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Market and network integration of distributed energy resources can be facilitated by their coordination within a virtual power plant (VPP). However, VPP operation subject to network limits and different market and physical uncertainties is a challenging task. This paper introduces a framework that co-optimizes the VPP provision of multiple market (e.g., energy, reserve), system (e.g., fast frequency response, inertia, upstream reactive power), and local network (e.g., voltage support) services with the aim of maximizing its revenue. To ensure problem tractability, while accommodating the uncertain nature of market prices, local demand, and renewable output and while operating within local network constraints, the framework is broken down into three sequentially coordinated optimization problems. Specifically, a scenario-based robust optimization for day-ahead resource scheduling, with linearized power flows, and two receding horizon optimizations for close-to-real-time dispatch, with a more accurate second-order cone relaxation of the power flows. The results from a real Australian case study demonstrate how the framework enables effective deployment of VPP flexibility to maximize its multi-service value stack, within an uncertain operating environment, and within technical limits. [ABSTRACT FROM AUTHOR]

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with a local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. Besides, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems. [ABSTRACT FROM AUTHOR]

This paper presents a novel model of voltage source converter (VSC) based energy routers (ERs) in microgrids. The proposed model explicitly describes the circuit laws within the ERs and captures the coupling of control variables among the AC/DC, DC/DC, DC/AC links. Therefore, the proposed model possesses unparalleled control capabilities in the operational parameters of both the AC and DC sides of ERs. By incorporating such a model into the AC-DC optimal power flow formulation, we not only optimize the power flows between the AC and DC sides of ERs, but also strategically schedule the flexible resources. To solve the ERs based AC-DC optimal power flow (ER-OPF) in a distributed fashion, we propose a hierarchical distributed optimization method that decouples the power grids into a master region and several sub-regions. In the master region, we propose a sequence of strong relaxations to transform the problem into a semidefinite program (SDP). We further show that this SDP relaxation is exact. For the sub-regions, we utilize sequential quadratic programming (SQP) to solve multiple small-scale subproblems with non-convex constraints in parallel. Case studies on the IEEE benchmark system show that fuel costs and power losses are reduced dramatically by utilizing ERs in microgrids. In addition, the proposed distributed algorithm can converge faster than alternating direction method of multipliers (ADMM). [ABSTRACT FROM AUTHOR]

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

With the large-scale integration of distributed generators (DGs), the coupling relations between transmission network (TN) and distribution networks (DNs) are getting closer. Coordinating the black-start processes of TN and DNs is beneficial to improving restoration efficiency. Therefore, a distributed black-start optimization method for global transmission and distribution (T&D) network is proposed in this paper. Firstly, a black-start optimization model of global T&D network is established to minimize the outage costs. Then, it is decomposed into the TN black-start optimization sub-problem and several DN black-start optimization sub-problems based on the analytical target cascading (ATC). The mixed integer quadratic programming (MIQP) is used for sub-problem modeling. The models take into account the restoration operations of different grid components at each black-start time step. The transmission control center (TCC) and distribution control centers (DCCs) only need to exchange partial information including the boundary power at each time step for distributed coordination, to obtain the coordinated black-start scheme for T&D network. Finally, the effectiveness of the proposed model and method is validated using a global T&D network case. [ABSTRACT FROM AUTHOR]

Non-negligible amounts of Distributed Generating Units (DGUs) are already connected to power systems, predominantly to medium- and low-voltage networks. The interaction between distribution and transmission systems is gaining the attention of system operators. Given the high controlability of DGUs, the active distribution networks can potentially support the transmission system during emergency situations. Previously proposed voltage emergency controls involving distribution network assets focused on preserving the transmission system integrity, even if it implies affecting the distribution system operation (intrusive schemes). More attention needs to be devoted to supporting transmission voltages, while preserving the distribution network operation (non-intrusive schemes). This paper introduces a new adaptive and non-intrusive voltage emergency control scheme based on the synchronization of DGUs and the load tap changer of the corresponding distribution transformer. The conclusions are derived from time-domain simulations using an extended version of the IEEE Nordic test system for voltage stability assessment. [ABSTRACT FROM AUTHOR]

This paper presents a passivity-based control (PBC) for a type 2 static synchronous compensator (STATCOM) based on an Euler-Lagrange model. The proposed method is designed based on a Lyapunov function by considering dissipation to improve transient performance. An additional nonlinear damping term is designed to regulate the capacitor voltage. It is guaranteed that the equilibrium point of the system is locally exponentially stable in the operating range. The performance of the proposed method is validated via a 100 Mvar STATCOM system connected to the 345-kV grid system in SimPowerSystems, MATLAB/Siumlink. To compare with the input-output feedback linearization method, the proposed control method has improved convergence and reduction of oscillations of the active current and DC voltage, as shown in simulation results. Lastly, it shows that the proposed method is robust to model mismatches as the variation of the grid voltage and the degradation of the capacitance. [ABSTRACT FROM PUBLISHER]

Prediction and shaping of dynamic response of the demand will enable advanced control algorithms for active demand management as well as improved stability assessment of the power system. Based on previously developed demand disaggregation approach, this paper develops a methodology for day-ahead prediction and shaping of dynamic response of the demand at bulk supply points without having to perform field measurements. The methodology is broadly based on application of artificial neural network and Monte Carlo simulations and incorporates multiple approaches namely, load forecasting, load disaggregation and the component-based load modelling approach. The input data include standard rms measurements at bulk supply points and actual and day-ahead forecasted weather data and does not rely on having access to detailed customer surveys or high-resolution load signatures. Measured dynamic responses of the demand from the substations of the local utility are used for validation. Load shifting and shaping of dynamic response of the demand are also illustrated. [ABSTRACT FROM PUBLISHER]

This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual \epsilon-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules for cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time. [ABSTRACT FROM PUBLISHER]

Many blackouts in electric power grids throughout the world are caused by cascading outages, which often involve complex processes in various timescales. The multi-timescale nature of cascading outages makes conventional quasi-static simulation methods inaccurate in characterizing actual evolution of outages. This paper proposes a multi-timescale cascading outage model using a quasi-dynamic simulation method. The model establishes a framework for simulating interactions among dynamics in quite different timescales. It realizes simulation of cascading outages with representation of time evolution, so it overcomes ambiguity of time in conventional cascading outage models and hence has better practicality. Moreover, the model considers dynamics, e.g., load variation and generator excitation protection which affect voltage and reactive power profiles. Also, an improved re-dispatch model based on sensitivity is proposed. These improvements facilitate better simulation for a realistic power system. Also, dynamic simulation can be flexibly incorporated into the simulation of short-term processes in this model as needed. Case studies with the proposed multi-timescale model on the IEEE 30-bus system discuss the role of generator protection in cascading outage evolution, and analyze stage characteristics in outages. The multi-timescale model is also demonstrated on a reduced 410-bus US-Canada northeast power grid. Moreover, impacts from dispatchers' involvements are analyzed. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a method to optimally set the reactive power contributions of distributed energy resources (DERs) present in distribution systems with the goal of regulating bus voltages. For the case when the network is balanced, we use the branch power flow modeling approach for radial power systems to formulate an optimal power flow (OPF) problem. Then, we leverage properties of the system operating conditions to relax certain nonlinear terms of this OPF, which results in a convex quadratic program (QP). To efficiently solve this QP, we propose a distributed algorithm based on the Alternating Direction Method of Multipliers (ADMM). Furthermore, we include the unbalanced three-phase formulation to extend the ideas introduced for the balanced network case. We present several case studies to demonstrate the method in unbalanced three-phase distribution systems. [ABSTRACT FROM PUBLISHER]

The total supply capability (TSC) is an important index for assessing the reliability of a distribution power system. In this paper, two models to evaluate the TSC are established. In the first, the TSC is acquired with the conditions that all load outages can be restored via network reconfiguration with transformers' N-1 contingencies, i.e., that all constraints related to branch thermal ratings and bus-voltage limits can be satisfied following restoration for each N-1 contingency. The second model, which is revision of the first, considers the daily load curves for different classes of customers, e.g., residential, commercial and industrial. Both models can be formulated as mixed integer problems with second-order cone programming (MISOCP), which can be solved using commercially available optimization software. Two test systems are used to demonstrate the applicability of the presented models. Numerical results show that the presented model is more accurate than the previously published models. This proposed analytical approach can be applied in a range of network planning studies, e.g., for selecting appropriate ratings of transformers, or for optimal locating of circuit breakers and distributed energy resources. [ABSTRACT FROM AUTHOR]

This paper presents a framework for the coordination of distributed energy resources (DERs) and demand response (DR) for voltage and frequency support of islanded microgrids. The proposed method basically relies on extracting information from real and reactive power sensitivities at different buses for minimizing the voltage and frequency deviations of the islanded microgrid. To this aim, a new power flow procedure is adopted in which the frequency deviation appears as an additional state variable. This helps to calculate the required setpoints for the DERs as well as the amount of the demanded power curtailed through the controllable loads to meet the overall goal. The loads are classified based on their a-priori known controllability degree. To minimize the manipulated load, the most effective buses are selected based on their associated sensitivity values. In the grid-connected mode, the total operation cost is minimized, while the microgrid bus voltages are maintained within the pre-specified acceptable range. In both modes, the whole process is formulated as a multiobjective problem solved by the particle swarm optimization (PSO). The control procedure involves a series of commands for which the incident command system (ICS) is used as a secure communication structure. The performance of the proposed control framework is evaluated for the case of a typical MV microgrid in both grid-connected and islanded modes. [ABSTRACT FROM PUBLISHER]

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

Existing population-based Stochastic Search Algorithms (SSAs) are too time-consuming to solve dynamic optimal power flow (OPF). The solution proposed in this paper is to accelerate SSAs with memory. Two memory schemes, the similarity retrieval scheme and the mean-based immigrants scheme, are proposed and applied together to the Differential Evolution and Particle Swarm Optimizer, which are two representatives of SSAs. Experiments are conducted on modified IEEE 30-bus and IEEE 118-bus systems with changing load buses and the objective of minimizing real power transmission loss. The results show that the proposed schemes significantly improve the performance of the two existing algorithms, and that SSAs could be practical for tracking optima of dynamic OPF. [ABSTRACT FROM AUTHOR]

This paper proposes a computationally efficient technique for estimating the composite load model parameters based on analytical similarity of parameter sensitivity. When the model parameters are updated in the optimization procedure to best fit the actual load dynamics, i.e., measurements, parameters of similar sensitivity representation in the given mathematical model structure are updated in the same manner at every iterative step. This research allows for practically reducing the number of load model parameters to be identified in the estimation process and the overall computational cost while preserving the desired complexity and accuracy of the original model. This approach consequently facilitates the parameter estimation in the optimization process and helps manage increased number of parameters often criticized for adopting the dynamic composite load model via measurement-based approach. Case studies for the real power system demonstrate the computational efficiency and intact accuracy of the proposed method with reference to the existing methods of estimating all the parameters of the given composite load model independently. [ABSTRACT FROM AUTHOR]

The penetration of renewable distributed generation (DG) sources has been increased in active distribution networks due to their unique advantages. However, non-dispatchable DGs such as wind turbines raise the risk of distribution networks. Such a problem could be eliminated using the proper application of energy storage units. In this paper, optimal planning of batteries in the distribution grid is presented. The optimal planning determines the location, capacity and power rating of batteries while minimizing the cost objective function subject to technical constraints. The optimal long-term planning is based on the short-term optimal power flow considering the uncertainties. The point estimate method (PEM) is employed for probabilistic optimal power flow. The batteries are scheduled optimally for several purposes to maximize the benefits. A hybrid Tabu search/particle swarm optimization (TS/PSO) algorithm is used to solve the problem. The numerical studies on a 21-node distribution system show the advantages of the proposed methodology. The proposed approach can also be applied to the realistic sized networks when some sensitive nodes are considered as candidate locations for installing the storage units. [ABSTRACT FROM AUTHOR]

This paper proposes a new policy to calculate the locational marginal price (LMP) in the distribution networks containing distributed generation (DG). The proposed policy is based on remunerating the DG units to reduce the loss and emission of the network. LMP at each DG bus is calculated according to the contribution of the DG to the reduced amount of loss and emission. An iterative algorithm which is based on the nucleolus theory is proposed to allocate the loss and emission reduction. The proposed algorithm will provide a robust state estimation tool for distribution companies (DISCOs) in the next step of operation. The state estimation tool provides the decision maker with the ability to exert its control over private DG units when the loss and emission are minimized. Also, the proposed pricing policy requires decision maker to simply apply its best response strategy to the LMP based on the priority of loss, emission and DISCO's extra benefit. The proposed methodology is applied to two realistic distribution networks, and efficiency and accuracy of the method are verified. [ABSTRACT FROM AUTHOR]

This paper presents a new control strategy for high voltage direct current (HVDC) transmission based on the synchronverter concept: the sending-end rectifier controls emulate a synchronous motor (SM), and the receiving end inverter emulates a synchronous generator (SG). The two converters connected with a DC line provide what is called a synchronverter HVDC (SHVDC). The structure of the SHVDC is firstly analyzed. It is shown that the droop and voltage regulations included in the SHVDC structure are necessary and sufficient to well define the behavior of SHVDC. The standard parameters of the SG cannot be directly used for this structure. A specific tuning method of these parameters is proposed in order to satisfy the usual HVDC control requirements. The new tuning method is compared with the standard vector control in terms of local performances and fault critical clearing time (CCT) in the neighboring zone of the link. The test network is a 4-machine power system with parallel HVDC/AC transmission. The results indicate the contribution of the proposed controller to enhance the stability margin of the neighbor AC zone of the link. [ABSTRACT FROM AUTHOR]

The deployment of the advanced metering infrastructure (AMI) in distribution systems provides an excellent opportunity for load monitoring applications. Load decomposition can be done at the smart meters level, providing a better understanding of the load behavior at near-real-time. In this paper, loads' current and voltage waveforms are processed offline to form a comprehensive library. This library consists of a set of measurements projected onto the eigenloads space. Eigenloads are basically the eigenvectors describing the load signatures space. Similar to human faces, every load has a distinct signature. Each load measurement is transformed into a photo and an efficient face recognition algorithm is applied to the set of photos. A list of all the online devices is always stored and can be accessed at any time. The proposed method can be implemented at the smart meters level. The distributed computation that can be achieved by performing simple calculations at each smart meter, without the need for sending intensive data to a central processor, is beneficial. From a system operator perspective, load composition in near-real-time provides the loads' voltage dependence that are needed, for example, in volt-VAR optimization (VVO) in distribution systems. Further applications of load composition data are also discussed. [ABSTRACT FROM PUBLISHER]

This paper presents a short-term power regulation mechanism for post-segmentation power distribution systems in the presence of severe fault or large disturbance. Firstly, load priority is introduced into system separation and centroids of load clusters are allocated at nodes with distributed sources, respecting power balance and network connectedness. Secondly, fast power flow calculation is performed on the primarily formed islands to resolve load interruption for operational feasibility of partitions from power quality perspective. Then the effect of distributed generation fluctuations on durable operation of subsystems with various optimization objectives is examined. The load response is instructed by the proposed cost-based pricing scheme contemplating consumers' willingness. In addition, the influence of network congestion and load controllability on results of economic scheduling is investigated. Numerical results from the PG&E-69 distribution system are used to show the effectiveness of the developed model in radial structure load clusters. Illustration on the IEEE 118-bus case further proves its robustness and practicability for other distribution systems applications. This property is also useful for transmission switching and micro-grid applications. [ABSTRACT FROM PUBLISHER]

This paper presents a novel formulation of the Distribution System State Estimation (DSSE) optimization model. For a given electric three-phase circuit feeder, network models are built using a quasi-symmetric impedance matrix TRX representing the entire structure and topology of the radial network. As a key contribution, the state variables of demands and generators connected to large-scale distribution grids are obtained by using a convenient matrix reduction technique. As a result, the size of the optimization problem is considerably reduced with respect to the jacobian formulation by considering radial and weakly meshed exploitation and elimination of interconnecting nodes. Results and comparative analysis are presented using the IEEE 4-, 13-, 37-, 123-, and 8500-node test systems. [ABSTRACT FROM PUBLISHER]

A method for solving the optimal power flow (OPF) problem including HVDC connected offshore wind farms is presented in this paper. Different factors have been considered in the proposed method, namely, voltage source converter (VSC-HVDC) and line-commutated converter high-voltage DC (LCC-HVDC) link constraints, doubly fed induction generators' (DFIGs) capability curve as well as the uncertainties of wind power generation. Information gap decision theory (IGDT) is utilized for handling the uncertainties associated with the volatility of wind power generation. It is computationally efficient and does not require the probability density function of wind speed. The proposed decision-making framework finds the optimal decision variables in a way that they remain robust against the considered uncertainties. To illustrate the effectiveness of the proposed approach, it is applied on the IEEE 118-bus system. The obtained results validate the applicability of the proposed IGDT-based OPF model for optimal operation of AC/DC power systems with high penetration of offshore wind farms. [ABSTRACT FROM PUBLISHER]

Convex relaxations of non-convex optimal power flow (OPF) problems have recently attracted significant interest. While existing relaxations globally solve many OPF problems, there are practical problems for which existing relaxations fail to yield physically meaningful solutions. This paper applies moment relaxations to solve many of these OPF problems. The moment relaxations are developed from the Lasserre hierarchy for solving generalized moment problems. Increasing the relaxation order in this hierarchy results in “tighter” relaxations at the computational cost of larger semidefinite programs. Low-order moment relaxations are capable of globally solving many small OPF problems for which existing relaxations fail. By exploiting sparsity and only applying the higher-order relaxation to specific buses, global solutions to larger problems are computationally tractable through the use of an iterative algorithm informed by a heuristic for choosing where to apply the higher-order constraints. With standard semidefinite programming solvers, the algorithm globally solves many test systems with up to 300 buses for which the existing semidefinite relaxation fails to yield globally optimal solutions. [ABSTRACT FROM PUBLISHER]

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

The task of autonomous power sharing in a micro-grid is usually achieved by decentralized droop control on individual interface power converters, which may suffer from the dependence on output line impedances. Inaccurate reactive power sharing will occur under strongly non-uniform line impedances. Due to inherently distributed and heterogeneous nature of the micro-grid, it becomes an ideal platform for applications of consensus control algorithms. In this paper, the consensus-based droop control with sparse communication network is proposed to overcome the drawback of existing droop control methods. In particular, when line impedances of the power grid are either lossy with the uniform R/X ratio or even pure resistive, the consensus droop control is still an effective method for autonomous real and reactive power sharing. In addition, closed-loop system stability of the proposed consensus-based droop control method can be ensured by the energy function approach under certain conditions. Real-time simulations of two micro-grid systems are studied to validate the feasibility of the proposed consensus-based droop control method. [ABSTRACT FROM AUTHOR]

Due to progressive displacement of conventional power plants by wind turbines, dynamic security of large-scale wind integrated power systems is significantly compromised. In this paper we first highlight the importance of dynamic reactive power support/voltage security in large-scale wind integrated power systems with least presence of conventional power plants. Then we propose a mixed integer dynamic optimization based method for optimal dynamic reactive power allocation in large-scale wind integrated power systems. One of the important aspect of the proposed methodology is that unlike static optimal power flow based approaches, the proposed method considers detailed system dynamics and wind turbine grid code compliance while optimizing the allocation of dynamic reactive power sources. We also advocate that in large-scale wind integrated power systems, 1) better utilization of existing wind turbines especially wind farms with additional grid support functionalities like dynamic support (e.g., dynamic reactive power support, etc.) and 2) refurbishment of existing conventional central power plants to synchronous condensers could be one of the efficient, reliable and cost-effective option to address not only the issue of dynamic voltage security but also to strengthen other dynamic capabilities of the system including system inertia, etc. that are also significant challenges in large-scale wind penetrated power system. The proposed methodology is applied to the detailed model of the western Danish power system which is characterized by large-scale wind integration and least presence of central power plants. [ABSTRACT FROM AUTHOR]

The impedance of the virtual synchronous generator (VSG) is an effective method to analyze the dynamic interactions between the VSG and the grid. For the existence of power controllers and asymmetric inner-loop controllers in the d- and q-axis, there are couplings in the output sequence impedance of VSG. Although the couplings are relatively small, they still have a significant impact on the stability performance. However, there is no result published on this aspect up to now. To bridge this gap, a sequence impedance model based on harmonic linearization is established in this paper, which explicitly reveals the mirror frequency effect (MFE) in VSG. Subsequently, the relationships between the power controllers and the MFE are demonstrated. Finally, simulation results verify the feasibility and correctness of the theoretical analysis presented above. [ABSTRACT FROM AUTHOR]

Modern mixed-integer quadratic solvers generally handle binary variables more efficiently than nonlinear mixed-integer solvers. This is relevant to the power system operation models as the unit commitment formulations typically contain a large number of binary variables. This paper investigates how to achieve the accuracy level close to the one of the exact nonlinear models, but by utilising convex models and solvers. The presented unit commitment model is based on a Taylor-series expansion where both the voltage magnitude and angle are quadratically constrained. To achieve high accuracy, the model takes advantage of the meshed transmission network structure that enables replacement of the quadratic inequality constraints that cause constraint relaxation errors with the linear equality constraints. Quadratic constraints to be replaced as well as the operating point parameters are determined based on the presolve. The first presented case study validates the model's accuracy and the convergence of the iterative algorithm, while the second is a non-iterative full unit commitment problem. Unit commitment results show superior accuracy and similar computation times to the existing quadratic formulations on one hand and faster computation times than the exact nonlinear polar formulation on the other. [ABSTRACT FROM AUTHOR]

This paper presents an extensive multi-period optimal power flow framework, with new modelling elements, for smart LV distribution systems that rely on residential flexibility for combating operational issues. A detailed performance assessment of different setups is performed, including: ZIP flexible loads (FLs), varying degrees of controllability of conventional residential devices, such as electric vehicles (EVs) or photovoltaics (PVs), by the distribution system operator (DSO) (adhering to customer-dependent restrictions) and full exploitation of the capabilities offered by state-of-the-art inverter technologies. A comprehensive model-dependent impact assessment is performed, including phase imbalances, neutral and ground wires and load dependencies. The de-congestion potential of common residential devices is highlighted, analyzing capabilities such as active power redistribution, reactive power support and phase balancing. Said potential is explored on setups where the DSO can make only partial adjustments on customer profiles, rather than (as is common) deciding on the full profiles. The extensive analysis can be used by DSOs and researchers alike to make informed decisions on the required levels of modelling detail, the connected devices and the degrees of controlability. The formulation is computationally efficient, scaling well to medium-size systems, and can serve as an excellent basis for building more tractable or more targeted approaches. [ABSTRACT FROM AUTHOR]

Geomagnetically induced currents (GICs) can cause half cycle saturation of transformers and consequently affect the power grid with harmonics and reactive power losses. To effectively mitigate the negative GIC impacts in large-scale power systems, the present paper considers the problem of placing blocking devices in transformer neutrals. The placement problem of multiple blocking devices is first considered by analytically quantifying the associated reactive power losses. A linear sensitivity analysis is further provided for the case of blocking a single transformer, and it has been observed that the effects of blocking transformer neutral currents to be mostly local. This motivates us to propose the scheme that selects multiple substations to block all high voltage level transformers therein, based on a linearized approximation model. The effectiveness of such scheme has been demonstrated using both a 20-bus GIC test case and a realistically sized larger power system. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of voltage regulation in power distribution networks with deep-penetration of distributed energy resources, e.g., renewable-based generation, and storage-capable loads such as plug-in hybrid electric vehicles. We cast the problem as an optimization program, where the objective is to minimize the losses in the network subject to constraints on bus voltage magnitudes, limits on active and reactive power injections, transmission line thermal limits and losses. We provide sufficient conditions under which the optimization problem can be solved via its convex relaxation. Using data from existing networks, we show that these sufficient conditions are expected to be satisfied by most networks. We also provide an efficient distributed algorithm to solve the problem. The algorithm adheres to a communication topology described by a graph that is the same as the graph that describes the electrical network topology. We illustrate the operation of the algorithm, including its robustness against communication link failures, through several case studies involving 5-, 34-, and 123-bus power distribution systems. [ABSTRACT FROM PUBLISHER]

This paper proposes a multi-purpose VAr control strategy for solar PV inverters for voltage support in distribution networks. The proposed strategy can be applied under various PV power generation conditions. The inverters will normally operate in a dynamic VAr compensation mode for voltage support (including low PV and no PV periods). During mid-day when PV has surplus power, the proposed strategy will control the PV inverters to absorb VAr for voltage rise mitigation using a droop characteristic approach. During passing clouds, the strategy will mitigate voltage fluctuations by ramp-rate control of inverter VAr output. A dynamic model of the proposed PV inverter control has been developed to analyze its performance in terms of fast VAr control and voltage support under various PV generation conditions. The results of the analysis performed on an Australian distribution system show that the proposed VAr control strategy can mitigate voltage rise, and improve the voltage profile despite potential vast changes in the sun irradiation during passing cloud and also in the absence of PV output during the evening. [ABSTRACT FROM PUBLISHER]

A centralized reactive power compensation system is proposed for low voltage (LV) distribution networks. It can be connected with any bus which needs reactive power. The current industry practice is to locally install reactive power compensation system to maintain the local bus voltage and power factor. By centralizing capacitor banks together, it can help to maintain bus voltages and power factors as well as reduce the power cable losses. Besides, the centralized reactive power system can be easily expanded to meet any future load increase. A reasonably sized centralized reactive power compensation system will be capable of meeting the requirements of the network and the optimization algorithm proposed in this paper can help to find this optimal size by minimizing the expected total cost (ETCH). Different load situations and their respective probabilities are also considered in the proposed algorithm. The concept of the centralized reactive power compensation system is applied to a local shipyard power system to verify its effectiveness. The results show that an optimally sized centralized reactive power system exists and is capable of maintaining bus voltages as well as reducing the power losses in the distribution network. A significant power loss reduction can be obtained at the optimal capacity of the centralized reactive power compensation system in the case study. [ABSTRACT FROM PUBLISHER]

This paper deals with the design of an adaptive power oscillation damping (POD) controller for a static synchronous compensator (STATCOM) equipped with energy storage. This is achieved using a signal estimation technique based on a modified recursive least square (RLS) algorithm, which allows a fast, selective, and adaptive estimation of the low-frequency electromechanical oscillations from locally measured signals during power system disturbances. The proposed method is effective in increasing the damping of the system at the frequencies of interest, also in the case of system parameter uncertainties and at various connection points of the compensator. First, the analysis of the impact of active and reactive power injection into the power system will be carried out using a simple two-machine system model. A control strategy that optimizes active and reactive power injection at various connection points of the STATCOM will be derived using the simplified model. Small-signal analysis of the dynamic performance of the proposed control strategy will be carried out. The effectiveness of the proposed control method to provide power oscillation damping irrespective of the connection point of the device and in the presence of system parameter uncertainties will be verified through simulation and experimental results. [ABSTRACT FROM PUBLISHER]

With increasingly large scale of intermittent and non-dispatchable resources being integrated into power systems, the power flow problem presents greater uncertainty. In order to obtain the upper and lower bounds of power flow solutions including voltage magnitudes, voltage angles and line flows, Cartesian coordinates-based power flow is utilized in this paper. A quadratically constrained quadratic programming (QCQP) model is then established to formulate the interval power flow problem. This non-convex QCQP model is relaxed to linear programming problem by introducing convex and concave enclosures of the original feasible region. To improve the solutions bounds while still encompassing the true interval solution, optimality-based bounds tightening (OBBT) method is employed to find a better outer hull of the feasible region. Numerical results on IEEE 9-bus, 30-bus, 57-bus, and 118-bus test systems validate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper proposes a new approach for corrective voltage control (CVC) of power systems in presence of uncertain wind power generation and demand values. The CVC framework deals with the condition that a power system encounters voltage instability as a result of severe contingencies. The uncertainty of wind power generation and demand values is handled using a scenario-based modeling approach. One of the features of the proposed methodology is to consider participation of demand-side resources as an effective control facility that reduces control costs. Active and reactive redispatch of generating units and involuntary load curtailment are employed along with the voluntary demand-side participation (demand response) as control facilities in the proposed CVC approach. The CVC is formulated as a multi-objective optimization problem. The objectives are ensuring a desired loading margin while minimizing the corresponding control cost. This problem is solved using \epsilon-constraint method, and fuzzy satisfying approach is employed to select the best solution from the Pareto optimal set. The proposed control framework is implemented on the IEEE 118-bus system to demonstrate its applicability and effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents the fundamental concepts of a generalized central power management system and a decentralized, robust control strategy for autonomous mode of operation of a microgrid that includes multiple distributed energy resource (DER) units. DER units are divided into voltage-controlled and power-controlled DER units. The frequency of each DER unit is determined by its independent internal oscillator and all oscillators are synchronized by a common time-reference signal based on a global positioning system (GPS). The power management system (PMS) specifies the power and voltage set points for the local controllers of each DER unit. A linear, time-invariant, multivariable, robust, decentralized control system is designed to track the setpoints. Each control agent guarantees fast tracking, zero steady state error, and robust performance despite uncertainties of the microgrid parameters, topology, and the operating point. Existence conditions, control design procedures, eigenanalysis and robust stability analysis of the closed-loop system, and performance of the control strategy based on digital time-domain simulation studies in PSCAD/EMTDC platform, are reported. Performance of the control system is also verified based on hardware-in-the-loop (HIL) studies in the RTDS environment. [ABSTRACT FROM AUTHOR]

This paper presents a new family of universal control and management strategies for microgrids in smart distribution grids. The paper also provides a general and computationally-efficient framework for modeling and analysis of power management strategies in a microgrid with multiple-distributed generation (DG) units which eases microgrid dynamic studies and controller parameters selection in large microgrids with multiple DG units. Three different approaches for real and reactive power management are proposed. The controllers offer the following advantages: 1) the proposed topologies can be applied to both voltage-controlled (VC) and current controlled (CC) voltage source converters (VSCs). 2) The controllers are universal and realize requirements of both grid-connected and islanded modes, i.e., they share real and reactive power during islanding with constant frequency operation and act as grid supporting VSCs in the grid connected mode. 3) The drooping variables can be either power or current, thus VC-power drooping, VC-current drooping and CC-power drooping are different available variants. 4) The concept of hybrid polar-vector control is developed in this paper. Thus, it can combine the benefits of both types of controllers in one augmented strategy. 5) The controller emulates the behavior of conventional synchronous generators (SGs) which in turn results in better integration of electronically-interfaced DG units into the power system and prevents instabilities due to interaction of fast response DGs and SGs. 6) The controllers realize seamless and robust transition to the islanding mode. The controllers are developed under new concept of synchronous converters. A theoretical analysis and simulation results show that the proposed controllers yield the aforementioned requirements in one compact structure. [ABSTRACT FROM PUBLISHER]

Dispersed storage systems (DSSs) can represent an important near-term solution for supporting the operation and control of active distribution networks (ADNs). Indeed, they have the capability to support ADNs by providing ancillary services in addition to energy balance capabilities. Within this context, this paper focuses on the optimal allocation of DSSs in ADNs by defining a multi-objective optimization problem aiming at finding the optimal trade-off between technical and economical goals. In particular, the proposed procedure accounts for: 1) network voltage deviations; 2) feeders/lines congestions; 3) network losses; 4) cost of supplying loads (from external grid or local producers) together with the cost of DSS investment/maintenance; 5) load curtailment; and 6) stochasticity of loads and renewables productions. The DSSs are suitably modeled to consider their ability to support the network by both active and reactive powers. A convex formulation of ac optimal power flow problem is used to define a mixed integer second-order cone programming problem to optimally site and size the DSSs in the network. A test case referring to IEEE 34 bus distribution test feeder is used to demonstrate and discuss the effectiveness of the proposed methodology. [ABSTRACT FROM PUBLISHER]

This paper proposes an optimal power flow (OPF) model with flexible AC transmission system (FACTS) devices to minimize wind power spillage. The uncertain wind power production is modeled through a set of scenarios. Once the balancing market is cleared, and the final values of active power productions and consumptions are assigned, the proposed model is used by the system operator to determine optimal reactive power outputs of generating units, voltage magnitude and angles of buses, deployed reserves, and optimal setting of FACTS devices. This system operator tool is formulated as a two-stage stochastic programming model, whose first-stage describes decisions prior to uncertainty realization, and whose second-stage represents the operating conditions involving wind scenarios. Numerical results from a case study based on the IEEE RTS demonstrate the usefulness of the proposed tool. [ABSTRACT FROM PUBLISHER]

Within an alternating current (AC) optimal power flow (OPF) market clearing framework, market-settlement surplus (MS) is inevitable due to network losses, congestion, and reactive power. For a general AC-OPF model, decomposition of MS into its constituents is a challenge. Therefore, this paper proposes a solution for decomposing MS into its constituents, i.e., network losses, congestion, and reactive support services, by deriving analytical expressions for each of the components. An optimization problem, named pseudo-IV-OPF, is set up around the existing AC-OPF solution to derive expressions. The central idea involved in current and voltage OPF, that the current flow at sending end is exactly equal and opposite at receiving end, is exploited to derive the elements of MS by using Karush–Kuhn–Tucker conditions of optimality. It is important to note that a converged OPF solution, obtained from the standard AC-OPF model used by the utility, is an input to the proposed model. The efficacy of the proposed expressions is illustrated on various benchmark systems. [ABSTRACT FROM AUTHOR]

In this paper, a novel agent based dynamic Volt/Var control approach is introduced, by which the voltage security (i.e., voltage profile and mid- and long-term stability) can be improved and also power loss is reduced under postdisturbance condition and in a wide-area manner. The proposed scheme employs organized multiagent system to preserve voltage magnitude of all busbars within permissible range and reduction of power losses after any disturbance through appropriate coordination of reactive power sources. To accelerate exploitation of on-load tap changers (OLTCs) as well as suppressing the possibility of encountering voltage instability which may be initiated by them, a preventive scheme based on sensitivity analysis is proposed which determines efficient number of multitap changes of OLTCs. To evaluate the effectiveness of the introduced algorithm, different scenarios have been performed in Nordic 32 test system, where the numerical results in all cases demonstrate the effectiveness and reliability of the proposed scheme. [ABSTRACT FROM AUTHOR]

The impact of the electric vehicle (EV) charging on node voltages and feeder currents of an electric grid can be reduced by upgrading its feeder capacity or deploying onsite photovoltaic (PV) and battery energy storage (BES), or their appropriate combination. It, in turn, enhances the quality of service (QoS) of the charging. This paper proposes an approach, which can enable a distribution network operator/business owner in finding the appropriate combination of the solutions above for providing the best QoS at a minimum cost while reducing the grid impact. The developed approach takes into account the previously scarcely incorporated characterization aspects (whether it is a constant power, constant current, or constant impedance load) of the EV charging. It has been applied to an IEEE 37-bus system in conjunction with the parking lots of the University of Queensland for a case study. The numerical results show that the proposed approach can effectively find the appropriate combination of the solutions above and the corresponding optimal sizes of PV and BES for a given EV penetration level or a given QoS. [ABSTRACT FROM AUTHOR]

In this paper, an agent-based model is proposed to improve the electricity market efficiency by using different demand response programs (DRPs). In the proposed model, the strategic self-scheduling of each market player in the electricity market and consequent market interactions are considered by using a game theoretic model powered by a security constrained unit commitment. The tariffs of price-based DRPs and the amount of incentive in the incentive-based DRPs are optimized. Furthermore, a market power index and the operation cost are used to evaluate the market efficiency by using a multi-objective decision-making approach. The results show that different types of DRPs differently affect the oligopolistic behavior of market players, and the potential of market power in power systems can be mitigated by employing the proposed model for DRP optimization. Numerical studies reveal that applying combinational DRPs is more efficient when the regulatory body considers both economic and market power targets. [ABSTRACT FROM AUTHOR]

In this paper, a day-ahead market-clearing model for smart distribution systems is proposed. Various types of distributed energy resources (DERs), such as distributed energy storage, distributed generators, microgrids, and load aggregators, can bid into the day-ahead distribution-level electricity market. Considering system Volt/VAR control, network reconfiguration, and interactions with the wholesale market, an optimization model is built to clear the day-ahead market, through which the distribution locational marginal pricing (DLMPs) for both active power and reactive power are determined. Through derivations of the Lagrangian function and sensitivity factors, DLMPs are decomposed to five components (i.e., marginal costs for active power, reactive power, congestion, voltage support, and loss), which provide price signals to motivate DERs to contribute to congestion management and voltage support. Finally, case studies demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a microgrid (MG) proactive management framework to cope with adverse impacts of extreme windstorms. Upon receiving alerts for the forecasted windstorm, the framework finds a conservative schedule of MG with the minimum number of vulnerable branches in service while total load is served. The schedule ensures the MG normal operation prior to the windstorm while reducing the MG vulnerability at the event onset. The proposed method makes benefit of network reconfiguration, generation reschedule, conservation voltage regulation, optimal parameter settings of droop-controlled units, demand-side resources, and backup generation capacity. A vulnerability index is defined to assess the effectiveness of the proposed proactive management in reducing the MG vulnerability at the event onset. The proposed model is linearized that guarantees simplicity, robustness, and computational efficiency of the solution. The effectiveness of the proposed method is tested on a real-scale MG against a windstorm. [ABSTRACT FROM AUTHOR]

In order to solve the voltage violation problem caused by high penetration of photovoltaic (PV) units in distribution power networks, this paper proposes a double-layer voltage control strategy based on the distribution network partition. By optimizing the active and reactive power outputs of PV units, the minimization objective of PV active power curtailment and network active power loss can be achieved. In the basis of community detection algorithm, a novel cluster performance index based on the electrical distance and regional voltage regulation capability is presented to partition a distribution network into several clusters. The proposed double-layer voltage control strategy combines the cluster autonomous optimization and distributed intercluster coordination optimization in different time scales. The cluster autonomous optimization can eliminate intracluster voltage violation rapidly by alternately updating the intracluster optimal solution and the virtual slack bus voltage. The distributed intercluster coordination optimization with a long-time scale is based on the alternating direction method of multipliers and realizes global optimal control through finite boundary data exchange among adjacent clusters. The effectiveness and feasibility of the proposed method have been demonstrated via simulation tests on a real 10.5 kV feeder in China and the IEEE 123-bus system. [ABSTRACT FROM PUBLISHER]

There are more large-scale photovoltaic (PV) plants being established in rural areas due to availability of low-priced land. However, distribution grids in such areas traditionally have feeders with low X/R ratios, which makes the independent reactive power compensation method less effective on voltage regulation. Consequently, upstream step voltage regulator (SVR) may suffer from excessive tap operations with PV-induced fast voltage fluctuations. Although a battery energy storage system (BESS) can successfully smooth PV generation, frequent charge/discharge will substantially affect its cost effectiveness. In this paper, a real-time method is designed to coordinate PV inverters and BESS for voltage regulation. To keep up with fast fluctuations of PV power, this method will be executed in each 5 s control cycle. In addition, charging/discharging power of BESS is adaptively retuned by an active adjustment method in order to avoid BESS premature energy exhaustion in a long run. Finally, through a voltage margin control scheme, the upstream SVR and downstream PV inverters and BESS are coordinated for voltage regulation without any communication. This research is validated via a real-time digital simulator MatLab cosimulation platform, and it will provide valuable insights and applicable strategies to both utilities and PV owners for large-scale PV farm integration into rural networks. [ABSTRACT FROM PUBLISHER]

The recent rapid development of distributed generation (DG) necessitates the consideration of transmission–distribution interactions in voltage stability assessment (VSA), and how to perform a transmission–distribution-coupled static VSA (TDVSA) has become a pressing problem. To resolve this urgent issue, this paper first theoretically analyzes the impacts of the voltage-maintaining capacity and low-voltage tripping of DG units on the static voltage stability of an integrated transmission–distribution system and then proposes a distributed TDVSA method that fully considers these impacts when assessing the voltage stability of the integrated system. As the core of the method, a distributed continuation power flow algorithm is designed that includes a distribution-equivalencing-based predictor, a distributed transmission–distribution corrector, and a step-length regulator and requires only a limited amount of data to be exchanged between the transmission system operator (TSO) and the distribution system operator (DSO). Numerical simulations show that even in the case of low DG penetration, a cascading low-voltage tripping event can significantly degrade an integrated system's voltage stability, and only the proposed distributed TDVSA method can produce an accurate assessment. In addition, the number of iterations between the TSO and DSO is shown to be limited, indicating the potential of applying the proposed method to future grids. [ABSTRACT FROM PUBLISHER]