are employed, leading to computationally efficient control algorithms for stabilization with provable optimality guarantees. This submodular control framework is tested on the IEEE 300-bus transmission system. [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 presents a new control method, in which a distributed generator (DG) actively participates in steady-state voltage control, together with an under-load tap changer (ULTC) and shunt capacitors (Sh.Cs). In the conventional DG control method, the integration of DGs into a distribution power system increases the number of switching operations of the ULTC and the Sh.Cs. To solve this problem, this paper proposes that the DG output voltage be dispatched cooperatively with the operation of the ULTC and the Sh.Cs, based on load forecasts for one day in advance. The objective of the proposed method is to decrease the number of switching device operations, as well as to reduce the power loss in the distribution lines, while maintaining the grid voltage within the allowed range. The proposed method is designed and implemented with Matlab, using two different dynamic programming algorithms for a dispatchable and a nondispatchable DG, respectively. Simulation studies demonstrate that the objective can be achieved under various grid conditions, determined by factors such as the DG output power characteristics, the location of the DG-connected bus on the feeder, and the load profile of the feeder containing the DG. [ABSTRACT FROM PUBLISHER]

The discrete coordinate-descent algorithm is a practical approach that is currently used in centralized Volt/VAr Control (VVC) implementations, mainly due to its good performance and speed for real-time applications. Its viability is however challenged by the increasing number of distributed generation that contribute to the VVC solution, in addition to the conventional transformer taps and switched capacitors. This paper presents the exact computation of sensitivity factors that speed up the discrete coordinate-descent implementation, by significantly reducing the number of forward/backward substitutions in the current injection power flow method; the speed up is achieved without affecting the control setting quality of the original implementation. The optimality of the discrete coordinate-descent solutions is investigated by computing the gaps relative to mixed-integer linear programming set-points, derived from a polyhedral reformulation of the VVC problem. The sensitivity-based discrete coordinate-descent algorithm is tested starting from two initial points, the default one given by the current control set-points, and a continuous solution obtained from a linear approximation of the VVC problem. Numerical results on networks with up to 3145 nodes show that the sensitivity-based approach significantly improves the runtime of the discrete coordinate-descent algorithm, and that the linear programming initialization leads to VVC solutions with gaps relative to the mixed-integer set-points that are less than 0.5%. [ABSTRACT FROM PUBLISHER]

This paper proposes a new formulation for the optimum reconfiguration of islanded microgrid (IMG) systems. The reconfiguration problem is casted as a multi-objective optimization problem, in order to: 1) minimize the IMG fuel consumption in the operational planning horizon for which islanded operation is planned; 2) ensure the IMG capability to feed the maximum possible demand by enhancing its voltage instability proximity index taken over all the states at which the islanded system may reside; and 3) minimize the relevant switching operation costs. The proposed problem formulation takes into consideration the system's operational constraints in all operating conditions based on the consideration of the uncertainty associated with renewable resources output power and load variability. Moreover, the proposed formulation accounts for droop controlled IMG special operational characteristics as well as the availability/unavailability of a supervisory microgrid central controller (MGCC). The formulated problem is solved using non-dominated sorting genetic algorithm II (NSGA-II). MATLAB environment has been used to test and validate the proposed problem formulation. The results show that the implementation of appropriate IMG reconfiguration problem formulations will enhance the performance of IMG systems and facilitate a successful integration of the microgrid concept in distribution networks. [ABSTRACT FROM AUTHOR]

Most existing approaches for distribution network reconfiguration assume that the distribution system is (three-phase) balanced and a single-phase equivalent is used. However, distribution feeders are usually unbalanced due to a large number of single-phase loads, nonsymmetrical conductor spacing, and three-phase line topology. This paper builds on our previous work and studies feeder reconfiguration for unbalanced distribution systems with distributed generation (DG). The three-phase bus locations and sizes of DG units are determined using sensitivity analysis and nonlinear programming, respectively, and distribution feeders are reconfigured every hour based on the status of time-varying loads, output power from DG units and faults on the network while minimizing the energy loss costs and DG operating costs. Simulation results show the effectiveness and computational efficiency of the proposed approach. [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]

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]

With the increasingly high demand for well-trained power systems engineers, the University of Pittsburgh has partnered with Eaton in the creation of the new Electric Power Systems Laboratory at the Swanson School of Engineering. This laboratory demands the capability to perform a wide variety of experimental procedures while providing students and researchers with a seamless working environment. To accomplish that goal, a novel lab workbench was developed. This lab workbench integrates the load banks necessary for laboratory procedures with advanced metering, controls and safety features, and contains them within a work station ideally suited for the laboratory space. This paper details the development of those lab workbenches, from concept, to design, to prototype construction, to testing. Additionally, this work describes planned classroom experiments utilizing the developed bench. Ultimately the realized workbench demonstrates its capability to be reconfigured to suit the demands of both education as well as new research projects for undergraduate and graduate studies. [ABSTRACT FROM PUBLISHER]

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 deals with the management of voltage constraints in active distribution systems that host a significant amount of distributed generation (DG) units. To this end we propose a centralized optimization approach which aims at minimizing the amount of MW curtailment of non-firm DG to remove voltage constraints. The salient feature of this approach is that it comprehensively and properly models the full variety of possible control means (i.e., DG active/reactive power including DG shut-down, on load tap changing transformer ratio, shunt capacitor, and remotely controlled switches or breakers), most of which having a discrete behavior. We develop and compare the performances of two optimization models on a snapshot basis for various distribution systems up to 1089 buses. In particular we show that the use of remotely controlled switches so as to transfer DG between feeders in case of voltage constraints may lead to significant reduction of the DG curtailment. [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]

The uptake of variable megawatts from photovoltaics (PV) challenges distribution system operation. The primary problem is significant voltage rise in the feeder that forces existing voltage control devices such as on-load tap-changers and line voltage regulators to operate continuously. The consequence is the deterioration of the operating life of the voltage control mechanism. Also, conventional non-coordinated reactive power control can result in the operation of the line regulator at its control limit (runaway condition). This paper proposes an optimal reactive power coordination strategy based on the load and irradiance forecast. The objective is to minimize the number of tap operations so as not to reduce the operating life of the tap control mechanism and avoid runaway. The proposed objective is achieved by coordinating various reactive power control options in the distribution network while satisfying constraints such as maximum power point tracking of PV and voltage limits of the feeder. The option of voltage support from PV plant is also considered. The problem is formulated as constrained optimization and solved through the interior point technique. The effectiveness of the approach is demonstrated in a realistic distribution network model. [ABSTRACT FROM PUBLISHER]

Deploying shunt capacitor banks in distribution systems can effectively reduce the power loss and provide additional benefits for system operation. In practice, the power loss on distribution transformers can account for a considerable portion of the overall loss. This paper proposes a method for optimal placement of capacitor banks to the distribution transformers to reduce power loss. The capacitor bank locations are considered at the low-side of transformers. The net present value (NPV) criterion is adopted to evaluate the cost benefit of the capacitor installation project. First, an explicit formula for directly calculating the power loss of radial distribution systems is derived. Then, the optimal capacitor bank placement is formulated as a mixed-integer programming (MIP) model maximizing the NPV of the project subject to certain constraints. The model is suitable for being solved by commercial MIP packages, and the operational control of the capacitor banks to maximize the power loss reduction can be simply achieved by local automatic switching according to VAR measurements. The proposed method has been practically applied in the Macau distribution system, and the simulation results show that the proposed method is computationally efficient, and a considerable positive NPV can be obtained from the optimal capacitor bank placement. [ABSTRACT FROM PUBLISHER]

Microgrids are able to provide a coordinated integration of the increasing share of distributed generation (DG) units in the network. The primary control of the DG units is generally performed by droop-based control algorithms that avoid communication. The voltage-based droop (VBD) control is developed for islanded low-voltage microgrids with a high share of renewable energy sources. With VBD control, both dispatchable and less-dispatchable units will contribute in the power sharing and balancing. The priority for power changes is automatically set dependent on the terminal voltages. In this way, the renewables change their output power in more extreme voltage conditions compared to the dispatchable units, hence, only when necessary for the reliability of the network. This facilitates the integration of renewable units and improves the reliability of the network. This paper focusses on modifying the VBD control strategy to enable a smooth transition between the islanded and the grid-connected mode of the microgrid. The VBD control can operate in both modes. Therefore, for islanding, no specific measures are required. To reconnect the microgrid to the utility network, the modified VBD control synchronizes the voltage of a specified DG unit with the utility voltage. It is shown that this synchronization procedure significantly limits the switching transient and enables a smooth mode transfer. [ABSTRACT FROM PUBLISHER]

This paper proposes a new coordinated voltage control scheme to ensure voltage security of power systems. The scheme schedules reactive power injection from VAR sources, including synchronous generators and condensers, capacitor banks, switchable reactors and FACTS devices, to ensure desired loading margin of power systems for a given horizon of time. The problem is treated as voltage security constrained multi-period optimal reactive power flow (VSC-MPORPF). To incorporate scheduling of both continuous and discrete VAR sources, the VSC-MPORPF is formulated as a mixed-integer nonlinear programming problem, and is solved using generalized Benders decomposition (GBD). Multi-period formulation ensures both optimal switching pattern of discrete voltage controllers and voltage security for a given future horizon. Also, to make the proposed method applicable for large-scale power systems, optimality condition decomposition approach is utilized, along with the GBD. The proposed methodology is examined through case studies conducted on a simple 6-bus, the IEEE 118-bus, and a 1180-bus test systems. The results demonstrate effectiveness and efficiency of the proposed framework in real-time operation of power systems. [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 this paper, an electromagnetic transient model for fixed-speed wind turbines equipped with induction generators is developed and implemented in PSCAD/EMTDC. The model is comprised by: an induction generator, aerodynamic rotor, and a two-mass representation of the shaft system. Model validation is conducted by measurement comparison using recordings obtained from switching operations performed at the Nysted Offshore Wind Farm in Denmark. A sensitivity analysis is performed to determine the impact of different model parameters on the simulated response as compared with measurements. This validated model will be used for assessing induced overvoltage conditions that may arise under switching operations similar to those captured by the measurements used for validation. [ABSTRACT FROM PUBLISHER]