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In this paper, novel models for electronically coupled distributed energy resources (ECDERs) for online fault calculations of large-scale systems are proposed. ECDERs have different fault responses than traditional synchronous and induction (AC) machines, and generally accepted models for these emerging DERs do not exist. The deployment of ECDERs is constantly increasing worldwide and there is an urgent need for developing appropriate models for fault calculations. In order to have fast calculations, applicable to large-scale systems, the dynamic behavior of traditional AC machines have been approximated in three steady state time-periods (sub-transient, transient, and steady-state). Accordingly, the online fault calculations of large-scale systems have been conducted for these three periods. To simulate the ECDERs’ dynamic behavior, and develop models that are compliant with traditional fault calculations, fault models of ECDERs in the sub-transient, transient, and steady-state periods are proposed, with a short peak current period included in the proposed models during the sub-transient period. To validate the proposed models, they are integrated into recently developed online fault calculations, and tested on various large-scale systems. Results from computer simulations are compared with results obtained using state-of-the-art laboratory equipment, as well as with relevant reports on fault current contributions of ECDERs. The results match very well, further validating the proposed models. [ABSTRACT FROM AUTHOR]

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

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

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

The distributed generators (DGs) and energy storages systems (ESSs) have different droop characteristics for power sharing in autonomous microgrids (MGs). In previous research, the distributed secondary control is proposed for only one specific type of units, and relies on periodic communications among neighbors. In this paper, a unified distributed real power sharing control scheme based on the dynamic event-triggered mechanism is proposed for droop-governed DGs and ESSs. A unified power sharing strategy is proposed where the power are fairly shared among all DGs and ESSs considering their different power ratings and capacities, while state-of-charges among ESSs are balanced. In the meantime, a distributed event-triggered control scheme with a novel dynamic triggering mechanism is designed to reduce the communications among controllers. Besides, the proposed event-triggered mechanism is sample-based and only uses the largest and the second smallest eigenvalues of the Laplacian matrix to design the controller gain and event-triggered parameters. To validate the proposed control design, a MG test system with detailed component models is built in the OPAL-RT real-time simulator. The results demonstrate the effectiveness and performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Maintaining balanced voltages across distribution networks is becoming more challenging with increasing deployment of single-phase distributed generation and larger single-phase loads. The paper develops a reactive power compensation strategy that uses distributed solar photovoltaic (PV) inverters to mitigate such voltage unbalance. The proposed strategy takes advantage of Steinmetz design and is implemented via both decentralized and distributed control. The latter coordinates PV inverters through a communication network. We demonstrate the performance of the controllers on the IEEE 13-node feeder and a much larger taxonomy feeder (617 nodes and 1196 triplex nodes), and consider different connections of loads and PV systems. Simulation results demonstrate the trade-offs between the controllers. It is observed that the distributed controller achieves greater voltage unbalance reduction than the decentralized controller, but requires communication infrastructure. [ABSTRACT FROM AUTHOR]

The ancillary services that could be provided by the distributed generators and the energy storage systems are expected to give great added value to the microgrid-based smart grid topologies. These services must be integrated into the control system of the microgrids. In this paper, the pseudo-state-of-charge concept is introduced to improve energy storage management. Additionally, a noninvasive-to-the-inverter PV-plant control strategy, based on the remote control of PV-strings actuators, is presented and applied on a microgrid-based smart grid topology. The operation of the microgrid with the improved control infrastructure and the iterative algorithm is compared, in terms of reliability, to a microgrid with a different control strategy and topology. The experimental results highlight the advantages of the developed strategy. [ABSTRACT FROM AUTHOR]

The authors have proposed Flexible, Reliable and Intelligent ENergy Delivery System (FRIENDS) as a future power distribution system. In the FRIENDS, new facilities called quality control centers (QCCs), which consist of power electronics devices, distributed generators (DGs), energy storage systems (ESSs), etc., are installed between distribution substations and customers. By controlling and operating those devices in QCCs adequately, various functions can be realized. Particularly, when a power supply from the transmission network is interrupted, isolated local networks which consist of some QCCs are composed in order to realize uninterruptible power supply. In the isolated local network, the DG and ESS in QCCs are employed as backup generators. This paper proposes a novel distributed and autonomous method for balancing the supply and demand during isolated operation. This paper also investigates the effectiveness of the proposed method through some computational simulations using PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

This paper explores the impact that different network access arrangements have on the capacity factor of non-firm wind generator connections to distribution networks. Active network management (ANM) projects are increasing in application in distribution networks as the need to integrate distributed generation becomes a more serious challenge. An important aspect of ANM is the contractual arrangement of the participating generation developer and network operator parties. These are sometimes referred to as “Principles of Access” (PoA) and deals with the rights of the generator when curtailment of generation output is required to maintain the network within its limits. Currently, a Last in First Off (LIFO) PoA is implemented in most U.K. ANM deployments and is the prevailing PoA in the Orkney ANM scheme. The Orkney network is used in this paper as a case study to analyze different PoA and compare the renewable energy capacity factor (CF) which result from these arrangements. The archival value of this paper is in the application of optimal power flow (OPF) to the PoA analysis challenge, in the quantification of the impact of previously identified PoA and in the conclusions drawn on the implications of different PoA choices for ANM schemes at the current early stage of ANM deployment. [ABSTRACT FROM PUBLISHER]

In this paper, a small signal model has been developed for a grid connected photovoltaic (PV)-diesel engine (DE) system feeding also to an induction motor at the low voltage level. The comprehensive mathematical model of the system has been developed by linearizing the system of equations around an operating point. To analyze the stability of the system, the eigen values and thus the modes of the system have been obtained from the resultant analytical A matrix. Further, to validate this small signal model, a complete nonlinear time-domain analysis of the system has been carried out. In order to enhance the stability of the system, a supplementary controller in the PV control loop has been proposed and its results have been verified both from the eigen values and from the nonlinear analysis. [ABSTRACT FROM PUBLISHER]

This paper presents a procedure for estimating the optimum allocation of distributed generation (DG) units in large distribution systems by using a multicore computing environment. The main goal of this work is to explore the application of a refined parallel Monte Carlo method for energy loss minimization in three-phase distribution systems when considering the intermittent nature of some distributed resources and the time varying shape of the loads. The procedure has been implemented in an open environment in which OpenDSS is driven from MATLAB. Some examples illustrate the scope of the proposed procedure. [ABSTRACT FROM AUTHOR]

Volatile voltage profiles in distribution systems caused by the fluctuating nature of renewable distributed generation (DG) are attracting growing concern. In this paper, we develop a new formulation of network reconfiguration to mitigate voltage volatility. It provides new insights into the voltage regulation problem in distribution systems with high renewable penetration, which is commonly addressed by power electronic controllers. From the linear DistFlow equations, we first propose a novel index that measures the voltage volatility of each bus in the system. This index is a function of distribution network parameters that characterizes the role of network structure in voltage volatility. Then, we formulate a new reconfiguration model that minimizes the network loss and restricts the voltage volatility indices with the coordination of switched capacitor banks. A Benders decomposition-based approach is designed to solve the problem using mixed-integer quadratic programming. The simulations on the IEEE 69-bus system show that the reconfiguration scheme is able to: first, minimize network loss when DG outputs are as predicted; and second, significantly reduce the risk of voltage violations when DG outputs deviate from the prediction. The proposed formulation unleashes the distinctive power of network reconfiguration in reducing voltage volatility, by which the cost of power electronic controllers can be saved. [ABSTRACT FROM AUTHOR]

Distribution system state estimation, which provides critical information for system monitoring and control, is being challenged by multiple sources of uncertainties such as random meter errors, stochastic power output of distributed generation (DG), and imprecise network parameters. This paper originally proposes a general interval state estimation (ISE) model to simultaneously formulate these uncertainties in unbalanced distribution systems by interval arithmetic. Moreover, this model can accommodate partially available measurements of DG outputs and inaccurate line parameters. Furthermore, a modified Krawczyk-operator algorithm is proposed to solve the general ISE model efficiently, and effectively provides the upper and lower bounds of state variables under coordinated impacts of these uncertainties. The proposed algorithm is tested on unbalanced IEEE 13-bus and 123-bus systems. Comparison with various methods including Monte Carlo simulation indicates that the proposed algorithm is many orders of magnitude faster and encloses tighter boundaries of state variables. [ABSTRACT FROM AUTHOR]

Power system planning is essential for ensuring development of a safe and stable power system. Articles on power system planning have been published in recent decades. In this paper, bibliometric analysis is applied to power system planning to identify its basic characteristics, and to summarize the research hotspots and trends. A total of 4562 publications were obtained from the Web of Science during 1971–2020. The 4562 publications cover 8136 keywords, 1526 journals, 107 countries/territories, and 2519 institutions. IEEE Transactions on Power Systems is the key journal in power system planning; USA, China, and England are the countries that dominate publication production. Research hotspots and trends were analyzed using author-keyword co-occurrence analysis and keyword burst detection. Four clusters were identified and topics from Cluster I (central nodes as power system stability and transient stability) and Cluster IV (central nodes as power system simulation and economics) are important for power system planning research. However, their relative popularities have declined over the past two decades. This indicates that Cluster II (central nodes as renewable energy, wind power, and energy storage) and Cluster III (central nodes as distributed generation and smart grids) will be the focus of future research. [ABSTRACT FROM AUTHOR]

Power losses estimation under time-varying distributed generation (DG) conditions usually demands several power flow simulations, which is a time-consuming task. To handle this issue, this paper proposes a method that uses the information of only one (base case) power flow to estimate the total power losses of distribution networks for any new DG condition. The method is based on the second-order power flow sensitivities, which are suitable to model the nonlinear nature of power losses. As a result, the method has the potential to speed up the solution of power losses reduction optimization problems, such as DG allocation problems, in which several DG configurations need to be considered. Moreover, a practical index is proposed to quantify the responsibility of each DG for the total power losses in a multi-DG scenario. The test results verified the validity of the proposed concept and method. [ABSTRACT FROM AUTHOR]

Planning distribution systems without considering the operation status of multiple distributed generation (DG) units could result in constraining the network, lowering the utilization of its assets and minimizing the total DG capacity that can be accommodated. In this paper, the impact of multiple DG configurations on the potential of active network management (ANM) schemes is firstly investigated. Secondly, the paper proposes a multi-configuration multi-period optimal power flow (OPF)-based technique (MMOPF) for assessing the maximum DG capacity under ANM schemes considering 1) variability of demand and generation profiles (multi-period scenarios), and 2) different operational status of DG units (multi-configurations). The results show that the availability of DGs at certain locations could critically impact the amount of DG capacity at other locations. If DGs are properly allocated and sized at certain locations up to the optimal limits, even with a “fit-and-forget” approach, the total connected DG capacity can be maximized, with minimum utilization of ANM schemes. However, exceeding these optimal limits may lead to minimizing the total DG penetration in the long term, impacting the system reliability due to the operational status of multiple DG units, and consequently, imposing more investments on ANM schemes to increase the amount of connected DG capacity. [ABSTRACT FROM AUTHOR]

This paper proposes a robust optimization approach for optimal operation of microgrids. The uncertain output variation of renewable energy sources (RESs) is addressed by collaboratively scheduling of energy storage (ES) and direct load control (DLC) through a two-stage complementary framework: an hour-ahead charging/discharging of ES and a quarter-hour-ahead activation of DLC. The objective is to maximize the total profit of the microgrid considering operation and maintenance costs of ES units, wind turbines and photovoltaics, and transaction with main grid and customer loads. Assuming the power output of RES randomly varies within a bounded uncertainty set, the problem is modeled to a two-stage robust optimization model and solved by a column-and-constraint generation algorithm. Compared with conventional operation methods, the ES and DLC are coordinated in different time-scales, and RES uncertainties are fully addressed during operation decision-making, ensuring the solutions to be optimal and robust for any realization of uncertainty. The proposed methodology is verified on the IEEE 33-bus distribution system through a wide range of different tests. [ABSTRACT FROM AUTHOR]

In this paper, a novel concept of Generalized Δ-circuit is proposed, that enables integration of distributed generators (DGs) based on contemporary technologies into the short-circuit calculations of large-scale distribution systems. Modern DG models, such as doubly fed induction generators (DFIGs) and three-phase inverter based DGs (IBDGs) differ from the classical synchronous and induction generator models. It is shown that their models cannot be integrated in traditional short-circuit calculation procedures because they include a large number of possible fault current control strategies. Therefore, the concept of Generalized Δ-circuit is proposed and allows for any control strategy implemented in modern DGs to be integrated in the short-circuit calculation procedure. An improved backward/forward sweep procedure is developed for calculation of the Generalized Δ-circuit state. The faulted system state is calculated by the superposition of the known prefault state and calculated Generalized Δ-circuit state. Results show that unlike previously developed online short-circuit calculations, the proposed method can handle DFIGs and IBDGs with arbitrary selected fault current control strategies. [ABSTRACT FROM AUTHOR]

This paper formulates a block-layer method for the reliability assessment of distribution systems. The characteristics of the method include: 1) identifying the impact of distribution component reliability on the system and load points using a block-layer structured assessment; 2) incorporating time-dependent failure parameters; and 3) taking account of the topological, seasonal, and meteorological features of the distribution systems under analysis. The proposed method first identifies the three critical parts of the distribution system: main supply, feeder, and secondary substation. It can also include reserve connections and distributed generation. Second, the method frames these parts into the layered structure, each corresponding to the zone of total load curtailment. To verify this reliability technique, this paper simulates distribution feeders assembled in a number of topologies and compares them with the state sampling technique. Data provided by the local utility company are processed to model the equipment and load for the base year. The results show that the proposed method can provide a wide range of partial and system indices. These values assist in the identification of parts of the distribution system and scenarios with low reliability and to determine possible remedial actions. [ABSTRACT FROM AUTHOR]

This paper proposes a series of new metrics for the reliability and economic assessment of microgrids in distribution system. These metrics include reliability parameters for a microgrid in the islanded mode, indices indicating distributed generation (DG) and load characteristics in the microgrid, microgrid economic indices, and customer based microgrid reliability indices. A two-step Monte Carlo simulation (MCS) method is proposed to assess the reliability and economics of a microgrid with intermittent DGs as well as the reliability of distribution system with microgrids. An application in IEEE-RBTS shows the effectiveness of the reliability and economic assessment technique with the proposed metrics, which can provide scientific and comparative information for the design and operation of microgrids. [ABSTRACT FROM PUBLISHER]

Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, provides restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is needed to perform optimally coordinated restoration that can achieve maximal restoration performance. This paper introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as a mixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder. [ABSTRACT FROM AUTHOR]

This paper presents a new methodology based on multiobjective optimization techniques to perform an optimized, coordinated, and selective allocation of control and protection devices in distribution networks with distributed generation (DG). The proposed mathematical model consists of two objective functions that consider economic issues and the network continuity index. Physical and operational constraints are taken into account, with emphasis on the set of constraints based on practical rules of distribution companies and international technical standards, which require the specification, coordination, and selectivity of the protection devices installed in the network. The possibility of load transfer from neighboring feeders and islanded DG operation is also considered. The proposed model is a mixed integer nonlinear programming, and we use NSGA-II (Nondominated Sorting Genetic Algorithm) to solve it. The proposed methodology is applied in a real 135-bus system found in the literature. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) can locally provide energies in distribution network and thus help to reduce the negative impact caused by large-scale electric vehicle (EV) charging demand. This paper proposes a two-stage robust DG investment planning model capable of accommodating uncertainty of EV charging demand and renewable generations. The DG investment location and size are optimized in the first stage and the distribution network operation feasibility in the worst case scenario is checked in the second stage to avoid constraint violations. The EV charging demand uncertainty is modeled by sampling from real-life scenarios of travel behavior. Finally, the column-and-constraint generation algorithm is adopted to solve the proposed problem. Simulations on modified IEEE 123-node distribution network demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper presents an analytical technique to evaluate the reliability of customers in a microgrid including distributed generations (DGs). Operators of the microgrid are responsible for a reliable energy supply to their customers. Due to the strategy of the priority on their customers, the restoration process of DGs should be reordered when system outage happens. The previous study has proposed the analytical technique to evaluate the reliability of customers in the distribution system that one operator owns all DGs. The proposed method includes photovoltaic (PV) systems and fuses, and the impact factor is modified to obtain the interruption cost. Also, equations are generalized to consider more than one component in a section. Case studies in RBTS Bus 4 verify that the accuracy of the proposed technique is comparable to that of MCS, and the configuration of system divided into several microgrids changes the reliability of customers in the microgrids. [ABSTRACT FROM AUTHOR]

This paper presents an analytical technique for evaluating the reliability of a distribution system, including distributed generation. Unlike the large-scale generation of the transmission system, distributed generation (DG) creates difficulties in evaluating reliability indices due to the complexity of the operation status. Explicit expressions for analyzing the reliability of distributed generation are proposed in this paper. The technique proposed includes the characteristics of DG, such as operation mode to mix peaking and standby modes and the failure of starting and DG itself. [ABSTRACT FROM AUTHOR]

This paper presents a multiperiod energy acquisition model for a distribution company (Disco) with distributed generation (DG) and interruptible load (IL) in a day-ahead electricity market. Assuming that cost information for individual generation companies (Gencos) and Discos is known, the Disco's energy acquisition strategy is modeled as a bilevel optimization problem with the upper subproblem representing individual Discos and the lower subproblem representing the independent system operator (ISO). The upper subproblem maximizes individual Discos' revenues. The lower subproblem simulates the ISO's market clearing problem that minimizes generation costs and compensation costs for interrupting load. The bilevel problem is solved by a nonlinear complementarity method. An 8-bus system is employed to illustrate the proposed model and algorithm. In particular, the roles of DGs and ILs to alleviate congestion are analyzed. [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]

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]

Active consumers will be integral to the future smart grid, scheduling their load and managing renewable generation in accordance with real-time pricing. The impact of spatially distributed renewable generation and active consumers on the distribution system must be quantified for operational planning. Most of the current studies are scenario-based and derived results are scenario specific. Determining the impact of spatially distributed active consumers with temporally variable behavior requires investigation of a large number of scenarios, which is computationally intractable using current iterative power flow algorithms. The objective of this work is to provide a new analytical method of voltage sensitivity analysis that allows for stochastic analysis of change in grid voltage due to change in consumer behavior (load and generation choices). This paper first derives an upper bound for change in voltage at a particular bus due to change in complex power at other buses in a radial distribution network. This bound is verified via simulations. Next, this bound is used to derive the probability distribution of voltage change at a bus due to random behavior of spatially distributed multiple active consumers. Results from the proposed probabilistic voltage sensitivity analysis is validated via traditional-scenario-based simulation of the IEEE 69 bus test system. [ABSTRACT FROM PUBLISHER]

Motivated by the fact that the location(s) and structural properties of the pinning node(s) affect the algebraic connectivity of a network with respect to the reference value, and thereby its dynamic performance, this paper studies the application of single and multiple pinning of distributed cooperative secondary control of distributed generators (DGs) in an islanded microgrid operation. It is shown that the selection of a pinning set based on the degree of connectivity and distance of leader DG(s) from the rest of the network improves the transient performance for microgrid voltage and frequency regulation. The efficacy of the distributed control strategy based on the proposed algorithms is illustrated via numerical results simulating typical scenarios for a variety of microgrid configurations. [ABSTRACT FROM AUTHOR]

Renewable distributed generation (DG) is likely to be actively controlled in future distribution networks to mitigate voltage issues resulting from high penetrations. This requires understanding the corresponding dependencies between voltage magnitudes and DG active/reactive power outputs. One approach to compute these dependencies is to use classical sensitivity methods such as those based on the Jacobian matrix inverse. However, updating the latter involves extensive remote monitoring. This paper presents a novel approach to produce voltage sensitivities applying the surface fitting technique on data based solely on the knowledge of network characteristics; making it suitable for decentralized DG control. To assess the benefits, comparisons with classical methods are carried out using the 16-bus UK GDS test network (1-min resolution simulations) considering a decentralized voltage control algorithm that simultaneously caters for the active and reactive power outputs of a single DG plant. The robustness of the proposed approach is also investigated considering changes in network parameters. Finally, the use of coordinated time delays is proposed to cater for multiple DG plants. Comparisons with a centralized optimization demonstrate that the combined use of the proposed voltage sensitivity approach and decentralized control algorithm is an effective and implementable candidate to actively manage renewable DG plants. [ABSTRACT FROM PUBLISHER]

Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point reliability. This growing proliferation, however, is changing the traditional consumption load curves by adding considerable levels of variability and further challenging the electricity supply–demand balance. In this paper, the application of microgrids in effectively capturing the distribution network net load variability, caused primarily by the prosumers, is investigated. Microgrids provide a viable and localized solution to this challenge, while removing the need for costly investments by the electric utility on reinforcing the existing electricity infrastructure. A flexibility-oriented microgrid optimal scheduling model is proposed and developed to coordinate the microgrid net load with the aggregated consumers/prosumers net load in the distribution network with a focus on ramping issues. The proposed coordination is performed to capture both inter- and intra-hour net load variabilities. Numerical simulations on a test distribution feeder with one microgrid and several consumers and prosumers exhibit the effectiveness of the proposed model. [ABSTRACT FROM PUBLISHER]

The existing three-phase imbalanced power flow calculation models for isolated micro-grid do not consider the non-smooth constraints such as voltage control limits and dead zone characteristics, which makes the power flow calculation results cannot meet the actual model constraints. In this paper, a more robust projected Levenberg-Marquardt (PLM) method is used to solve the problem after the non-smooth constraints are converted into smooth functions, which can reduce the model dependence on the initial values and solve the convergence problem caused by non-smooth constraints. The numerical experiments of micro-grid show that considering the non-smooth constraints can effectively improve the accuracy of power flow calculation. In addition, the PLM method has better convergence dealing with non-smooth constraints even poor initial value settings. [ABSTRACT FROM AUTHOR]

This paper presents an approach to deal with the uncertainty of generation and load in the optimal island partitioning of the automated radial distribution networks. The proposed approach is based on the concept of interval analysis, Relative Distance Measure (RDM) interval arithmetic, mixed integer linear programming with interval coefficients, and risk management tools. It defines a number of different island partitioning scenarios taking into account dependence (correlation) between loads and DGs. The best island partitioning scenario is obtained by employing the Minimal risk (Minimax) criterion for risk measurement. In this way, the presented approach provides a tool for a decision-maker to determine the island partitioning scenario that minimizes the risk of unsuccessful island operations in the uncertain environment. [ABSTRACT FROM AUTHOR]

The integration of volatile distributed energy resources (DERs) brings new challenges for the active distribution network maintenance scheduling (DN-MS). Conventionally, the DN-MS is formulated as a deterministic optimization model without considering the uncertainties of DERs. In this paper, the DN-MS is formulated as a multistage stochastic optimization problem, which is cast as a stochastic mixed-integer nonlinear programming model. It aims to reduce the total maintenance cost constrained by the reliability indices. To capture the operational characteristics of active distribution networks, the uncertainties of DERs and post-outage operation strategies of switching devices are incorporated into the model. In general, this type of model is intractable and mainly solved by heuristic search methods with low efficiency. Recently, Monte-Carlo tree search (MCTS) is emerging as a scalable and promising reinforcement learning approach. We propose a stochastic MCTS solution to this problem. In the tree search procedure, a sample average approximation technique is developed to estimate multistage maintenance costs considering uncertainties. To speed up the MCTS, the complicated constraints of the original problem are transformed to penalty or heuristics functions. This approach can asymptotically approximate the optimum with promising computation efficiency. Numerical test results demonstrate the superiority of the proposed method over benchmark methods. [ABSTRACT FROM AUTHOR]

The optimal management of energy generation/consumption in modern distribution systems has gained attention in the smart grid era. This paper presents optimized and coordinated strategies for performing and assessing energy management in multi-microgrid systems. The energy management process is formulated for multi-microgrid systems that simultaneously incorporate several energy generation/consumption units, including different types of distributed generators (DGs), energy storage units, electric vehicles (EVs), and demand response. Due to the probabilistic nature of some loads (e.g., EVs) and generators (e.g., wind turbine and photovoltaic (PV) modules), a novel probabilistic index is defined to measure the success of energy management scenarios in terms of cost minimization. Moreover, by using the new index, common types of energy controllers, such as DGs, storage units, EVs and demand side management are implemented simultaneously and individually, in a system, and the effect of each addition on the defined index and on operational costs is investigated. Finally, the robustness of the process to the load and generation prediction errors is investigated. [ABSTRACT FROM AUTHOR]

Investment in distributed generation (DG) is an attractive distribution planning option for adding flexibility to an expansion plan, mainly by deferring network reinforcements. In this first part of a two-part paper, a risk-based optimization approach is proposed to model a multistage distribution expansion planning problem that takes DG into account as a flexible option to temporarily defer large network investments. Five features of the installation of DG related to location, size, type, operation and timing are all optimized. The evolutionary particle swarm optimization (EPSO) method is applied to solve this mixed integer nonlinear problem. A return-per-risk index is proposed to assess expansion investments. This index achieves an efficient synergy between the expected return and the risk of investments by performing Monte Carlo simulations. In turn, the flexibility of network investment deferral is assessed through a real option valuation. Finally, in order to quantify the investment deferral benefit, the expected return from a traditional expansion plan (without DG) is compared to the return obtained from a flexible expansion plan (with DG). In the companion paper, the proposed approach is tested on a typical Latin American distribution network; implementation aspects and analysis of numerical results are presented. [ABSTRACT FROM PUBLISHER]

This paper proposes a method to evaluate the worth of installing renewable distributed generation (DG) in distribution networks. Moreover, the work optimally allocates these DG units in the distribution network to maximize the worth of the connection to the local distribution company (LDC), as well as the customers connected to the system. The proposed methodology helps the LDC to better assess the benefits of the renewable DG units' proposed connections and to identify the optimal buses on which to connect these DG units. The benefits considered in this paper are deferral of upgrade investments, reduction of the cost of energy losses, and reliability improvement, which is represented by the interruption cost reduction. The proposed methodology takes into consideration the uncertainty and variability associated with the output power of renewable DG as well as the load variability. The planning problem of determining the optimal location and sizes of DG units is defined as multi-objective mixed integer programming. [ABSTRACT FROM PUBLISHER]

In this paper, a modeling technique for small-signal stability assessment of unbalanced power systems is presented. Since power distribution systems are inherently unbalanced, due to its lines and loads characteristics, and the penetration of distributed generation into these systems is increasing nowadays, such a tool is needed in order to ensure a secure and reliable operation of these systems. The main contribution of this paper is the development of a phasor-based model for the study of dynamic phenomena in unbalanced power systems. Using an assumption on the net torque of the generator, it is possible to precisely define an equilibrium point for the phasor model of the system, thus enabling its linearization around this point, and, consequently, its eigenvalue/eigenvector analysis for small-signal stability assessment. The modeling technique presented here was compared to the dynamic behavior observed in ATP simulations and the results show that, for the generator and controller models used, the proposed modeling approach is adequate and yields reliable and precise results. [ABSTRACT FROM PUBLISHER]

In designing procedure of a power sharing controller for a voltage source converter (VSC)-based microgrid with no communication link, three issues should be considered. Firstly, in VSC-based microgrids, which use droop controller method, the desired frequency of VSCs is altering regarding the output active power. Consequently, the conventional load frequency control techniques are inappropriate since their operation is based on a fixed pre-specified desired frequency. Secondly, to prevent circulating current and thermally overstressing, all DGs should participate in active power supply. In addition, since there is no communication link, the steady state value of each micro-source active power is unknown. Therefore, the conventional fixed active power control method for DGs is not appropriate. Thirdly, when the microgrid loads are increased, the output power of VSCs is increased rapidly; however, the output power of each VSC's primary source could not change in the same rate to respond. It causes the DC voltage of VSCs to decrease, which could affect the appropriate performance of VSCs. In this paper, a novel control strategy for VSCs and an energy storage system in a VSC-based microgrid without communication link accompanied with a novel hybrid model of VSC-based DGs, which considers primary source effect, is proposed. [ABSTRACT FROM PUBLISHER]

In deregulated power systems, the distribution network operator (DNO) is not responsible for investment in distributed generation (DG) units, and they are just concerned about the best architecture ensuring a good service quality to their customers. The investment and operating decisions related to DG units are then taken by entities other than DNO which are exposed to uncertainty. The DNO should be able to evaluate the technical effects of these uncertain decisions. This paper proposes a fuzzy evaluation tool for analyzing the effect of investment and operation of DG units on active losses and the ability of distribution network in load supply at presence of uncertainties. The considered uncertainties are related to load values, installed capacity, and operating schedule of DG units. The proposed model is applied on a test system and also a real French urban network in order to demonstrate its functionality in evaluating the distribution expansion options. [ABSTRACT FROM PUBLISHER]

This paper presents a new paradigm for distribution system operation in the presence of distributed generation (DG) sources taking into consideration the goodness factor of the DG units. The proposed concept of goodness factor of DG units is based on the computation of the incremental contribution of a DG unit to distribution system losses. The incremental contributions of a DG unit to active and reactive power losses in the distribution system are termed as the active/reactive incremental loss indices (ILI). The goodness factors are integrated directly into the distribution system operations model, which is based on an optimal power flow (OPF) framework. This model seeks to minimize the distribution company's (disco's) energy costs in the short term taking into account the contribution (goodness factor) of each DG unit. Two scenarios are considered in the paper: the first scenario considers the disco to be the owner of the DG units and hence is responsible for their scheduling and dispatch, and the second scenario considers the DG units to be investor-owned. The analysis was carried out considering an 18-bus distribution network extracted from the well-known IEEE 30-bus system and a 69-bus distribution system. [ABSTRACT FROM AUTHOR]

Variability in power generation at multiple consumer-owned renewable energy sources can cause random voltage fluctuations, which may result in voltage violations at multiple nodes in a power distribution system. Traditional methods of voltage control are ineffective to address fast voltage variations. New dynamic methods of voltage control using end-user devices can significantly benefit from the knowledge of the dominant influencer of voltage fluctuation (DIVF). This paper introduces information theoretic metrics to identify DIVF for every node in the power distribution system. A node can be DIVF due to its location in the distribution system and its capacity to generate and change its power. Use of traditional power flow algorithms to identify the DIVF is computationally complex, which limits their use in real-time applications. In this paper, information theoretic indicators of the DIVF are computed analytically in a computationally efficient manner, and their effectiveness to identify the DIVF is tested using the IEEE 69 node test system. From simulations, it is shown that differential entropy, Kullback–Leibler distance, and Frechet distance are effective indicators of the DIVF and can successfully identify the most influential nodes providing the foundation for intelligent voltage control. [ABSTRACT FROM AUTHOR]

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the installation of both feeders and substations reinforcement and DG integration at different times are considered in the formulation of a minimum cost distribution systems reinforcement strategy problem. An application on a medium size network, hypothesizing a scenario of reinforcement also using as DG gas micro-turbines, is carried out using a novel optimization technique allowing the identification of optimal paths in trees or graphs. The proposed technique is the Dynamic Ant Colony Search algorithm. [ABSTRACT FROM AUTHOR]

This paper shows that the current an inverter interfaced distributed generator (IIDG) contributes to a fault varies considerably, due mainly to fast response of its controller. This paper proposes a method to extend the conventional fault analysis methods so that IIDG contribution can be estimated in the fault analysis. The proposed method gives rms profiles of the fault currents of interest (IIDG contribution and the fault currents the protective device will see). Test results, based on a prototype feeder, show that the proposed approach can estimate the fault current's contributions under both balanced and unbalanced fault conditions. [ABSTRACT FROM AUTHOR]

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

This paper proposes a unified distributed control strategy for DC microgrid operating modes, without bus voltage signaling or mode detection mechanisms that are normally required for decentralized control strategies. The proposed control strategy is based on the novel integration of distributed controllers for energy balancing between DC microgrid energy storage systems with distributed controllers used to regulate the average DC microgrid bus voltage, and a new method for controlling the grid connected rectifier that maintains the distributed control structure. Under the proposed control strategy, seamless mode transitions are achieved between qualitatively different operating modes, namely, 1) grid connected operation with the rectifier providing load balancing, 2) grid connected operation with the rectifier charging the energy storage systems, and 3) islanded operation. In all operating modes, the average DC microgrid bus voltage is regulated to the microgrid voltage reference, and the energy storage systems are controlled independently of the operating mode to achieve and maintain a balanced energy level. Simulations are presented demonstrating the performance of the proposed control strategy for a 380 VDC datacenter with intermittent photovoltaic generation and communication delays expected from a WiFi control network implementation. [ABSTRACT FROM AUTHOR]

This paper proposes a vehicle-to-grid reactive power support (V2GQ) strategy for optimal coordinated voltage regulation in distribution networks with high distributed generation (DG) penetration. The proposed algorithm employs plug-in electric vehicles (PEVs), DG, and on-load tap changer (OLTC) to satisfy PEV charging demand and grid voltage requirements with relaxed tap operation, and minimum DG active power curtailment. The voltage regulation problem is formulated as a nonlinear programming and consists of three consecutive stages, in which successive stages apply the outputs of their preceding stages as constraints. The first stage aims to maximize the energy delivered to PEVs to assure PEV owner satisfactions. The second stage maximizes the DG extracted active power. Third stage minimizes the voltage deviation from its nominal value utilizing the available PEV and DG reactive powers. The main implicit objective of the third stage problem is relaxing the OLTC tap operation. In addition, the conventional OLTC control is replaced by a proposed centralized controller that utilizes the output of the third stage to set its tap position. Real-time simulations are developed to demonstrate the effectiveness of the proposed optimal coordinated algorithm on a typical distribution network using OPAL-RT real-time simulator (RTS) in a hardware-in-the-loop (HIL) application. [ABSTRACT FROM PUBLISHER]

This paper addresses the multistage expansion planning problem of a distribution system where investments in the distribution network and in distributed generation are jointly considered. Network expansion comprises several alternatives for feeders and transformers. Analogously, the installation of distributed generation takes into account several alternatives for conventional and wind generators. Unlike what is customarily done, a set of candidate nodes for generator installation is considered. Thus, the optimal expansion plan identifies the best alternative, location, and installation time for the candidate assets. The model is driven by the minimization of the net present value of the total cost including the costs related to investment, maintenance, production, losses, and unserved energy. The costs of energy losses are modeled by a piecewise linear approximation. As another distinctive feature, radiality conditions are specifically tailored to accommodate the presence of distributed generation in order to avoid the isolation of distributed generators and the issues associated with transfer nodes. The resulting optimization problem is a mixed-integer linear program for which finite convergence to optimality is guaranteed and efficient off-the-shelf software is available. Numerical results illustrate the effective performance of the proposed approach. [ABSTRACT FROM AUTHOR]

In traditional distribution system, power flow was unidirectional; thus loads were usually aggregated into the substation as an equivalent constant bus in the original risk analysis of transmission system. Detail structures of the distribution system were absolutely ignored. However, distribution system is transformed from passive to active nowadays with more and more distributed generations (DGs) being integrated into it. So, distribution system not only can be considered as loads but also can be considered as virtual power plants to supply power to local loads and even to send power back to the transmission system sometimes. In this paper, a hierarchical method is presented to evaluate the impact of role changing of the distribution system in power system risk assessment. In the study, DGs can supply critical loads in distribution system through re-dispatching after some contingency happens. Discrete probability model is employed to simulate the intermittent output of DGs. Available supply capacity (ASC) is used as a general constraint to guarantee the security level of distribution system that needs high reliability. Also, an iterative calculation between transmission system and distribution network is adopted to derive the risk indices with considering detail structures of the active distribution network. Further, impact of some factors on system risk calculation, such as DGs' capacities, dispersions, locations, and component outage probabilities, are discussed. Finally, correctness and effectiveness of the proposed method are validated by a modified IEEE RTS and RBTS system. [ABSTRACT FROM PUBLISHER]