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DC-DC converters are needed for the future development of high voltage direct current (HVDC) grids, as they allow to interconnect lines with different voltages and topologies. The dc-dc converters can increase the grid controllability adding power flow control, voltage regulation and/or fault blocking capability. The dc modular multilevel converter (dc-MMC) is a non-isolated solution proposed to interconnect HVDC systems with the same line topology. This paper proposes a new dc-MMC with a control strategy, which allows the converter to interconnect different line topologies (e.g., rigid bipole connected to a symmetric monopole). The paper presents the different line topologies in HVDC installations. Then, a mathematical model with a variable transformation is proposed for the new dc-dc converter. A control structure is proposed and implemented in Matlab/Simulink using an average arm model and simplified dc grids. The results validate the control in normal operation, fault blocking capability and post-fault scenario (degraded mode). [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 presents a distributionally robust network-constrained unit commitment (DR-NCUC) model considering AC network modeling and uncertainties of demands and renewable productions. The proposed model characterizes uncertain parameters using a data-driven ambiguity set constructed by training samples. The non-convex AC power flow equations are approximated by convex quadratic and McCormick relaxations. Since the proposed min-max-min DR-NCUC problem cannot be solved directly by available solvers, a new decomposition algorithm with proof of convergence is reported in this paper. The master problem of this algorithm is solved using both primal and dual cuts, while the max-min sub-problem is solved using the primal-dual hybrid gradient method, obviating the need for using duality theory. Also, an active set strategy is proposed to enhance the tractability of the decomposition algorithm by ignoring the subset of inactive constraints. The proposed model is applied to a 6-bus test system and the IEEE 118-bus test system under different conditions. These case studies illustrate the performance of the proposed DR-NCUC model to characterize uncertainties and the superiority of the proposed decomposition algorithm over other decomposition approaches using either primal or dual cuts. [ABSTRACT FROM AUTHOR]

Power flow (PF) flexibility in the multi-terminal HVDC (MT-HVDC) grids is a thought-provoking issue. It leads to employing the active DC power flow controller (DC-PFC)s. Hence, this paper examines the static average model (AM) and power injection model (PIM) of an interline DC-PFC (IDC-PFC). It is to provide a suitable base for DC PF studies and easy embedding of the DC-PFCs into MT-HVDC grids’ PF equations. In this regard, this paper proposes a new DC PF solver (DC-PFS) for the IDC-PFC compensated MT-HVDC grids within the well-accepted Newton-Raphson (NR) framework. It requires a few modifications in the main structure of the system's Jacobin (J) matrix compared to the uncompensated MT-HVDC grid. Also, the system's admittance matrix and its symmetry are preserved. In the proposed concept, the IDC-PFC cooperates with other MT-HVDC grid's state variables to satisfy the predetermined control objective(s). Furthermore, this paper proposes a new solution procedure (SP) to handle various system's limitations during the processes of solving the DC PF problem. Meanwhile, there is no need to modify the related J matrix. The effective and accurate performance of the IDC-PFC's models, as well as presented NR-based DC-PFS and SP, are verified by performing several simulations on the 8-bus CIGRE MT-HVDC grid. [ABSTRACT FROM AUTHOR]

This paper proposes a Transient Stability Constrained Optimal Power Flow (TSCOPF) formulation that models non-synchronous renewable generation equipped with synthetic inertia. The proposed optimization problem calculates the optimal operating point of the system, accommodating high shares of non-synchronous renewable generation while ensuring transient stability in the event of critical incidents. Synthetic inertia controllers are used to improve the dynamic stability of the system in cases of very high share of renewable generation. The proposed tool is tested in the North-West Spanish system, a network with a high penetration of wind energy that causes a reduction in the total system inertia. The results of the study show that 1) synthetic inertia in renewable power plants can diminish electromechanical oscillations after a severe contingency, reducing the cost of ensuring transient stability; 2) using synthetic inertia the system becomes more stable when conventional generation is decommissioned following de-carbonization and renewable promotion policies; and 3) the proposed model can be used to calculate the parameters of the synthetic inertia control. [ABSTRACT FROM AUTHOR]

The high-precision parameters in distribution networks are difficult to obtain, which brings difficulties to the model-based methods and analysis. With the widespread deployment of high-precision measurement units, data-driven methods have greater advantages in practice. In addition, with massive integration of distributed renewable generation and fast electric vehicle chargers, the fluctuations of net load increase significantly. The data-driven power flow calculation method based on the linear model becomes difficult to obtain accurate results for the low nonlinear adaptability. To improve the data-driven power flow calculation accuracy under high penetration of renewable distribution generation, this paper proposed an approach with high adaptability to the nonlinearity of power flow. Based on the thought of Koopman operator theory, the nonlinear relationship in power flow calculation is converted into a linear mapping in a higher dimension state space, which can significantly improve the calculation accuracy. Case studies on different IEEE cases have demonstrated that the proposed method can realize higher accuracy in power flow calculation with large-scale power fluctuations, compared to the existing data-driven method, in both mesh and radial networks. Finally, measurement data of a practical 10kV distribution network has been further used to verify the effectiveness of the proposed method in practical applications. [ABSTRACT FROM AUTHOR]

In the steady-state contingency analysis, the traditional Newton-Raphson method suffers from non-convergence issues when solving post-outage power flow problems, which hinders the integrity and accuracy of security assessment. In this paper, we propose a novel robust contingency analysis approach based on holomorphic embedding (HE). The HE-based simulator provides theoretical convergence guarantee, which is desirable because it avoids the influence of numerical issues and provides a credible security assessment conclusion. In addition, based on the multi-area characteristics of real-world power systems, a partitioned HE (PHE) method is proposed with an interface-based partitioning of HE formulation. The PHE method does not undermine the numerical robustness of HE and significantly reduces the computation burden in large-scale contingency analysis. The PHE method is further enhanced by parallel or distributed computation to become parallel PHE (P2HE). Tests on a 458-bus system, a synthetic 419-bus system and a large-scale 21 447-bus system demonstrate the advantages of the proposed methods in robustness and efficiency. [ABSTRACT FROM AUTHOR]

Hybrid ac-dc grids can gain the benefits of both ac and dc grids. The Ac-Dc circuit analysis can be performed using sequential methods that decouple ac and dc systems or unified (simultaneous) methods that solve the ac and dc mismatch equations simultaneously. This paper introduces a unified ac–dc analysis via an improved model for the ac–dc coupling through which the ac and dc load flow analyses can be simultaneously conducted. The ac–dc coupling is modeled by an admittance building block, and thus, the dc grid is converted to an ac-equivalent circuit within the hybrid network. However, unlike past literature, state variables beyond nodal voltages and angles are avoided, leading to a simpler algorithm, and reactive power injection of the coupling mechanism, a requirement for the IEEE 1547 Std, is explicitly modeled. Furthermore, the proposed model can be applied to both voltage-source and line-commuted converters. Accordingly, the conventional ac power flow algorithms can be applied to the hybrid circuit paving the path for seamless adoption of hybrid circuits and significantly saving time and effort in programming, troubleshooting, and upgrading techniques currently used in research and industry as well as a high-level analysis tool regarding the hybrid ac-dc grid is achieved. [ABSTRACT FROM AUTHOR]

Isothermal natural gas flow model with constant gas temperature has been widely used in conventional coordinated operations of integrated electricity and natural gas systems (IEGS). However, as a crucial state variable in IEGS, gas temperature varies significantly among nodes in a natural gas system, which can be calculated along with nodal pressures and mass flow rates. This paper proposes a novel non-isothermal optimal power and gas flow (OPGF) model that avoids the isothermal assumptions involved in traditional natural gas network model and improves the accuracy significantly. In the proposed model, partial differential terms with minimal weights are neglected based on the quantitative analysis of the energy conservation equation to further simplify the energy conservation equation. A non-isothermal model of natural gas networks is developed by introducing the finite difference method and laws of thermodynamics to incorporate the gas temperature change into the coordinated operation of IEGS. A start point initialization scheme is developed based on the Newton-Raphson algorithm to accelerate the interior point method solution convergence and improve its solution quality. Numerical experiments presented for two test systems validate the effectiveness of the proposed OPGF model and solution methodology. [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]

Electric power grids regularly experience uncertain fluctuations from load demands and renewables, which poses a risk of violating operational limits designed to safeguard the system. In this paper, we consider the robust AC OPF problem that minimizes the generation cost while requiring a certain level of system security in the presence of uncertainty. The robust AC OPF problem requires that the system satisfy operational limits for all uncertainty realizations within a specified uncertainty set. Guaranteeing robustness is particularly challenging due to the non-convex, nonlinear AC power flow equations, which may not always have a solution. In this work, we extend a previously developed convex restriction to a robust convex restriction, which is a convex inner approximation of the non-convex feasible region of the AC OPF problem that accounts for uncertainty in the power injections. We then use the robust convex restriction in an algorithm that obtains robust solutions to AC OPF problems by solving a sequence of convex optimization problems. We demonstrate our algorithm and its ability to control robustness versus operating cost trade-offs using PGLib test cases. [ABSTRACT FROM AUTHOR]

Distributed Series Reactances are devices that dynamically increase the impedance of a line to reduce the power flow it carries. This work explores whether widely deploying these devices enhances a power system's robustness against line overload cascading failures. The presence of Distributed Series Reactances may make it less likely that equipped lines would become overloaded by contingencies elsewhere, and so their presence may arrest the propagation of line overloads through a system. However, the efficacy of these devices in this role has not been widely investigated. Likewise, there are few extant methodologies for siting dynamic reactances within the grid to mitigate the propagation of cascades. In this paper, the ability of these devices to arrest the propagation of cascading failures within power grids is investigated. First, a novel dc power flow is formulated, which models dynamic line impedances. A novel methodology is proposed for siting the devices on lines spread throughout the network. With these innovations in hand, the devices’ effects on cascade propagation are simulated using a sizeable database consisting of multiple load & generation snapshots across eight test networks. No major beneficial effect is found, even when 25% of lines are equipped. [ABSTRACT FROM AUTHOR]

Energy feedback systems (EFSs) have been widely applied in urban rail transit, and a power flow algorithm and energy-saving evaluation of urban rail power supply systems with EFSs are studied in this paper. First, trains, the reflux system, and traction substations with EFSs are modeled, and the multimode transitions are analyzed, including the maximum power state of the EFS. Then, a modified AC/DC unified power flow algorithm for the DC power supply system, which simplified the DC reflux system is proposed, and a field case study based on a multiple train scenario is presented to validate the algorithm. Furthermore, system-level energy-saving evaluation indexes are applied according to system power flow analysis. When the headway time decreases, the proposed indexes decrease in general mainly as there is more regenerative braking energy absorbed by adjacent trains. The higher the load rates of the step-down substations are, the more daily feedback energy is utilized. When the start voltage of the EFS ranges from 1650 V to 1770 V, the maximum energy-saving rate reaches 11.9%, which occurs when the start voltage is 1670 V. When the no-load voltage is relatively high, the start voltage should not be higher than 1750 V to keep the system running in high efficiency. These results can provide advice for the design and operation of traction power supply systems with EFSs. [ABSTRACT FROM AUTHOR]

Topology identification and parameter estimation form the basis for the operation and control of the distribution network with little or no observability. This paper proposes a method to estimate the admittance matrix for open-loop distribution networks based only on active/reactive power injection and voltage magnitude data. We derive the linear relationship between the admittance matrix and the measurements based on decoupled linear power flow (DLPF) equations. A total least squares regression method is proposed based on analysis of the characteristics of the open-loop grid admittance matrix. Case studies on the IEEE 33-bus system demonstrate the proposed method's effectiveness, accuracy, and efficiency. [ABSTRACT FROM AUTHOR]

Transmission line failure in power systems prop-agate non-locally, making the control of the resulting outages extremely difficult. In Part II of this paper, we continue the study of line failure localizability in transmission networks and characterize the impact of cut set outages. We establish a Simple Path Criterion, showing that the propagation pattern due to bridge outages, a special case of cut set failures, are fully determined by the positions in the network of the buses that participate in load balancing. We then extend our results to general cut set outages. In contrast to non-cut outages discussed in Part I whose subsequent line failures are contained within the original blocks, cut set outages typically impact the whole network, affecting the power flows on all remaining lines. We corroborate our analytical results in both parts using the IEEE 118-bus test system, in which the failure propagation patterns exhibit a clear block-diagonal structure predicted by our theory, even when using full AC power flow equations. [ABSTRACT FROM AUTHOR]

Large blackouts in power grids are often the consequence of uncontrolled failure cascades. The ability to predict the failure cascade process in an efficient and accurate manner is important for power system contingency analysis. In this paper, we propose to apply the influence model for the prediction and screening of failure cascades in large scale DC and AC power networks. Then, the trained influence model is applied to some large power grids with thousands of buses and transmission lines. The prediction performance is evaluated in four different aspects, from the global perspective of the overall failure size to the individual information regarding the link failure time. The results show that under limited training samples, the proposed framework is capable of predicting the failure cascade size with a 7% error rate, the final state of links with a 10% error rate, and the failure time within 1 time unit for both the DC and AC model. One major advantage of the proposed method is that it can reduce the computational time of the failure cascade prediction by a few orders of magnitude with limited compromise in accuracy, as compared to the power flow based contingency analysis. Another important feature of the proposed method is that the trained influence parameters can reveal the critical initial contingencies. This information is very helpful for identifying the worst contingency scenarios for system operators. [ABSTRACT FROM AUTHOR]

The nonlinear programming (NLP) problem to solve distribution-level optimal power flow (D-OPF) poses convergence issues and does not scale well for unbalanced distribution systems. The existing scalable D-OPF algorithms either use approximations that are not valid for an unbalanced power distribution system, or apply relaxation techniques to the nonlinear power flow equations that do not guarantee a feasible power flow solution. In this paper, we propose scalable D-OPF algorithms that simultaneously achieve optimal and feasible solutions by solving multiple iterations of approximate, or relaxed, D-OPF subproblems of low complexity. The first algorithm is based on a successive linear approximation of the nonlinear power flow equations around the current operating point, where the D-OPF solution is obtained by solving multiple iterations of a linear programming (LP) problem. The second algorithm is based on the relaxation of the nonlinear power flow equations as conic constraints together with directional constraints, which achieves optimal and feasible solutions over multiple iterations of a second-order cone programming (SOCP) problem. It is demonstrated that the proposed algorithms are able to reach an optimal and feasible solution while significantly reducing the computation time as compared to an equivalent NLP D-OPF model for the same distribution system. [ABSTRACT FROM AUTHOR]

Linearization of power flow is an important topic in power system analysis. The computational burden can be greatly reduced under the linear power flow (LPF) model while the model error is the main concern. Therefore, various linear power flow models have been proposed in literature and dedicated to seek better linear models. Many linear power flow models are based on some kind of transformation/simplification/Taylor expansion of AC power flow equations. In this paper, numerical performance and theoretical explanation of the data-based linear power flow model are investigated. The direct least-squares method with complete orthogonal decomposition is designed for addressing collinear data and big data. The resulted linear power flow model is named as least-squares distribution factors (LSDF) and its performance is investigated in cold-start applications. It is found that LSDF is in fact an approximation of the optimal LPF with minimum mean square error. It is also proved that the LSDF can give an accurate estimation of total system losses. Comprehensive numerical testing show that the LSDF can work very well for system with large load variations. The average error of LSDF is only about 1% of the average error of power transfer distribution factor (PTDF) in numerical testing. [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]

In order to effectively suppress surplus torque, realizing high precision loading, this paper applies proportional resonant (PR) control to the load torque control of electric load simulator (ELS), and analyzes and optimizes the stability and dynamic performance of ELS. The mathematical model of ELS is built in z-domain first in this paper, to establish foundation for designing and analyzing PR controller. The stability of the ELS with PR controller is analyzed through Nyquist diagrams, and optimized by reasonably designing the phase compensation angle of PR controller. The dynamic performance is analyzed through pole–zero plots, and the resonant gain of PR controller is designed based on the pole–zero plots to optimize the dynamic performance. Experimental results on ELS are provided, and the proposed method is compared with other typical methods, validating the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper presents a fundamental study of voltage collapses that occur on a post-fault trajectory of a stressed power system in seconds after large disturbances. The focus of the study are voltage collapses that are induced by certain load models. Using an n-machine-N-bus power system model, the paper explicitly shows that the voltage collapse is caused by the non-existence of a real, positive solution for a load voltage magnitude in different areas of a relative rotor angle space when the load is of non-linear type. These “areas without voltage solution” are denoted as Voltage Impasse Regions (VIR) and are mathematically characterized as trigonometric functions of (n -1) relative rotor angles. Once the post-fault trajectory enters a VIR, voltage magnitude solutions become complex or negative, the algebraic Jacobian becomes singular, and the behaviour of a system becomes undefined. The case study has been carried out using a simple 3-machine-1-load system with static load models. In the study, VIR appeared and enlarged as the non-linear (constant power and constant current) load increased. Furthermore, the non-convergence of time-domain solution occurred exactly at VIR, thereby confirming that the problem is of structural nature. [ABSTRACT FROM PUBLISHER]

For nearly 20 years, the Test Feeder Working Group of the Distribution System Analysis Subcommittee has been developing openly available distribution test feeders for use by researchers. The purpose of these test feeders is to provide models of distribution systems that reflect the wide diversity in design and their various analytic challenges. Because of their utility and accessibility, the test feeders have been used for a wide range of research, some of which has been outside the original scope of intended uses. This paper provides an overview of the existing distribution feeder models and clarifies the specific analytic challenges that they were originally designed to examine. Additionally, this paper will provide guidance on which feeders are best suited for various types of analysis. The purpose of this paper is to provide the original intent of the Working Group and to provide the information necessary so that researchers may make an informed decision on which of the test feeders are most appropriate for their work. [ABSTRACT FROM PUBLISHER]

Following the vision of future Supergrids, the existing power systems are expected to evolve into AC/DC systems containing voltage source converters with multiterminal configurations. This paper presents a new sequential power flow algorithm for such power systems. The algorithm can be applied to systems with multiple AC and DC grids of any grid topology. Because of its pure AC/DC network decomposition, the simplification of elements within the converter stations is not required, as is the case with other proposals in the literature. The paper also addresses the convergence properties of the proposed algorithm. A convergence factor has been designed that allows controlling the exit criterion within each inner loop of the sequential AC/DC load flow problem. It is shown that by modulating the convergence factor, the number of inner loop iterations needed to achieve a solution can be diminished. [ABSTRACT FROM AUTHOR]

Two key problems in meshed high-voltage direct current (HVDC) transmission grids are managing line power flows and protection against dc faults. Current flow controllers (CFCs) will be required to balance cable currents in meshed dc grids, in order to prevent individual line power capacity limits restricting overall power flow in the grid. Direct current circuit breakers (DCCBs) will be also required to protect HVDC grids from dc faults. This paper demonstrates that the current flow controller functionality can be added into a hybrid CB's design. This paper proposes integrating an interline CFC into the load commutation switch (LCS) of a hybrid DCCB. The integrated design LCS/CFC is analyzed and a state-space model is derived. The control of the CFC is designed and the performance of the LCS/CFC during normal operation is verified by means of MATLAB Simulink and PSCAD simulations. A comparison of the integrated LCS/CFC and the separate design is given. The case studies show a reduction in total power losses, and improved protection operation times can be achieved. [ABSTRACT FROM PUBLISHER]

This paper presents a new hybrid passive power device, denoted as the hybrid transformer, which is an improved alternative to the classical two-winding high-frequency transformer (100's kHz–MHz). The hybrid transformer is comprised of a coupled inductor topology, that provides load–source matching, denoted as the mutual branch topology, and a dielectric isolation device denoted as the multilayer capacitive isolation device. The main focus of this paper is on the design and operation of the mutual branch topology. Simulation results are shown to highlight the improved efficiency of the hybrid transformer over a conventional high-frequency transformer. Finally, the efficiency of the hybrid transformer is compared with that of a classical two-winding transformer using the same resonant converter, highlighting the improved efficiency of the hybrid transformer (up to 10% improved efficiency for light loads). [ABSTRACT FROM AUTHOR]

The more electric aircraft concept aims at increasing the amount and the power of the electrical subsystems on the next generation of aircraft. One of the major challenges in this framework is that the electric power is generated by means of electrical generators connected to the jet turbine shaft. In order to satisfy the peak power demand and overload conditions, the generators are oversized, increasing weight and total cost of operation. Possible solutions to this problem is to decrease the size of the generator and to provide the peak power with storage systems. As an alternative, load disconnection during peak demand (load-shedding) can be enforced with solid-state switches. This paper presents a different approach, i.e., by modifying the dc voltage of the distribution, the load can be controlled. In order to achieve this objective, a precise on-line identification algorithm is proposed. Theoretical analysis is performed, and simulation results on a study-case distribution system are reported, highlighting how the proposed load identification and control method effectively manages a power curtailment condition without load-shedding or storage systems. Power hardware in the loop simulations on a dc microgrid with a multiport power converter confirm the simulation analysis. [ABSTRACT FROM AUTHOR]

This paper introduces a new technique to characterize the ac grids stability connected to multiterminal high-voltage direct current networks. The proposed method identifies the maximum active powers that converters can exchange with an ac network without losing the transient stability using trajectory sensitivity analysis. Therefore, the generators' rotor angles variations due to various converters active powers exchange are measured and normalized. Consequently, the norm of each trajectory vector is used as an indicator of the system proximity to instability. To enhance the accuracy of the method for online stability assessment applications, the steady-state initial conditions of the sensitivity network variables are precisely obtained using the Newton shooting method. For this purpose, the detailed differential and algebraic models representing the dynamics of the ac and dc networks have been formulated and analytically solved simultaneously with the sensitivity network. Comprehensive simulation studies on the IEEE 68-bus benchmark system are carried out using PSCAD/EMTDC for validation purposes. Results show that the modified approach provides more accurate results compared to the normal trajectory sensitivity analysis with less time compared to multiple time-domain simulations. [ABSTRACT FROM PUBLISHER]

This two-part paper considers the coordination of a population of thermostatically controlled loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak energy constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data and price data, and is compared with other approaches in terms of aggregated load response. Simulation results indicate that our coordination framework can effectively improve the operational efficiency of the distribution system and reduce power congestion at key times. [ABSTRACT FROM AUTHOR]

This paper deals with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers. The indices are developed in a way consistent with a mixed-integer linear programming (MILP) approach. A key contribution of the paper is the efficient implementation of the \mmb\varepsilon-constraint method using lexicographic optimization in order to solve the multi-objective optimization problem. After the Pareto efficient solution set is generated, the resulting configurations are evaluated using a backward/forward sweep load-flow algorithm to verify that the solutions obtained are both non-dominated and feasible. Since the \mmb\varepsilon-constraint method generates the Pareto front but does not incorporate decision maker (DM) preferences, a multi-attribute decision making procedure, namely, the technique for order preference by similarity to ideal solution (TOPSIS) method, is used in order to rank the obtained solutions according to the DM preferences, facilitating the final selection. The applicability of the proposed method is assessed on a classical test system and on a practical distribution system. [ABSTRACT FROM AUTHOR]

Load modeling is essential for designing and operating power systems. This paper presents an approach for load modeling on smaller power systems that could be “islanded,” an approach that preserves the detail of a full differential equation simulation of relevant loads while requiring far less computation by employing behavioral models of important loads. Mixed domain models, e.g., stochastic, finite-state machine, and differential equation models, are employed to provide accuracy in a computationally tractable framework. Where simple load models may not be adequate, particularly for generation-constrained systems (in a paper by Sotiropoulos ), and full models are computationally unfavorable, this approach provides excellent results that enable “what-if” studies and flexible re-evaluation during power system design and operational assessment. Naval vessels, particularly warships with relatively large and increasing load power requirements, offer a unique laboratory for understanding isolated power grids. This paper examines the DDG-51 power distribution system as an example. [ABSTRACT FROM PUBLISHER]

Industrial microgrids functioning under islanded mode of operation are often subjected to large and fluctuating demands from loads such as crushers, excavators, and steel rolling mills. This paper studies the supercapacitor (SC) cycle life when multiple small rated but distantly located distributed energy resources are supplying a cement plant crusher-conveyor load in the islanded operation of the microgrid. Each DER consists of a fuel cell (FC) supplemented with a SC. After having carried out extensive modeling, simulation, and analysis, this paper demonstrates that the SC cycle life can be equalized by employing the cooperative framework of flexible distribution of energy and storage resources. [ABSTRACT FROM AUTHOR]

Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 p.u. voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology. [ABSTRACT FROM PUBLISHER]

This paper addresses how to improve the computational efficiency and estimation reliability in cascading outage analysis. Under mild assumptions, we first formulate a cascading outage as a Markov model with specific state space and transition probability by leveraging the Markov property of cascading outages. Such a model provides a rigorous formulation that allows analytic investigation on cascading outages in the framework of standard mathematical statistics. Then, we derive a sequential importance sampling (SIS)-based strategy for cascading outage simulations and blackout risk analysis with solid theoretical foundation. Numerical experiments manifest that the proposed SIS strategy can significantly enhance the efficiency of simulations and reduce the estimation variance of blackout probability/risk compared with the traditional Monte Carlo simulation strategy. [ABSTRACT FROM PUBLISHER]

This paper proposes a unified load flow (LF) model for AC–DC hybrid distribution systems (DSs). The proposed model can be applied in hybrid DSs with mixed configurations for AC/DC buses and AC/DC lines. A new classification of DS buses is also introduced for LF analysis. A set of generic LF equations has been derived based on comprehensive analysis of the possible AC–DC hybrid system configurations. Three binary matrices, which are used as a means of describing the configuration of the AC and DC buses and lines, have been employed in the construction of the unified power equations. These matrices enable a single configuration at a time to be activated in the power equations. The proposed LF model is generic and can be used for both grid-connected and isolated hybrid DSs. The new model has been tested using several case studies of hybrid DSs that include different operational modes for the AC and DC distributed generators. As a means of evaluating the effectiveness and accuracy of the proposed model, the LF solution was compared to the solution produced by PSCAD/EMTDC. A comparison of the results reveals the efficacy of the proposed model. [ABSTRACT FROM AUTHOR]

A crude oil production and shipping terminal was built and expanded over time such that the facility was powered by three isolated power systems. These separate plants have since been interconnected to permit the sharing of generation reserves. Initially, the interconnected system was supervised by a power management system (PMS) that relied on isochronous operation of one power plant for frequency control. The PMS attempted to implement system wide load sharing by issuing raise and lower speed and voltage signals to the second power plant, which was operated in droop control. Due to a variety of factors, this control proved unsatisfactory. The control strategy was revised to operate all generators in droop mode and to handle management of frequency, voltage, and power flows between plants at the secondary control level. This paper describes why the initial PMS was unsatisfactory, why it was abandoned, and how it was modified to enable the successful interconnection of all three power plants into a single network. [ABSTRACT FROM AUTHOR]

The optimized operation of a building energy management system (BEMS) is of great significance to its operation security, economy, and efficiency. This paper proposes a day-ahead multiobjective optimization model for the BEMS under time-of-use price-based demand response (DR), which integrates building integrated photovoltaic with other generations to optimize the economy and occupants’ comfort by the synergetic dispatch of source–load–storage. The occupants' comfort contains three aspects of the indoor environment: visual comfort; thermal comfort; and indoor air quality comfort. With the consideration of controllable load that could participate in DR programs, the balances among different energy styles, electric, thermal, and cooling loads are guaranteed during the optimized operation. YALMIP toolbox in MATLAB was applied to solve the optimization problem. Finally, a case study was conducted to validate the effectiveness and adaptability of the proposed model. [ABSTRACT FROM AUTHOR]

Power electronic systems are prone to instability. The problem, generally attributed to the constant power load (CPL) behavior of their power electronic controlled loads, can become more acute when the systems are subject to parametric uncertainties. The structured singular value (SSV) based $\mu$ method has proven to be a reliable approach for assessing the stability robustness of such uncertain systems. Despite its numerous benefits, the $\mu$ method is not often applied to electrical power systems (EPS) with multiple uncertainties. This may be due to the mathematical complexity underlying the $\mu$ theory. This paper aims to make the $\mu$ approach more application-friendly by providing clearer insights into the meaning and usefulness of the robust stability measure $\mu$ for EPS with multiple parametric uncertainties. This is achieved by presenting a methodology for translating $\mu$ analysis results from the frequency domain to the more perceivable uncertain parameters domain. The method directly demonstrates dependences of system stability on uncertain system parameters. Further, it clearly identifies robust stability domains as subsets of the much wider stability domains. The work is based on a representative EPS connected to an ideal CPL. $\mu$ analysis predictions are evaluated and validated against analytical results, for example, CPL system. [ABSTRACT FROM PUBLISHER]

This paper describes a technique to model a vector-controlled induction motor drive in large-scale phasor-level dynamic simulation programs. The performance-based load model is implemented by obtaining the linearized power-voltage and power-frequency transfer functions from test data or from detailed electro-magnetic transient simulation used as a surrogate for test data. Voltage and frequency modulations are performed to obtain the amplitude and phase responses of the detailed vector-controlled drive model for a range of discrete frequencies. The prediction error minimization technique is utilized to generate best-fit analytical transfer function expressions. The electrical interface of the performance-based drive load model is developed to interact with the external system in positive-sequence dynamic simulation programs. The drive model is used to investigate the relative damping effects of drive-connected and direct-connected motors on system voltage and frequency oscillations. [ABSTRACT FROM PUBLISHER]

In this paper, we present a Fingerprint Linear Estimation Routine to identify topology changes in power networks using readings from sparsely deployed phasor measurement units (PMUs). When a power line, load, or generator trips in a network, or when a substation is reconfigured, the event leaves a unique “voltage fingerprint” of bus voltage changes that we can identify using only the portion of the network directly observed by the PMUs. The naive brute-force approach to identify a failed line from such voltage fingerprints, though simple and accurate, is slow. We derive an approximate algorithm based on a local linearization and a novel filtering approach that is faster and only slightly less accurate. We present experimental results by using the IEEE 57-bus, IEEE 118-bus, and Polish 1999-2000 winter peak networks. [ABSTRACT FROM PUBLISHER]

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers. [ABSTRACT FROM PUBLISHER]

Inverters and loads can freely connect to any node in a meshed parallel inverters system, leading to variations of line impedance between two nodes and the structure of the electric network. More challenges exist for proportional load-sharing control in such a system. An improved proportional load-sharing strategy for a meshed parallel inverters system with complex impedances is proposed in this paper. The RL-type droop method is modified through injecting the power droop information of all other inverters, which can improve the load-sharing accuracy to some extent and completely compensate the voltage amplitude and frequency deviations caused by droop equations under accurate load-sharing conditions. Besides, an adaptive virtual resistance tuned by the integral of the linear combination of output active and reactive powers, is added to eliminate load-sharing errors. In addition, the central controller broadcasts the control variables to all inverters. This improves the simultaneity of control data and minimizes the mismatch of control delay. Three modified droop methods are compared with the small-signal analysis and simulation. Experimental results are presented to investigate the performance of the proposed control strategy. [ABSTRACT FROM PUBLISHER]

An increasing number of power-electronic-based distributed generation systems and loads generate not only characteristic harmonics but also unexpected harmonics. Several methods, such as impedance-based analysis, which are derived from the conventional average model, are introduced to perform research about the harmonic interaction. However, it is found that the linear-time-invariant-based model analysis makes it difficult to analyze these phenomena because of the time-varying properties of the power-electronic-based systems. This paper investigates a grid-connected converter by using the harmonic state-space (HSS) small-signal model, which is based on a linear time-varying periodically theory. The proposed model can include the switching behavior of the model, where it makes the model possible to analyze how harmonics are transferred into both the ac-side and dc-side circuits. Furthermore, a harmonic matrix of the grid-connected converter is developed to analyze the harmonic interaction at the steady-state behavior. Besides, the frequency-domain results are compared with time-domain simulation results by using the HSS modeling to verify the theoretical analysis. Experimental results are finally discussed to verify the proposed model and study. [ABSTRACT FROM PUBLISHER]

Plug-in electric vehicle (PEV) charging equipment incorporates protection that ensures that grid disturbances do not damage the charger or vehicle. When the grid voltage sags below 80% of nominal, undervoltage protection is likely to disconnect the charging load from the grid. Most PEV charging will occur overnight, when non-PEV load is at a minimum. This paper argues that PEV voltage-sag response, when synchronized across large numbers of PEVs, could result in the loss of a significant proportion of the total load. It is shown that this load loss can lead to unacceptably high voltages once the initiating event has been cleared. This paper explores the nature of this voltage-rise phenomenon. Analysis tools are developed to assist in determining PEV loading conditions that demarcate acceptable postdisturbance voltage response from unacceptable outcomes. Two examples, based on standard distribution test systems, are used to illustrate PEV-induced overvoltage behavior, and demonstrate applications of the analysis tools. [ABSTRACT FROM AUTHOR]

This paper presents an on-line technique for achieving fuel-energy efficiency while meeting the electrical demands of a stationary combat vehicle. A vehicle's electrical load depends on the requirements of a combat mission. To achieve higher efficiency, a vehicle can use any existing advanced energy management systems and techniques (hardware/software), but they require complex, costly, and time-consuming implementations. The authors propose an approach in this paper to achieve energy efficiency in a stationary combat vehicle by operating the engine at a fuel-efficient speed to meet the vehicle load demand. The method accomplishes the aim by combining engine and alternator efficiency data, mission awareness, and a fuzzy logic soft computing methodology. The simulation uses a computerized vehicle software model and a test bench to validate the approach. In comparison to vehicles with high-idle RPM technology, the simulation results of the new approach show a 15.7% efficiency improvement for combat mission scenarios. The future implementation of this approach on a real vehicle will test the performance of the technique using a fuzzy electronic chip. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed control approach to coordinate multiple energy storage units (ESUs) to avoid violation of voltage and thermal constraints, which are some of the main power quality challenges for future distribution networks. ESUs usually are connected to a network through voltage source converters. In this paper, both ESU converters active and reactive power are used to deal with the above mentioned power quality issues. ESUs' reactive power is proposed to be used for voltage support, while the active power is to be utilized in managing network loading. Two typical distribution networks are used to apply the proposed method, and the simulated results are illustrated in this paper to show the effectiveness of this approach. [ABSTRACT FROM PUBLISHER]

The large-scale power systems are liable to performance deterioration due to the presence of sudden small load perturbations, parameter uncertainties, structural variations, etc. Due to this, modern control aspects are extremely important in load frequency control (LFC) design of power systems. In this paper, the LFC problem is illustrated as a typical disturbance rejection as well as large-scale system control problem. For this purpose, simple approach to LFC design for the power systems having parameter uncertainty and load disturbance is proposed. The approach is based on two-degree-of-freedom, internal model control (IMC) scheme, which unifies the concept of model-order reduction like Routh and Padé approximations, and modified IMC filter design, recently developed by Liu and Gao refid="ref24"/ . The beauty of this paper is that in place of taking the full-order system for internal-model of IMC, a lower-order, i.e., second-order reduced system model, has been considered. This scheme achieves improved closed-loop system performance to counteract load disturbances. The proposed approach is simulated in MATLAB environment for a single-area power system consisting of single generating unit with a non-reheated turbine to highlight the efficiency and efficacy in terms of robustness and optimality. [ABSTRACT FROM PUBLISHER]