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The work reported in this paper aims at developing an algorithm for system operators to solve a robust security-constrained AC optimal power flow (R-SC-ACOPF) problem, which also optimizes the settings of discrete controllers including load tap changers (LTCs) and shunt capacitor banks (SCBs). An iterative algorithm involving a master problem and a number of sub-problems is proposed. The master problem selects the optimal discrete controllers’ settings by taking into account primal SC-ACOPF constraints based on the single-component worst contingencies identified by the sub-problems. Each sub-problem is a bi-level max-min problem used to find the current worst contingency. The overall objective is to minimize the total cost, including generation and load shedding cost, while satisfying all relevant constraints. The master problem and sub-problems allow representing LTC tap positions, SCB status, and contingencies using binary variables. Two case studies are presented as applications of this novel technique. [ABSTRACT FROM AUTHOR]

This paper is concerned with a fuzzy analysis of power-flow (PF) involving uncertainties of load demands and network parameters. The crux of this paper is to propose an advanced fuzzy arithmetic. Fuzzy transformation method merges with backward–forward sweep in order to evaluate the contribution and propagation of uncertainty in IEEE 33-bus and 69-bus distribution systems. Results are validated by true intervals and random ranges. To determine true intervals, Global Optimization Problems (GOPs) are defined and solved through derivative-based and free techniques. To estimate random ranges, Monte-Carlo Simulations (MCSs) are employed. Our findings confirm that the sharpness of fuzzy intervals, tractability of computations, and applicability of possibility distributions. Following scenario-based evaluations, this paper discusses new implications of power losses, voltage profiles, optimal re-configuration, feeder extension, and reactive power compensation so that results would be beneficial to system planners and operators. Altogether, this paper provides a blueprint for a new way to handle uncertainties in a wide variety of power system problems without global optimization, linearization, and randomized simulations. [ABSTRACT FROM AUTHOR]

As the inverter-based generation replaces the conventional synchronous generators, it may also need to fill in the missing ancillary service support. One of these ancillary services is dynamic reactive power provision and voltage control. This paper analyzes optimal strategy of reactive and active fault-current support of the inverter-based generation leading to fast voltage recovery of the system. For the purpose of the analysis, new ramping active current controller able to emulate different behavior of active current injection is proposed. By optimizing its parameters for different case studies of the system, the conclusions about optimal behavior of the inverter based generation with respect to system parameters and operating conditions are drawn. It is observed that the optimal combination of active and reactive fault-current is the most sensitive to the dynamic load component penetration levels in the system. With the increasing penetration levels, the significance of active fault-current injection increases. The results show that with higher penetration levels of dynamic load component in the heavy load areas, the ramping down of the inverter-based generation active fault-current results in slower voltage recovery of the system. Following this conclusion, a recommendation on update of current European grid codes is proposed. [ABSTRACT FROM AUTHOR]

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]

Microgrid's voltage regulation is of particular importance during both grid-connected and islanded modes of operation. Especially, during the islanded mode, when the support from the upstream grid is lost, stable voltage regulation is vital for the reliable operation of critical loads. This paper proposes a robust and data-driven control approach for secondary voltage control of AC microgrids in the presence of uncertainties. To this end, unfalsified adaptive control (UAC) is utilized to select the best stabilizing controller from a set of pre-designed controllers with the minimum knowledge required from the microgrid. Two microgrid test systems are simulated in MATLAB to verify the effectiveness of the proposed method under different scenarios like load change and communication link failure. [ABSTRACT FROM AUTHOR]

The commutation failure (CF) is the most common fault in line-commutated high voltage direct current (LCC-HVDC) systems that may lead to the transient overvoltage in the sending-side system. In the worst condition, the CF may lead to large-scale wind turbine tripping. To resolve this problem, the mathematical relationship between the reactive power consumed by the rectifier and DC voltage, DC current is derived. Then, a transient overvoltage calculation method is proposed in this paper. Furthermore, the mechanism of transient overvoltage caused by the CF is analyzed; it is revealed that the reason for three times transient overvoltage is the rapid decrease of the reactive power consumed by the rectifier during the CF and the recovery period from the CF. This paper proposes a constant reactive power control (CRPC) to inhibit transient overvoltage of the sending-side AC system. The proposed CRPC can increase the reactive power consumed by the rectifier, reduce the exchange reactive power between AC and DC systems, and suppress the transient overvoltage. A simulation model in PSCAD serves to verify the proposed CRPC on the transient overvoltage suppression in the situation of different fault types, fault duration, fault severity and short circuit ratio (SCR). [ABSTRACT FROM AUTHOR]

The paper considers the problem of sub-synchronous resonances (SSR) in doubly fed induction generators connected to the grid through series-compensated lines. The existence of oscillations is observed on a laboratory test-bed in various conditions, with instabilities developing in the worst-case scenario. Despite the limitations of a small-scale test-bed, the ability to investigate problems and solutions in ways that would not be possible on a full-scale system is very valuable. In particular, the paper demonstrates the significant effect of the choice of dq reference frame on the severity of SSR. Stator-aligned algorithms are found to be significantly more resonant than grid-oriented algorithms, as evidenced in experiments as well as using an analysis method proposed in the paper. From this observation, an algorithm is proposed to emulate a grid-alignment using stator voltages and currents, but without measurements of the grid and series-capacitor voltages. Two control laws are then presented to regulate the active and reactive powers generated, resulting in well-damped transient responses. SSR oscillations are found to be eliminated in experime, as well as simulations of a full-scale system and using a frequency response analysis of the closed-loop system. The effectiveness of the proposed control schemes is verified through experiments for different compensation levels and varying speeds. Within the assumptions made in the design, the proposed controllers are global. [ABSTRACT FROM AUTHOR]

Volt-VAR optimization (VVO) has been investigated extensively in power systems. However, under the era of integrated energy systems (IES), the growing interdependencies between different energy systems complicate traditional VVO. This is further hardened by incurred gas quality problems due to the hydrogen injection in IES, produced by widely applied power-to-gas (P2G) facilitates that couple between power and gas systems. This paper develops a two-stage volt-VAR-pressure optimization (VVPO) model for PV-penetrated IES to manage the variation of system voltages while managing gas quality indices. In addition to the traditional voltage regulating devices, P2G facilities, which can mitigate fluctuating PV output via converting the surplus generation into hydrogen, are also used for voltage management. A two-stage distributionally robust optimization (DRO) based on moment information is utilized to model PV uncertainty. A semidefinite programming model is formulated and finally solved by the constraint generation algorithm. A 33-bus-20-node IES is used to verify the effectiveness of the proposed VVPO on voltage management, ensured gas quality with high economic efficiency. The proposed VVPO is applicable to injecting other green gases into gas systems while ensuring power quality and enable system operators to provide low-cost but high-quality multi-energy to customers. [ABSTRACT FROM AUTHOR]

The paper introduces the concept of complex frequency. The imaginary part of the complex frequency is the variation with respect of a synchronous reference of the local bus frequency as commonly defined in power system studies. The real part is defined based on the variation of the voltage magnitude. The latter term is crucial for the correct interpretation and analysis of the variation of the frequency at each bus of the network. The paper also develops a set of differential equations that describe the link between complex powers and complex frequencies at network buses in transient conditions. No simplifications are assumed except for the usual approximations of the models utilized for the transient stability analysis of power systems. A variety of analytical and numerical examples show the applications and potentials of the proposed concept. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new mathematical model for power flow problem based on the linear and nonlinear matrix inequality theory. We start with rectangular model of power flow (PF) problem and then reformulate it as a Bilinear Matrix Inequality (BMI) model. A Theorem is proved which is able to convert this BMI model to a Linear Matrix Inequality (LMI) model along with One Nonconvex Quadratic Constraint (ONQC). Our proposed LMI-ONQC model for PF problem has only one single nonconvex quadratic constraint irrespective of the network size, while in the rectangular and BMI models the number of nonconvex constraints grows as the network size grows. This interesting property leads to reduced complexity level in our LMI-ONQC model which in turn makes it easier to solve for finding a PF solution. The non-conservativeness, iterative LMI solvability, well-defined and easy-to-understand geometry and pathwise connectivity of feasibility region are other important properties of proposed LMI-ONQC model which are discussed in this paper. An illustrative two-bus example is carefully studied to show different properties of our LMI-ONQC model. We have also tested our LMI-ONQC model on 30 different power-system cases including four ill-conditioned systems and compared it with a group of existing approaches. The numerical results show the promising performance of our LMI-ONQC model and its solution algorithm to find a PF solution. [ABSTRACT FROM AUTHOR]

This paper establishes an instantaneous voltage model to illustrate the dynamic characteristics of grid voltage in electromagnetic time scale affected by power-electronic interfaced voltage regulatory devices with two typical categories of control systems, i.e., power-current cascading control and power synchronization control, exemplified by the STATCOM and virtual synchronous condenser (VSCON) respectively. In this paper, a linearized instantaneous voltage model is firstly established to analyze the impact paths of control loops in the STATCOM and VSCON. Based on the model, the dynamic process of grid voltage is divided into three stages. Various factors on the dynamic process of grid voltage are analyzed, especially cascading control loops prior to the functioning of AC voltage control. Moreover, stiffness characteristic is proposed to evaluate the effects of power electronic interfaced voltage regulatory devices with different control structures. In addition, the effectiveness of the stiffness compensation based on the VSCON is validated by the study cases. [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]

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]

The wide variety of inverter control settings for solar photovoltaics (PV) causes the accurate knowledge of these settings to be difficult to obtain in practice. This paper addresses the problem of determining inverter reactive power control settings from net load advanced metering infrastructure (AMI) data. The estimation is first cast as fitting parameterized control curves. We argue for an intuitive and practical approach to preprocess the AMI data, which exposes the setting to be extracted. We then develop a more general approach with a data-driven reactive power disaggregation algorithm, reframing the problem as a maximum likelihood estimation for the native load reactive power. These methods form the first approach for reconstructing reactive power control settings of solar PV inverters from net load data. The constrained curve fitting algorithm is tested on 701 loads with behind-the-meter (BTM) PV systems with identical control settings. The settings are accurately reconstructed with mean absolute percentage errors between 0.425% and 2.870%. The disaggregation-based approach is then tested on 451 loads with variable BTM PV control settings. Different configurations of this algorithm reconstruct the PV inverter reactive power timeseries with root mean squared errors between 0.173 and 0.198 kVAR. [ABSTRACT FROM AUTHOR]

This paper presents a novel hierarchical cooperative control strategy to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable bus voltage for battery storage system (BSS) in islanded DC microgrid. In the communication layer, a neighbor-to-neighbor communication network architecture is constructed in which each battery storage unit (BSU) only communicates information with neighboring nodes, and a multi-agent consensus algorithm is used to iteratively estimate the relevant average global variables. In the main control layer, the droop coefficient is dynamically adjusted by constructing a fast SoC convergence function to ensure that the load current is reasonably distributed based on the rated capacity of each BSU. In the secondary control layer, a virtual voltage drop equalization controller and an average bus voltage compensation controller are designed to eliminate the impact of line impedance mismatch and compensate the average bus voltage. Furthermore, an optimized factor is designed to accelerate the later stage of SoC convergence. Finally, a DC microgrid experimental platform based on StarSim HIL is built, and the results demonstrate that the proposed strategy can achieve the control objectives of fast SoC balance, proportional load current sharing, and bus voltage stability. [ABSTRACT FROM AUTHOR]

This paper proposes a novel contribution factor (CF) approach to predict diversified daily peak load of low voltage (LV) substations. The CF for each LV template developed in part I of the paper is determined by a novel method—clusterwise weighted constrained regression (CWCR). It takes into account the contribution from different customer classes to substation peaks, respecting the natural difference in time and magnitude between LV substation peaks and the variance within the templates. In CWCR, intercept and coefficients are constrained to ensure that the resultant coefficients do not lead to reverse load flow and can respect zero-load substations. Cross validation is developed to validate the stability of the proposed method and prevent over fitting. The proposed method shows significant improvement in the accuracy of peak estimation over the current status quo across 800 substations of different mixes of domestic, industrial and commercial (I&C) customers. The work in the two parts of the paper is particularly useful for understanding the capabilities of LV networks to accommodate the increasing penetration of low carbon technologies without large-scale monitoring. [ABSTRACT FROM PUBLISHER]

The modern photovoltaic inverter has an active power-reactive power (Watt-VAr) control curve that is part of its management modes. The Watt-VAr curve, whose settings can be remotely modified, regulates the inverter reactive power output in function of its active power. This paper proposes the optimization of inverter segregated linear decision rules (LDRs), starting from the legacy Volt-VAr optimization in distribution networks. As opposed to classical LDRs that are interfaced with Volt-VAr optimization, the segregated LDRs are piecewise linear continuous curves that directly satisfy the reactive power capability of inverters, and their multiple segments can capture the correlation in solar power variability. The paper presents linear programming formulations for optimizing the segregated linear decision rules using stochastic optimization, robust optimization, and distributionally robust optimization. The optimization schemes are demonstrated on both meshed and radial networks, and their performance is validated via Monte-Carlo simulation. [ABSTRACT FROM AUTHOR]

Distribution power systems (DPSs) are generally unbalanced, and their loads may have notable static voltage characteristics (ZIP loads). Hence, although many papers have focused on linear single-phase power flow models, it is still necessary to study linear three-phase distribution power flow models. This paper proposes a data-driven-aided linear three-phase power flow model for DPSs. We first formulate how to amalgamate data-driven techniques into a linear power flow equation to establish our linear model. This amalgamation makes our linear model independent of the assumptions commonly used in the literature (e.g., nodal voltages are nearly 1.0 p.u.); therefore, our model is characterized by relatively high accuracy, even when the assumptions become invalid. We then demonstrate how to apply our model to DPSs with ZIP loads. We also show that with the Huber penalty function employed, the adverse impact of bad data on our model's accuracy is significantly reduced, rendering our model robust to poor data quality. Case studies demonstrate that our model is generally more accurate, with 2- to 100-fold smaller errors, than most existing linear models, and remains fairly accurate even under poor data conditions. Our model also contributes to a rapid solution to DPS analyses and optimization problems. [ABSTRACT FROM AUTHOR]

Renewable Energy Sources (RESs) integration strengthens the need for a power network that can robustly handle the system’s uncertain scenarios. This paper proposes the first nonlinear novel dual-based bi-level approach for robust AC Transmission Expansion Planning (TEP) with uncertainties in RES generations and loads. It utilizes a convex relaxation and is solved by Benders Decomposition (BD), where the master determines the robust AC expansion plan. The novel dual slave for the second level of BD circumvents the issues in using conventional conic dual theory and aids in the worst-case realization of uncertainties using additional novel constraints. The proposed slave is solved using Interior Point Method (IPM), as it is not a mixed-integer problem. The proposed work includes additional linear constraints to speed up BD’s convergence and direct the master towards optimality. The approach is tested on several transmission systems, including the Indian Northern Regional Power Grid (NRPG) system. The robustness of the obtained plans is verified by Monte-Carlo Simulation (MCS) of the actual nonlinear and nonconvex AC Optimal Power Flow (OPF). The effect of the budget of uncertainty on the AC expansion plan is also investigated. A comparison with two previous works reveals the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Power systems are undergoing fundamental changes with increasing penetration of renewable energies. A reactive power ancillary service market is of significance to incentivize private providers, such as thermal power units and renewable power plants (RPPs), to participate in maintaining voltage security. Because of the local nature of reactive power, one of the recognized issues is that monopolistic participants may have great market power and strategically manipulate their costs. To pursue economic efficiency, this paper proposes an incentive-compatible mechanism based on Vickery-Clarke-Groves (VCG) auctions for the day-ahead reactive power ancillary service market. The obligations of reactive power ancillary service are quantified in the VCG-based market mechanism. Depending on the expected performance of participants compared with the corresponding obligations, payments are obtained for thermal power units, RPPs, and loads. Hence, providers have the incentive to declare their true costs and undertake obligations. Furthermore, a scarcity price is employed to reward the provision of scarce reactive power resources and ensure reliable market clearing. The proposed mechanism is illustrated using the IEEE 24-bus and 118-bus systems. The results verify the effectiveness of the proposed mechanism. Moreover, high rewards or penalties are observed for voltage weak areas, thereby inducing appropriate investments in reactive power capacities. [ABSTRACT FROM AUTHOR]

Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make full use of the EVs’ charging flexibility for improving the operational flexibility of power systems. To this end, this paper proposes a CSs-DSO distributed coordination strategy. The proposed strategy integrates a supply-curve-based quantification method to quantify the EVs’ flexibility contribution and a Nash bargaining game-theory-based peer-to-peer (P2P) transactions model for maximizing the profits of entities participating in the coordination. To tackle the CSs-DSO coordination problem that has a bi-level-parallel coupling structure, an analytical target cascading (ATC) and alternating direction method of multipliers (ADMM) jointly-based distributed solution approach is proposed. First, the CSs-DSO bi-level model is decoupled by ATC with tie-line power being the only exchanged information; then, the model is further decomposed for each CS by ADMM for protecting the CSs’ privacy and autonomy. The effect of coordination and the computational efficiency of the proposed strategy is verified by numerical simulations on a modified IEEE 33-bus distribution system connecting multiple CSs. [ABSTRACT FROM AUTHOR]

The control of reactive power exchange between grids of different voltage levels has always been a concern for system operators. With production moving from the transmission to the distribution level, its importance increases. This paper proposes a novel approach to estimate reactive power capability of the grid as a whole. A linearized analytical model for an estimation of available reactive power exchange at the interface between two grids has been developed. The maximum estimation error for the scenarios we tested was only 2%. The model gives the relation between important grid parameters and the supported reactive power. The conclusions drawn from the model are confirmed on typical Swedish distribution network with scattered wind power and small industry consumers. Common scenarios in development of distribution grids are applied to show relevant parameters influence. One studied scenario is replacement of overhead lines with cables. It is shown that this particular change enhances the reactive power capability of the grid which is directly seen from the analytical analysis without running any optimal power flow. The analytical model proposed in this paper gives fundamental understanding of the reactive power capability of radial distribution grids. [ABSTRACT FROM AUTHOR]

This paper presents an optimization approach for the placement of geomagnetically induced current (GIC) blocking devices (BDs) on power system transformers to mitigate the adverse effects of a geomagnetic disturbance (GMD). Solar storms lead to GMDs which, in turn, drive GICs along transmission lines and through transformer windings. GICs cause half-cycle saturation in power transformers, increase their shunt reactive power loss, lead to a significant lack of power system reactive power support, and, as a result, create voltage instability and, potentially, large-scale voltage collapse. To mitigate these detrimental effects, a long-term remedy is to install GIC BDs at the neutral point of transformers. Since these devices are fairly costly, their placement should be performed in an optimal manner. The optimization problem proposed in this paper minimizes the cost of BD placement while satisfying power system voltage and generator maximum reactive power limits. The numerical results demonstrate the effectiveness of the proposed method in maintaining an acceptable voltage profile for the power system in case of GMDs with any degree of severity. [ABSTRACT FROM AUTHOR]

This paper studies the feasibility of utilizing the reactive power of grid-connected variable-speed wind generators to enhance the steady-state voltage stability margin of the system. Allowing wind generators to work at maximum reactive power limit may cause the system to operate near the steady-state stability limit, which is undesirable. This necessitates proper coordination of reactive power output of wind generators with other reactive power controllers in the grid. This paper presents a trust region framework for coordinating reactive output of wind generators with other reactive sources for voltage stability enhancement. Case studies on 418-bus equivalent system of Indian southern grid indicates the effectiveness of proposed methodology in enhancing the steady-state voltage stability margin. [ABSTRACT FROM PUBLISHER]

Optimal power flow (OPF) programs must be able to provide sound operating points for power systems under different conditions while meeting a large number of constraints. These constraints, however, either due to the operating conditions at hand or by construction, can have linearly dependent gradients, thus defining ill-behaved feasible sets. This paper analyzes the use of an alternative set of optimality conditions, derived from the Fritz-John (FJ) conditions, to represent OPF solutions in such critical cases. Results are presented for realistic test systems. [ABSTRACT FROM PUBLISHER]

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]

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]

Due to the increasing penetration of large-scale renewable energy generation at transmission level, hybrid AC/DC transmission expansion is becoming more relevant by the day, especially if the considered renewable generation is far away from existing AC grid infrastructure. This paper presents a multi-period hybrid AC/DC network expansion planning model that incorporates node voltages, reactive power and network losses. Since the operation of a high voltage DC link is influenced considerably by the converter stations, converter transformer, filter, and phase reactor are modeled in each converter station. Since the AC power flow equations render a non-convex problem whose solution algorithms do not always guarantee convergence or optimality, a second-order conic relaxation is utilized. The resulting model is a mixed-integer convex problem with a convergence guarantee that embodies a better approximation of system operation than its DC linear counterpart. Three case studies are considered to illustrate the proposed model. [ABSTRACT FROM AUTHOR]

Weak grid scenarios and low-inertia systems are emerging issues in power systems, which could lead to voltage and frequency instabilities. Synchronous Condensers (SynCons) have recently drawn renewed attention as a promising solution to provide system strength and inertia support. Even though the exciter control of SynCons is a well-established technology, further developments are required to guarantee the stability of post-fault operations, in particular, in weak grids. This paper proposes a data-driven approach for designing higher-order optimized exciter controllers to meet this requirement. A pseudo-random binary sequence (PRBS)-based system identification method is used to obtain frequency response data of the power system, from the exciter point of view, which is then fed into the proposed optimal control design procedure. The proposed exciter controller is tested for voltage ride-through and fault scenarios in a single machine infinite bus (SMIB) case and the IEEE 39-bus test system to assess its performance compared to the conventional AC1A exciter controller. The results obtained through simulation tests carried out using the PSCAD/EMTDC software verify that the proposed exciter controller guarantees the post-fault stability in both strong and weak grids. [ABSTRACT FROM AUTHOR]

The icing on transmission lines threatens the power system security while the heat caused by power transmission losses can prevent icing growth. This paper proposes a preventive scheduling model for mitigating the glaze icing by optimizing the distribution of power losses on ice-coated transmission lines. An analytical glaze icing growth model is established based on the heat balance theory, which builds a direct relationship between icing growth and power transmission losses. Accordingly, the analytical glaze icing model is embedded into the proposed scheduling model to quantify the impact of power system schedules on transmission line icing and reduce the glaze icing of transmission lines. The scheduling model co-optimizes active power dispatch, demand response, and reactive power optimization for promoting the de-icing effect. To overcome the computational difficulties, the analytical glaze icing growth model is further linearized, and the Lagrangian relaxation method is adopted for identifying a practical solution. Case studies are conducted on different icing scenarios in the IEEE RTS-79 test system to verify the validity of the proposed model. Results show that the proposed preventing scheduling model can avoid the icing on transmission lines for mild ice disasters, while efficiently restraining the icing growth on transmission lines when they cannot be completely de-iced in severe storms. [ABSTRACT FROM AUTHOR]

In this paper, we propose a distributed voltage control in power distribution networks through reactive power compensation. The proposed control can operate in a distributed fashion where each bus makes its decision based on local voltage measurements and communication with neighboring buses, always satisfy the reactive power capacity constraint, drive the voltage magnitude into an acceptable range, and minimize an operational cost. We also perform various numerical case studies to demonstrate the effectiveness and robustness of the controller using the nonlinear power flow model. [ABSTRACT FROM AUTHOR]

This paper focuses on developing an appropriate combinatorial optimization technique for solving the optimal sizing problem of hybrid ac–dc microgrids. A novel two-stage iterative approach is proposed. In the first stage, a meta-heuristic technique based on a tailor-made genetic algorithm is used to tackle the optimal sizing problem, while, in the second, a non-linear solver is deployed to solve the operational problem subject to the obtained design/investment decisions. The proposed approach, being able to capture technical characteristics such as voltage and frequency through a detailed power flow algorithm, provides accurate solutions and, therefore, can address operational challenges of microgrids. Its capability to additionally capture contingencies ensures that the proposed sizing solutions are suitable both during normal operation and transient states. Finally, the genetic algorithm provides convergence of the model with relative computational simplicity. The proposed model is applied to a generalizable microgrid comprising of ac and dc generators and loads, as well as various types of storage technologies in order to demonstrate the benefits. The load and natural resources data correspond to real data. [ABSTRACT FROM AUTHOR]

The integration of the dynamic line rating (DLR) of overhead transmission lines (OTLs) in power systems security constrained unit commitment (SCUC) potentially enhances the overall system security as well as its technical/economic performances. This paper proposes a scalable and computationally efficient approach aimed at integrating the DLR in SCUC problem. The paper analyzes the case of the SCUC with AC load flow constraints. The AC-optimal power flow (AC-OPF) is linearized and incorporated into the problem. The proposed multi-period formulation takes into account a realistic model to represent the different terms appearing in the Heat-Balance Equation (HBE) of the OTL conductors. In order to include the HBE in the OPF, a relaxation is proposed for the heat gain associated to resistive losses while the inclusion of linear approximations are investigated for both convection and radiation heat losses. A decomposition process relying on the Benders decomposition is used in order to breakdown the problem and incorporate a set of contingencies representing both generators and line outages. The effects of different linearization, as well as time step discretization of HBE, are investigated. The scalability of the proposed method is verified using IEEE 118-bus test system. [ABSTRACT FROM AUTHOR]

This paper proposes a method for calculating short-circuit current in distribution systems with inverter interfaced distributed generators (IIDG). It is capable of calculating the short circuit in a multi-phase distribution systems based on the symmetrical components without obtaining the complete impedance matrix. Furthermore, it considers the load effect and the pre-fault state of the system for the fault analysis and is able to handle unbalanced systems with mutually coupled phases. The problem is formulated as an iterative linear system calculation and is solved by generalized minimal residual (GMRES) approach. The validity of the proposed algorithm is verified through the simulation of IEEE 13-node, 123-node, 478-node, 954-node, and 1430-node distribution systems. Simulation results demonstrate the effectiveness of the proposed algorithm and the advantages of using the GMRES method to calculate the short circuit current in a distribution system with IIDG. [ABSTRACT FROM AUTHOR]

Traditional power flow algorithms assume that a slack bus is present and that the frequency is not fluctuating. In islanded industrial systems and microgrids, however, these assumptions are not valid because such systems usually do not have a strong source performing as the slack bus and the system frequency is more prone to vary near nominal frequency. Considering these characteristics, this paper presents a novel universal power flow (UPF) algorithm for industrial systems and microgrids as well as traditional systems, with a focus on active power. Development of a reactive power UPF algorithm will be presented in a subsequent paper. The proposed UPF model has the following merits: first, it can handle islanded and grid-connected systems at nominal or off-nominal frequency; second, it can handle the active control strategies of distributed generators (DGs), such as isochronous (ISOC) control, droop control, or constant power control; third, it can handle the megawatt and megavolt-ampere reactive limitations of ISOC or droop DG units; fourth, it can evaluate system frequency; and finally, it can handle frequency-dependent active and reactive power loads. The proposed UPF model is validated by comparing the results with those obtained from a real-time simulator. [ABSTRACT FROM AUTHOR]

Uncertain power sources are increasingly integrated into distribution networks and causes more challenges for the traditional load modeling. A variety of distributed load components present dynamic characteristics with time-varying parameters. Toward the end, this paper proposes a robust time-varying parameter identification (TVPI) method for synthesis load modeling in distribution networks, including time-varying ZIP, induction motor, and equivalent impedance models. The nonlinear optimization model is developed and solved by the nonlinear least square (NLS) to find the minimum error between estimated outputs and measurements. To cope with TVPI deteriorated by voltage disturbances, dynamic programming is first used to detect the disturbance. Then, a robust TVPI engine is designed to constrain the estimated time-varying parameters within a stable range. Furthermore, advanced tolerance thresholds are also required during iterations of NLS. Numerical simulations on the 9- and 129-bus distribution systems verify the effectiveness and robustness of the proposed TVPI method. Also, this method can be robust to the ambient noise of measurements. [ABSTRACT FROM AUTHOR]

A growing number of inverter interfaced rooftop photovoltaic and battery systems are changing suburban distribution systems. The potential of reactive power support from this equipment is attracting attention as a way of addressing the systems’ voltage magnitude problems. However, if the voltage is controlled by a conventional droop-based strategy, common radial configuration at suburban feeders can cause an uneven allocation of the reactive power compensation among the inverters. A droop control strategy is developed in this paper using two parameters of the steady-state Thévenin equivalent model of the system seen by each inverter. The Thévenin based droop control permits even allocation of the reactive power compensation. A sufficiently invisible low-level probing is utilized by each inverter to robustly identify Thévenin reactance and Thévenin source in steady state. The inverter's output power is adjusted by the two identified parameters. Demand changes are addressed. Interference by the neighbor inverters’ simultaneous probing and compensation is also considered. Simulations results on the IEEE 33-bus and a large-scale system show the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper presents a two-timescale multi-objective coordinated volt/var optimization system for active distribution networks with renewable energy resources (RESs). In the hourly timescale, power loss and the number of control actions of on-load tap changers and (switchable) shunt capacitors for 24 h are minimized by coordinating on-load tap changers, (switchable) shunt capacitors, and reactive power outputs of RESs. A three-step method consisting of global search, user preference, and local search is adopted to solve the corresponding multi-objective mixed-integer nonlinear optimization problem. A rolling volt/var optimization is executed every 6 h, considering the day-ahead RES forecast errors. In the 15-min timescale, the RES reactive powers are optimized with RES uncertainties explicitly taken into consideration to minimize the pilot-bus voltage deviation under all representative scenarios. The pilot buses are those buses whose voltage magnitudes capture the network voltage profile. In this paper, a linear method is applied to quickly identify a set of pilot buses, and the impact of the identified pilot bus on the entire network voltage profile is evaluated. The IEEE 33-bus distribution network is used to evaluate the proposed two-timescale volt/var optimization formulations and methods with promising results. [ABSTRACT FROM AUTHOR]

The distributed Volt/Var control solution is a promising one for active distribution networks (ADNs), but a critical issue is how to improve the distributed algorithm's convergence with less communication burden. In this paper, we propose a bi-level consensus alternation direction multiplier method-based fully distributed Volt/Var optimization algorithm (B-FADMM) for ADNs by exploiting inverter-based rapid control devices. In the first level, the Volt/Var optimal solution of subpartitions is obtained in parallel, and the second level completes the variable increment of each partition to correct the search direction of the first level. In the algorithm, firstly, an adaptive matrix $\omega $ initialization strategy is proposed to adapt to the different magnitude of variables, which avoids non-convergence or slow convergence of the algorithm. Secondly, the null-space method is used in the second level of the algorithm to obtain the null-space basis matrix on the active constraint of the subpartition, which reduces the dimensions of the problem and the computational complexity. In addition, the conjugate gradient (CG) algorithm is used to update the dual multiplier of each partition only by exchanging coupling information among partitions, which protects information privacy. Experiments showed the proposed approach attains the same result as the centralized, the computational performance of the proposed method is far superior to some popular other distributed methods in terms of accuracy, computational efficiency, and scalability. [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]

The uncertain nature of renewable energy resources (RERs) and fast demand response lead to recurring voltage violations in the power systems, which causes frequent transformer tap shifting and capacitor switching. Therefore, this paper resorts to the static var compensators (SVCs) to manage the bus voltages based on the multi-agent deep reinforcement learning (MA-DRL) algorithm. The proposed scheme includes several system agents and SVC agents to collaboratively adjust the injected reactive power to restrict the bus voltages within the normal range. All the agents are trained centrally and executed separately, which requires minimum communication cost. The IEEE 14-bus system, IEEE 300-bus system, and China 157-node urban power grid are used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The penetration of photovoltaics (PVs) has been increasing in active distribution networks (ADN), which leads to severe voltage violation problems. PV inverters can provide fast and flexible reactive power support and are now allowed to participate in the voltage regulation process. This paper proposes a real-time combined central and local Volt/Var control (VVC) strategy to mitigate voltage violation problems while minimizing the network power loss. Based on the historical PV and load data, the load flow and optimal power flow are performed in the centralized controller (CC) to obtain multiple voltage and optimal power settings for each PV system. The local controller (LC) then generates voltage control curves with these optimal scatters. To improve the voltage control effect, a novel 3-Dimension voltage control curve is proposed considering both the measurements of node voltage and PV generation. Moreover, a data-driven deep convolution neural network is designed and trained to generate optimal local voltage control curves without prior knowledge of specific curve functions. The proposed approach is tested on the IEEE 33-bus distribution system and simulation results verify the effectiveness in voltage control compared with the optimal Q(V) and Q(P) method. [ABSTRACT FROM AUTHOR]

This paper provides an overview of hyperloop technologies, including a brief discussion of key components of a hyperloop system that determine the electric power requirements as a function of time. At-scale hyperloop systems do not yet exist, so a model was used to generate a set of load profiles for conceptual hyperloop realizations at four locations in the United States: two systems in California and one each in Colorado and Ohio. In all four cases, the modeled hyperloop load profiles included pulses in both active and reactive power. Grid modeling was performed to estimate the grid impacts and for discussing grid integration challenges. The paper discusses how energy storage systems might be used to eliminate the pulsating load characteristics or significantly reduce it to accommodate current grid planning guidelines. [ABSTRACT FROM AUTHOR]

This paper proposes a novel online measurement-based Wide-Area Voltage Control (WAVC) method using Phasor Measurement Unit (PMU) data in power systems with Flexible AC Transmission System (FACTS) devices. As opposed to previous WAVC methods, the proposed WAVC does not require any model knowledge or the participation of all buses and considers both active and reactive power perturbations. Specifically, the proposed WAVC method exploits the regression theorem of the Ornstein-Uhlenbeck process to estimate the sensitivity matrices through PMU data online, which are further used to design and apply the voltage regulation by updating the reference points of FACTS devices. Numerical results on the IEEE 39-Bus and IEEE 68-Bus systems demonstrate that the proposed model-free WAVC can provide effective voltage control in various network topologies, different combinations of voltage-controlled and voltage-uncontrolled buses, under measurement noise, and in case of missing PMUs. Particularly, the proposed WAVC algorithm may outperform the model-based WAVC when an undetected topology change happens. [ABSTRACT FROM AUTHOR]

In this paper five different flexibility options are analysed from a techno-economic perspective as alternatives to traditional grid expansion for a specific distribution grid in Germany. The options are: two reactive power control strategies with photovoltaic inverters (as a function of the power feed-in, or of the voltage at the connection point), one residential and two large scale battery storage applications (primary control reserve with autonomous reactive power control or self consumption maximisation strategy with autonomous reactive power control). For the pilot grid located in Southern Germany a photovoltaic expansion pathway is determined. The main goal of this work is to quantify the grid expansion actions that can be avoided by applying these five flexibility options for the assumed expansion pathway, focusing on large scale battery storages. It is shown that the five flexibility options increase the hosting capacity for PV systems, compared to a scenario without, by up to 45%. Furthermore, the results of the economic assessment indicate that the analysed flexibility options might be a viable alternative to traditional grid expansion as all of them show a cost reduction potential for the pilot region. These results could encourage DSOs to consider the integration of additional PV and battery storage systems not as a problem which triggers grid expansion, but as part of the solution reducing future grid expansion costs. [ABSTRACT FROM AUTHOR]

Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this paper proposes an ensemble learning based convex approximation for alternating current (AC) power flow equations that differs from the existing convex relaxations. The proposed approach is based on three-phase quadratic power flow equations in rectangular coordinates. To develop this data-driven convex approximation of power flows, the polynomial regression (PR) is first deployed as a basic learner to fit convex relationships between the independent and dependent variables. Then, ensemble learning algorithms such as gradient boosting (GB) and bagging are introduced to combine learners to boost model performance. Based on the learned convex approximation of power flow, optimal power flow (OPF) is formulated as a convex quadratic programming problem. The simulation results on IEEE standard cases of both balanced and unbalanced systems show that, in the context of solving OPF, the proposed data-driven convex approximation outperforms the conventional semi-definite programming (SDP) relaxation in both accuracy and computational efficiency, especially in the cases that the conventional SDP relaxation fails. [ABSTRACT FROM AUTHOR]

With the introduction of massive renewable energy sources and storage devices, the traditional process of grid operation must be improved in order to be safe, reliable, fast responsive and cost efficient, and in this regard power flow solvers are indispensable. In this paper, we introduce an Interior Point-based (IP) Multi-Period AC Optimal Power Flow (MPOPF) solver for the integration of Stationary Energy Storage Systems (SESS) and Electric Vehicles (EV). The primary methodology is based on: 1) analytic and exact calculation of partial differential equations of the Lagrangian sub-problem, and 2) exploiting the sparse structure and pattern of the coefficient matrix of Newton-Raphson approach in the IP algorithm. Extensive results of the application of proposed methods on several benchmark test systems are presented and elaborated, where the advantages and disadvantages of different existing algorithms for the solution of MPOPF, from the standpoint of computational efficiency, are brought forward. We compare the computational performance of the proposed Schur-Complement algorithm with a direct sparse LU solver. The comparison is performed for two different applicational purposes: SESS and EV. The results suggest the substantial computational performance of Schur-Complement algorithm in comparison with that of a direct LU solver when the number of storage devices and optimisation horizon increase for both cases of SESS and EV. Also, some situations where computational performance is inferior are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes some methods for the purpose of reactive power and voltage control. Real cases show them as potentially harmful for power systems, since dynamic instability and voltage collapse may appear. Control actions like tap changers, active and reactive power redispatch may help the system voltage stability, but may present reverse results for some operating conditions. This paper is firstly devoted to identify and classify an operating point under the voltage stability point of view. Following this classification, an index to assess the robustness of a bus is proposed. The studies are carried out with the help of the QV curves. Methods to change the region of operation of a bus are then discussed with the help of a real Brazilian system with all limits considered. [ABSTRACT FROM PUBLISHER]

This paper presents details of the practical implementation of a coordinated reactive power–voltage controller (CQVC) developed for a multi-machine steam power plant. The CQVC performs optimal coordination of the synchronous generators' reactive power outputs in order to maintain the total reactive power delivered by a steam power plant (SPP) or the voltage at a steam power plant HV busbar. This is required to achieve slow preventive control of generated reactive powers in order to maximize reactive power reserves along with slow high side voltage control. The CQVC is designed to act through existing automatic voltage regulator inputs, thus no modification of an existing excitation system was made. In order to increase the robustness to changes in operating conditions and to achieve the desired shape of the reactive power response, the two-step predictor corrector method is implemented. A newly developed algorithm for steady state detection ensures non-interference of reactive power voltage control with excitation system response. The paper also presents practical design solutions to overcome limitations posed by application to a real system. Acceptance and functional tests carried out during the commissioning of the CQVC are also discussed in this paper. [ABSTRACT FROM AUTHOR]