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This paper proposes a switching angle controller (SAC) and an automatic generation controller (AGC) for the doubly-fed induction generator (DFIG) to control the frequency of DFIG-based wind power penetrated power systems. The concept of virtual rotor angle of the DFIG is defined. The virtual rotor angle is controlled by the SAC in a bang-bang manner such that the active power of the DFIG is regulated to provide frequency support to the external power grids. The output of the SAC is also used for the control of pitch angle to offer a short-term regulation of the mechanical power input to the DFIG, and the long-term control of the mechanical power input is achieved with the AGC. Small-signal analysis is undertaken to verify the effectiveness of the SAC and the AGC. Simulation studies are carried out in a two-machine power system and a modified Kundur four-machine two-area power system, respectively. The frequency support performance of DFIGs having different control configurations is investigated. Modal analysis is undertaken to evaluate the effect of the SAC and the AGC in providing additional damping to the rotor oscillation modes of the modified Kundur four-machine two-area power system. [ABSTRACT FROM AUTHOR]

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

A novel online line switching methodology for increasing load margins to static stability limit of a look-ahead power system is developed. A design goal of the methodology is to balance speed (for online computation) and effectiveness (for quality of line switching solutions). Instead of dealing with the combinatorial nature of line switching problem, the proposed methodology employs the strategy of screening, ranking and identifying to find a set of high-quality solutions. The proposed methodology ensures the satisfaction of operational and engineering constraints of (look-ahead) post-switching power system. The proposed methodology also determines multiple solutions of line switching for operators to choose a desired one. The effectiveness of the online line switching methodology is evaluated on the IEEE 118-bus and a 1648-bus power systems with very promising results. [ABSTRACT FROM AUTHOR]

We investigate the potential for aggregations of residential thermostatically controlled loads (TCLs), such as air conditioners, to arbitrage intraday wholesale electricity market prices via non-disruptive load control. We present two arbitrage approaches: 1) a benchmark that gives us an optimal policy but requires local computation or real-time communication and 2) an alternative based on a thermal energy storage model, which relies on less computation/communication infrastructure, but is suboptimal. We find that the alternative approach achieves around 60%–80% of the optimal wholesale energy cost savings. We use this approach to compute practical upper bounds for savings via arbitrage with air conditioners in California's intraday energy market. We investigate six sites over four years and find that the savings range from $2–$37 per TCL per year, and depend upon outdoor temperature statistics and price volatility. [ABSTRACT FROM PUBLISHER]

This paper proposes a new transmission-constrained unit commitment method that combines the cost-efficient but computationally demanding stochastic optimization and the expensive but tractable interval optimization techniques to manage uncertainty on the expected net load. The proposed hybrid unit commitment approach applies the stochastic formulation to the initial operating hours of the optimization horizon, during which the wind forecasts are more accurate, and then switches to the interval formulation for the remaining hours. The switching time is optimized to balance the cost of unhedged uncertainty from the stochastic unit commitment against the cost of the security premium of the interval unit commitment formulation. These hybrid, stochastic, and interval formulations are compared using Monte Carlo simulations on a modified 24-bus IEEE Reliability Test System. The results demonstrate that the proposed unit commitment formulation results in the least expensive day-ahead schedule among all formulations and can be solved in the same amount of time as a full stochastic unit commitment. However, if the range of the switching time is reduced, the hybrid formulation in the parallel computing implementation outperforms the stochastic formulation in terms of computing time. [ABSTRACT FROM PUBLISHER]

The problem of the optimal placement of sectionalizing switches in radial distribution networks is studied. Tree-structure based algorithms for the computation of performance indexes for the given positions of sectionalizing switches are presented. It is shown that the algorithms are very efficient and can be useful in search methods that require the evaluation of reliability indexes for a large number of test selections. Efficient deterministic algorithms are presented to find the optimal allocation of a given number of sectionalizing switches to minimize a selected performance/reliability index. The performance of the algorithms is assessed using the existing distribution networks of various sizes. It is shown that the proposed algorithms outperform the state-of-the-art approaches in terms of computational efficiency. [ABSTRACT FROM AUTHOR]

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

This second part of a two-part paper presents the implementation and simulations of a risk-based optimization approach for distribution expansion planning with distributed generation (DG), as described in Part I. The proposed approach is first applied to a test system in order to test convergence of the optimization algorithm and then comparing its numerical results with the ones from the exhaustive method. Later, the expansion planning of a typical Latin American distribution network is assessed and analyzed. For this, two expansion optimizations are performed: one, taking into account traditional expansion alternatives (without DG) and, the other, considering DG as flexible expansion options. Finally, the computational effort is analyzed. Results show that the greatest contribution of DG lies in the flexibility it gives to expansion planning, mainly by deferring network reinforcements. [ABSTRACT FROM PUBLISHER]

Black start is the primary procedure deployed for rapid recovery from a complete blackout. For isolated power systems such as the Taiwan power system (TPS), a reliable and efficient black start procedure is more important than interconnected power systems. In this paper, a black start decision-supporting system (BSS) with an interactive graphical user interface (GUI) has been developed. BSS can rapidly generate optimal black start strategies according to the updated system data configuration and objective function; furthermore, BSS can automatically simulate the strategies and visualize the results. By applying the BSS to evaluate the black start strategies for TPS, the effectiveness of BSS has been demonstrated. The BSS has been utilized by Taiwan Power Company (TPC) for black start planning with comparison to traditional manual planning. With the aid of BSS, the dispatchers are equipped with more support and the restoration risk can be much alleviated. [ABSTRACT FROM PUBLISHER]

In power system operation, transmission congestion can drastically limit more economical generation units from being dispatched. In this paper, optimal transmission switching as a congestion management tool is utilized to change network topology which, in turn, would lead to higher electricity market efficiency. Transmission switching (TS) is formulated as an optimization problem to determine the most influential lines as candidates for disconnection. In order to relieve congestion without violating voltage security, TS is embedded in an optimal power flow (OPF) problem with AC constraints and binary variables, i.e., a mixed-integer nonlinear programming (MINLP) problem, solved using Benders decomposition. Also, a methodology is presented which provides a guideline to the system operator showing the order of switching manoeuvres that have to be followed in order to relieve congestion. It is also shown that TS based on DC optimal power flow (DCOPF) formulation as used in the literature may jeopardize system security and in some cases result in voltage collapse due to the shortcomings in its simplified models. In order to evaluate the applicability and effectiveness of the proposed method, the IEEE 57-bus and IEEE 300-bus test systems are used. [ABSTRACT FROM PUBLISHER]

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

The existing microgrid-based distribution system restoration methods follow traditional restoration criteria, which achieve a maximum coverage of distribution systems. In extreme conditions (e.g., natural disasters and physical and cyber attacks), the traditional restoration plans could pose additional financial and security risks to local utility customers. That is, restored services could be further interrupted by subsequent outages in the extended event. To address such resilience challenges, this paper proposes the formation of adaptive multimicrogrids as part of the critical service restoration strategy. The proposed strategy comprises microgrid formation (MF) and load switching sequence (LSS) steps. The MF forms multiple microgrids with minimum overall scale and radial or looped topologies and includes optimally positioned mobile emergency resources to address potential risks in extreme conditions. The LSS determines a proper load switching sequence for ensuring the system dynamic performance in the restoration process. The effectiveness of the proposed strategy is verified by a case study on the IEEE 132-node test feeder system and the time-domain simulation in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of improving the conventional iterative method used for integrated extended equal area criterion (IEEAC) and single machine equivalent (SIME) for multi-swing transient stability limit analysis in power system operation. Effects of the complicated phenomena on the conventional method, i.e., nonmonotonic variation of the stability margin and the isolated stability domain (ISD), are studied. Accordingly, the conventional method is improved for both efficiency and accuracy. With this knowledge, an improved sensitivity-based iterative method for searching multi-swing transient stability limit is proposed. The advantage of this method is that the complicated phenomena are fully considered and their effects are either overcome or avoided as much as possible. Case studies on the ten-generator New England power system are presented to verify the effectiveness and efficiency of this improved method. [ABSTRACT FROM PUBLISHER]

The Shangdu power plant has four 600-MW turbine-generators connected to the North-China Grid through two 500-kV transmissions, which are compensated with 45% fixed series capacitors. Extensive studies conducted on the system model indicate that the system suffers from multimodal subsynchronous resonance (SSR). To solve the problem, a countermeasure is developed by combining the supplementary excitation damping control (SEDC) and the torsional stress relay (TSR). In this paper, the characteristics of the SSR problem are investigated. Then the developed SEDC is presented. To validate the effectiveness of the proposed SEDC as well as the results of model studies, field tests were conducted under various operating conditions. The tests fully exposed the realistic threat of SSR in the system. Meanwhile, it is demonstrated that the developed SEDC can improve torsional damping significantly, and thus solve the multimodal SSR problem effectively. This is the first time in China that practical SEDCs have been developed and their ability to mitigate multimodal SSR has been verified in a real series-compensated system. [ABSTRACT FROM AUTHOR]

Remote-controlled switches (RCSs) play an important role in prompt service restoration of distribution systems (DSs). However, the cost of RCSs and the vast footprint of DSs limit widespread utilization of RCSs. In this paper, we present a new approach to RCS allocation for improving the performance of restoration and optimizing reliability benefits with reasonable RCS cost. Specifically, the optimal number and locations of to-be-upgraded switches can be determined with different objectives: maximizing the reduction of customer interruption cost; maximizing the reduction of system average interruption duration index; or maximizing the amount of loads that can be restored using the upgraded RCSs. We show that these models can actually be formulated as mixed-integer convex programming problems. We further introduce a novel method to equivalently transform and efficiently solve each of them. The global optimum can thus be computed within a reasonable amount of time. The IEEE 33-node and 123-node test systems are used to demonstrate the proposed models and algorithms. [ABSTRACT FROM PUBLISHER]

A transmission topology control (TC) framework for production cost reduction based on a shift factor (SF) representation of line flows is proposed. The framework can model topology changes endogenously while maintaining linearity in the overall Mixed Integer Linear Programming (MILP) formulation of the problem. In large power systems it is standard practice to optimize operations considering few but representative contingency constraints. Under these conditions and when tractably small switchable sets are analyzed, the SF framework has significant computational advantages compared to the standard B$\theta$ alternative used so far in TC research. These claims are supported and elaborated by numerical results on full models of PJM with over 13,000 buses. We finally present analytical investigations on locational marginal price (LMP) computation in our SF TC framework and their relation to LMPs computed for problems without TC. Also, we discuss practical implementation choices such as sufficient conditions on lower bounds that allow selection of large numbers employed in the MILP formulation. [ABSTRACT FROM AUTHOR]

We present a threshold-based cardinality inimization formulation for the security-constrained economic dispatch problem. The model aims to minimize the operating cost of the system while simultaneously reducing the number of lines operating in emergency operating zones during contingency events. The model allows the system operator to monitor the duration for which lines operate in emergency zones and ensure that they are within the acceptable reliability standards determined by the system operators. We develop a continuous difference-of-convex approximation of the cardinality minimization problem and a solution method to solve the problem. We also present mixed-integer programming reformulation of the cardinality minimization problem. Our numerical experiments demonstrate that the cardinality minimization approach reduces the overall system operating cost as well as avoids prolonged periods of high electricity prices during contingency events. [ABSTRACT FROM AUTHOR]

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly. [ABSTRACT FROM PUBLISHER]

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

With the expansion and enhancement of the power transmission network, short-circuit current (SCC) has become a major concern in grid operations. While transmission switching is one effective solution to reduce the SCC without investing in additional equipment, switching lines could threaten system N-1 security. To find an efficient, and secure, yet economic switching solution, this paper proposes an optimal transmission switching model with SCC limitation and N-1 reliability. As the relationship between SCC and integer variables associated with the line states is coupled, nonlinear and difficult to explicitly express, an effective linearization method is proposed. Theoretical analysis of the linearization error is performed using an illustrative example. Case studies have shown that the linearization error is generally small and decreases rapidly with the increase of electrical distance. Based on the linearized expression for SCC, a transmission switching model with SCC limitation and N-1 reliability constraints is proposed. Furthermore, to assure the calculation accuracy for the SCC, an iterative algorithm is designed to compensate for the linearization error. Case studies on the modified IEEE 30-bus, 118-bus and practically-sized 300-bus systems validate the effectiveness of the proposed model and algorithm. The solving efficiency of the model is investigated and discussed as well. [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]

The European Union is targeting a 20% share of energy from renewable resources by 2020, and this increase is in turn expected to lead to operational challenges that will require various congestion management actions by system operators. In this paper, we deal with topology control of the transmission network as a congestion management resource and evaluate the impacts of topology control on the European electricity network. To do this, we co-optimize unit commitment and transmission switching over 24 h, and we use a decomposition scheme to tackle the resulting large-scale problem. Our analysis is conducted on different scenarios of load and renewable power generation. We find that topology control results in significant cost savings within Europe which tend to be inversely related to net load. The robustness of our results is supported by an extensive sensitivity analysis. [ABSTRACT FROM AUTHOR]

The dc symmetrical component method is introduced for the analysis and control of bipolar dc distribution systems under asymmetrical operation. This method is an extension of the classical symmetrical component theory in three-phase ac power systems. The asymmetrical voltage and current in the positive and negative poles are decomposed into symmetrical components in common and differential modes. The equivalent circuit for each mode is derived, which forms decoupled mode networks. Consequently, it allows for independent investigation of each mode, and provides an insightful view of the static and dynamic behavior of a bipolar dc power system. The dc symmetrical component method is a general approach which is applicable to different aspects of system design. As an example, an enhanced common-mode voltage regulation scheme is described. It suppresses common-mode LC resonance by adding active damping control, and reduces common-mode impedance to improve power quality and voltage stability. The major theoretical conclusions are verified by experimental results. [ABSTRACT FROM AUTHOR]

Delta-connected switched capacitors are common in three-wire MV distribution systems as found in Europe and Australia but the majority of past studies focus on star-connected capacitors as applied in North America. This study presents a comprehensive optimization based sequential strategy and a multi-objective optimization based real-time strategy for the optimal placement and control of delta-connected switched capacitors. Considering load variations, a comprehensive optimization for capacitor placement is formulated to maximize the net annual returns from network loss reduction and capacity release. A sequential strategy based on loss sensitivity analysis is presented for efficient capacitor placement on large-scale unbalanced distribution networks. Then a capacitor control strategy is proposed to simultaneously minimize network losses, voltage deviations and voltage unbalance factor (VUF) while a weighted sum method reflects the preferences on the mutually conflicting control objectives. For the mixed integer programming (MIP) problems of capacitor placement and control, an improved backward/forward sweep (BSFS) load flow based particle swarm optimization (PSO) method is used. Finally, the robustness of the proposed capacitor placement and control strategies are verified by comparison against existing popular schemes through detailed simulations over 24 h on a real unbalanced Australian MV network. [ABSTRACT FROM AUTHOR]

Three-phase unbalance could have significant impacts on the secure and economic operation of a low-voltage distribution system. With the deployment of smart meters and the emergence of phase switch devices (PSDs), more efficient schemes for mitigating three-phase unbalance are expected by utilizing numerous measurement data and the installed PSDs in low-voltage areas. Therefore, a bi-level optimal phase switch device placement model for mitigating three-phase unbalance is proposed in this work. In the upper-level model, the PSD placement strategy is optimized by minimizing the total costs of PSD installation and operation costs of low-voltage areas determined in the lower-level model. In the lower-level model, the operation costs of low-voltage areas for typical days are minimized based on the PSDs and their locations determined in the upper-level model. The proposed bi-level model is tested by an actual low-voltage area of Zhejiang province, China, and the effectiveness of the optimal PSD placement model for reducing the total investment and operation costs of the low-voltage area demonstrated. [ABSTRACT FROM AUTHOR]

A hierarchical decentralized network reconfiguration approach to minimize power losses for smart distribution systems was presented in Part I. In this paper, the proposed approach is applied to four test distribution systems to examine its performance. A demonstration system consisting of the test system and distributed intelligent agents is built using MATLAB/Simulink to illustrate how the decentralized approach is implemented. Simulation results of the proposed approach are then compared with results of a centralized implementation and the harmony search method. It is shown that the decentralized approach can achieve similar results as other methods with significantly reduced computation time. The impacts of time-varying loads and faults are also studied through dynamic network reconfiguration on the 118-bus test system. Simulation results illustrate that dynamic network reconfiguration with time-ahead planning can determine the optimal configuration for each operating period to significantly reduce system energy losses. The enhanced performance of the hierarchical decentralized approach is clearly established. [ABSTRACT FROM PUBLISHER]

This paper introduces a multi-objective fault indicator (FI) placement method in electric distribution systems. The prevalent FI placement problem formulation is extended by considering effects of existing protection and control devices on customers' restoration time. Moreover, the customers' average restoration time index (CARTI) is proposed, as a new technical objective function with respect to uncertainties of automatic switching. Furthermore, a multi-objective solution approach is developed to simultaneously minimize indispensable economic and technical objectives. The resultant optimization problem is solved through a multi-objective particle swarm optimization (MOPSO) based algorithm, accompanied by a fuzzy decision making method to select the best result among the obtained Pareto optimal set of solutions. Assuming SAIDI and CARTI as technical objectives, the proposed method is applied to bus number four of the Roy Billinton test system (RBTS4), as well as a real-life distribution network with about 5500 customers, followed by a discussion on results. [ABSTRACT FROM PUBLISHER]

The authors discuss an article by M. Lavorato and colleagues on imposing radiality constraints in power distribution system optimization problems. They claim that the paper lacks any reference where an alternative mathematical formulation is proposed to deal with transfer nodes or zero-injection nodes. In their opinion, the possibility for transfer nodes is not realistic, being in opposition to the usual operation of the medium voltage (MV) systems where all the transfer nodes are connected to.

The reconfiguration of distribution networks is an important combinatorial problem. This work addresses the particular case of reconfiguration after an outage caused by the loss of a single branch of the network. The reconfiguration is carried out over two domains simultaneously: re-switching strategies and transformer tap-changer adjustments. The approach was tested using a real large-scale network within the concession area of Energy Australia. The model considers four operational elements: an AC power flow model, the network's radial topology when operating, voltage limits and load limits. Two evolutionary algorithms were implemented and tested. The first was a genetic algorithm, applied over the space of possible re-switching strategies, and for both re-switching and tap-changer adjustments, simultaneously. The second was a memetic algorithm, applied over the same two variations of the reconfiguration problem. Computational tests consider the evaluation of the loss of every branch, reporting the number of buses affected, and the number of overloaded branches after the reconfiguration. [ABSTRACT FROM PUBLISHER]

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

Recently, a hybrid average-value/detailed modeling technique has been presented for efficient electromagnetic transient (EMT) simulation of power systems containing ac–dc line-commutated rectifiers (LCRs). In this letter, the hybrid modeling methodology is extended to consider asymmetrical operation of LCRs due to internal faults of switches. The hybrid model permits large time-steps as opposed to conventional switching models that require precise handling of switching events and respectively small time-steps. The extended hybrid model is also demonstrated to possess numerical advantages over the existing state-of-the-art average-value models (AVMs) of faulty LCRs while providing more accurate results. [ABSTRACT FROM AUTHOR]

Multi-area load frequency control (LFC) selects and controls a few generators in each area of the power system in an effort to dampen inter-area frequency oscillations. To effectively dampen such oscillations, it is required to enhance and lower the control activity dynamically during operation, so as to adapt to changing circumstances. Changing circumstances should cover not only parametric uncertainties and unmodelled dynamics (e.g. aggregated area dynamics and bus dynamics), but also the increasing structural flexibility of modern power systems (e.g. protection mechanisms against faults and cyber-attacks, or topology reconfiguration mechanisms for demand response). As formal stability guarantees around such an attractive adaptive multi-area LFC concept are still lacking, this work proposes framework in which adaptation and switching are combined in a provably stable way to handle parametric uncertainty, unmodelled dynamics, and dynamical interconnections of the power system. Stability is studied in the Lyapunov theory sense using the standard structure-preserving modelling approach, and the resulting adaptive multi-area LFC design is validated using an IEEE 39-bus benchmark. [ABSTRACT FROM AUTHOR]

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

Requirements of economic and reliability criteria are often stressed simultaneously in operating and planning models for distribution systems. However, conventional reliability evaluation algorithms are hard to be integrated to these optimization models analytically. Recently, several optimization model-based reliability assessment methods have been proposed, which can be embedded into such models. Nevertheless, the detailed placement and actions of circuit breakers and switches are ignored or oversimplified in these methods, leading to an inconsistency with the real world situation. Thus, we propose a new optimization model-based reliability assessment method that fully considers detailed placement and actions of circuit breakers and switches in distribution networks. Based on fictitious fault flows, strategies for tripping circuit breakers to cut fault current, operating switches to isolate the fault and processing post-fault network reconfiguration are linearly modeled as constraints. Therefore, this method can be easily integrated into operating and planning models of distribution networks. Case studies on 54-node, 85-node, 137-node and 417-node distribution networks show the scalability and efficiency of the proposed model. [ABSTRACT FROM AUTHOR]

It is speculated that higher penetration of inverter-based distributed photo-voltaic (PV) power generators can increase the risk of tripping events due to voltage fluctuations. To quantify this risk utilities need to solve the interactive equations of tripping events for networked PVs in real-time. However, these equations are non-differentiable, nonlinear, and exponentially complex, and thus, cannot be used as a tractable basis for solar curtailment prediction and mitigation. Furthermore, load/PV power values might not be available in real-time due to limited grid observability, which further complicates tripping event prediction. To address these challenges, we have employed Chebyshev's inequality to obtain an alternative probabilistic model for quantifying the risk of tripping for networked PVs. The proposed model enables operators to estimate the probability of interdependent inverter tripping events using only PV/load statistics and in a scalable manner. Furthermore, by integrating this probabilistic model into an optimization framework, countermeasures are designed to mitigate massive interdependent tripping events. Since the proposed model is parameterized using only the statistical characteristics of nodal active/reactive powers, it is especially beneficial in practical systems, which have limited real-time observability. Numerical experiments have been performed employing real data and feeder models to verify the performance of the proposed technique. [ABSTRACT FROM AUTHOR]

The fast urbanization process in developing countries creates an electricity load surge that poses serious congestion problems to the urban power grid (UPG). The current practice of system operators is to reconfigure the topological structure of the 110-kV high voltage distribution network (HVDN) in an attempt to adjust the load distribution and eliminate the UPG congestion. However, HVDN reconfiguration is a large scale, non-convex and non-linear optimization problem that is intractable to be solved in an efficient manner. In order to reduce the computing cost and overcome the difficulty in the solving process, new partition rules are proposed to divide the HVDN into multiple smaller regions. The topological structure of each region can be optimized either independently or interdependently based on the condition of the UPG. The solving process is modeled as a bi-level iterative line switching problem. At the upper level, the operational boundary (OB) of each regional HVDN is calculated based on a set of convex ACOPF constraints. At the lower level, the line switching scheme of each regional HVDN is derived based on the corresponding mixed integer second-order cone programming (MISOCP) model considering the OB. Then, the line switching result is examined by the AC power flow to identify whether there is any violation or not. This iterative process continues until all the violations are corrected in the UPG. The proposed method was validated by a modified IEEE 58-node test system and a practical 157-node UPG system. The simulation results showed that the proposed method is able to achieve a higher computational efficiency than the traditional method so it is promising for online applications. [ABSTRACT FROM AUTHOR]

With the advent of Smart Grids and advanced communication technologies, the self-healing scheme has become a desirable function of the operation and planning of electrical distribution systems (EDSs). In the presence of a permanent fault, an optimized self-healing scheme minimizes the unsupplied demand while maintaining the faulted section of the network isolated. The service restoration of the self-healing scheme is a combinatorial optimization problem whose computational complexity grows exponentially with the number of binary variables. To resolve this issue, a distributed optimal service restoration strategy is developed based on the alternating direction method of multipliers (ADMM). The service restoration problem is formulated as a mixed-integer second-order cone programming (MISOCP) problem. The decision variables of the problem are the status of the remote-controlled switches, load zones and load shedding at each controllable demand. Operational constraints, such as current and voltage magnitude constraints, distributed generation (DG) capacity constraints and radial topology constraints, are respected in the optimization problem. Through the ADMM, the optimization problem is distributed among the zones of the EDS, without requiring a central controller. Two test systems, an unbalanced 44-node system and the IEEE 123-node system, were used to conduct case studies. Results show that the proposed method can provide optimal service restoration solutions in reasonable time without a central controller. [ABSTRACT FROM AUTHOR]

A look-ahead contingency-constrained line switching problem is presented to enhance the static voltage stability of a look-ahead (say 30 minutes) base case, respecting a set of credible contingencies. This problem seeks to identify the ‘best’ network topology by switching out transmission lines to maximize the load margin of a look-ahead base case while ensuring the load margins of a set of credible contingencies are acceptable. Moreover, the voltage and thermal limitations are respected in the post-switching look-ahead base case. To solve the problem in an online environment, a group-based method is developed to reduce the complexity of the contingency constraints and enable tractable computation. Extensive numerical results on the IEEE 118-bus and the 1648-bus power systems examine the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

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

In a multi-microgrid system (MMG), the microgrids (MGs) are normally managed by independent operators. Distributed energy trading/scheduling schemes via interactions of these MG operators have been extensively investigated. How to coordinate these MGs to implement the acquired optimal schedule in the real time under constant load fluctuation while guaranteeing operational stability is seldom reported. Due to the intrinsic advantages of scalability, robustness, and fast response in comparison to the centralized scheme, a multi-agent based distributed optimal tie-line power flow control strategy is proposed to achieve this objective, which is facilitated by a regional communication network overlapping each MG and distributed sensors monitoring the tie-line power flows. When the MMG is operated in the grid-connected mode, the proposed scheme can maintain the scheduled tie-line power flows among the MGs in the presence of any disturbance by adjusting the real-time power outputs of the distributed energy resources proportionally. When the MMG is islanded, frequency recovery can be further achieved via a local frequency feedback mechanism. Convergence of the proposed approach is analytically proved. Simulation results in a four-MG system modified from the IEEE 34-bus test feeder system validate the effectiveness and efficiency of the proposed approach in both grid-connected and islanded modes. [ABSTRACT FROM AUTHOR]

The electrical power grid is a critical infrastructure that plays a key role in supporting modern society. The reliability of power systems needs to be continuously maintained to deliver high-quality electric services. Due to the tremendous amounts of potential investment demanded for constructing new electricity transmission facilities, electric utilities need economical solutions that can enable them to supply electricity to their customers in a cost-effective and reliable way. Dynamic thermal rating (DTR) and network topology optimization (NTO) technologies aim to maximize the use of existing transmission assets and to provide flexible ways to enhance reliability of the power system. In this study, the DTR and NTO are incorporated into the power grid reliability assessment procedure using the sequential Monte Carlo simulation. Multiple case studies are carried out based on the modified IEEE RTS-79 and IEEE RTS-96 systems, accounting for long-term multiarea weather conditions. The numerical results indicate that with the incorporation of DTR and NTO, the reliability of power systems can be improved. The effect of these methods is especially significant for power grids with lower electricity delivery capabilities. [ABSTRACT FROM AUTHOR]

Metal oxide varistors (MOVs) are used in power distribution engineering to suppress lightning and switching surges. Techniques from solid state engineering as well as laboratory experiments have been used to derive models for these devices. The models so derived are combined with circuit models for the distribution system to obtain an integrated, lumped parameter, nonlinear model. The model is used to assess the voltage and current waveshapes in the MOV and to evaluate the energy dissipated in the MOV. The application of such a calculation is illustrated to assess the “energy rating” of an MOV arrester for an electronically controlled distribution circuit. Comments on the switching time of the MOV are provided: the characteristic time of impact ionization events is typically on the order of femtoseconds to picoseconds. [ABSTRACT FROM AUTHOR]

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

A novel, fast, and flexible holomorphic embedding (FFHE) method is proposed for solving power flow problems with Q-limits. New embedded systems are developed for power flow equations at the PV and PQ buses for flexibility that allows us taking any state, instead of accepting only some certain point (e.g., a flat start and a zero-current injection point), as the initial guess. This flexibility allows us a warm start, a dc power flow solution, or other starts, leading to the reduced runtime and a decreased number of needed steps, as compared with existing embedded systems that only accept several particular points as the initial guess. However, the proposed method may not be globally convergent in the sense that such flexibility and flexible embedded systems do not ensure convergence or a superior rate of convergence for an arbitrary start. To implement the proposed FFHE, a new numerical scheme is devised to compute the numerical solution without explicitly calculating the rational approximant. To evaluate its effectiveness and practicability, the proposed novel FFHE method is applied to a series of power flow test cases ranging from 3 to 13659 buses. It is found that the proposed FFHE method requires less runtime than Newton's method for most test cases. By using Newton's method as a reference, FFHE is shown to be more effective than the holomorphic embedding methods that had been documented in the literature; partly due to its flexibility and the new scheme for computing numerical solutions. [ABSTRACT FROM PUBLISHER]

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

Reactive power outputs of DGs are used along with capacitor banks to regulate distribution network voltage. However, reactive power capability of a DG is limited by the inverter ratings and real power outputs of the DG. In order to achieve optimal power flow, minimize power losses, and minimize switching of capacitor banks, a day-ahead coordinated dispatch method of reactive power is proposed. Forecast errors of DG real power in every period are used to estimate the probability distribution of DGs reactive power capacity. Considering different output characteristics and constraints of reactive power sources, a dynamic preliminary-coarse-fine adjustment method is designed to optimize DG and shunt compensator outputs, decrease the switching cost, and reduce loss. The preliminary optimization obtains initial values, and multiple iterations between the coarse and fine optimizations are used to achieve a coordinated result. Simulations studies are performed to verify the proposed method. [ABSTRACT FROM AUTHOR]

Proliferation of renewable energy resources in distribution networks has captured distribution companies' attention towards more active management tools. Thanks to the smart grid paradigm, hourly network reconfiguration, which is still among immature ideas, can bring the activeness required to handle fluctuating output of renewable resources. The aim of this study is to analyze the worthiness of the hourly reconfiguration in the presence of renewable energy resources. For doing so, a mathematical model is devised to minimize daily network losses via applying hourly reconfigurations. The model is a mixed integer second-order cone programming problem and is solved via MOSEK solver. The electrical demand variations as well as renewable power generation fluctuations during a day are taken into account. The proposed method is applied to the Baran 33-bus system and the results including a great deal of sensitivity analyses on key parameters are presented and discussed. [ABSTRACT FROM AUTHOR]