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Harmonic power flow simulation is the main method to deduce and evaluate the steady-state harmonic content of urban rail flexible traction power supply system (FTPSS). The AC power quality of FTPSS can be optimized by conducting harmonic power flow simulation. However, traditional modeling and simulation methods are inefficient, so that it is difficult to achieve the real-time and accurate deduction of the harmonic power flow. Therefore, a high precision real-time simulation method of harmonic power flow based on multi-layer perceptron (MLP) is proposed in this paper. Firstly, the harmonic model of fully controlled converter is established by adopting MLP, which reduces the complexity of the model and improves the efficiency of harmonic calculation. Subsequently, the high precision data samples are used for the regression training of MLP model to ensure the accuracy of harmonic calculation. Moreover, the high precision real-time simulation of harmonic power flow is realized through the synchronous and interactive solution of MLP model and power flow model. Finally, theoretical analysis and simulation are conducted. The results demonstrate that the steady-state harmonic calculation time of the MLP model is significantly reduced to merely 1.02% of the traditional mechanism model's duration, which enables the harmonic power flow simulation to be effectively integrated into real-time system applications. In addition, the RMSE of the MLP model is only 0.0147, indicating the accuracy of the real-time simulation. The method proposed in this paper can quickly and precisely calculate the harmonic power flow, which is of practical value for harmonic evaluation and optimization of FTPSS. [ABSTRACT FROM AUTHOR]

• Analysis of traction power supply system is conducted considering cross-bonding cable. • Model simplification method based on multiport network hybrid parameters is designed. • The calculation difference of loss before and after consideration is more than 10 %. • Cross-bonding cables should be set near the position with large train power. The urban rail transit traction power supply system adopts DC power supply. The upstream and downstream rails are generally connected by cross-bonding cables at intervals, so as to decrease the rail equivalent resistance and reduce the rail potential and loss. The existing modelling methods for power flow calculation do not consider the influence of cross-bonding cables due to the complexity of modelling, which causes some deviations in the calculation results. Hence, a modelling method for power flow calculation of urban rail transit traction power supply system considering cross-bonding cables is proposed in this paper. Firstly, the influence of cross-bonding cables on power flow model is analyzed. Subsequently, a model simplification method based on multiport network hybrid parameters is designed. Finally, power flow calculations considering cross-bonding cables are carried out with a metro line. The calculation results show that the calculation difference of traction network loss before and after consideration is more than 10 %. Moreover, this paper analyzes the influence law of the setting of cross-bonding cables on the power flow state, and gives some suggestions on the setting in actual engineering application. [ABSTRACT FROM AUTHOR]

• A new control method for DER is suggested. • The proposed control method balances the load between feeders. • DER connects to feeder through SST. • DER-controlled circuit shared the load between two feeders like ring connection. • Voltage profiles are improved. The multi-purpose use of distributed energy resources (DER) can bring a lot of income to its owners. For example, the load imbalance of the radial feeders in the distribution network is an old problem that occurs due to the simple structure of the radial topology and the unidirectional power flow in traditional networks. With emerging DERs and the development of power electronic technology, previous concepts are changing continuously. This paper aims to balance the load between two feeders whilst, it yields better voltage profiles and more appropriate utilization of distribution feeders. This paper proposes a new control method for DERs (including PV panels plus battery storage) that makes the radial system pretends a ring topology properties. It is done with the help of a solid-state transformer (SST). The relationships of the DER current controller are formulated based on current passes through the ring connection. Case studies are carried out on improved IEEE 33-node and 13-node systems with DERs and SSTs. The results show that the suggested control method can simulate the real ring topology and operating objective namely, load balancing is reached. [ABSTRACT FROM AUTHOR]

Modern distribution systems with high penetration of distributed energy resources face multiple sources of uncertainty. This transforms the traditional Optimal Power Flow problem into a problem of sequential decision-making under uncertainty. In this framework, the solution concept takes the form of a policy , i.e., a method of making dispatch decisions when presented with a real-time system state. Reasoning over the future uncertainty realization and the optimal online dispatch decisions is especially challenging when the number of resources increases and only a small dataset is available for the system's random variables. In this paper, we present a data-driven distributed policy for making dispatch decisions online and under uncertainty. The policy is assisted by a Graph Neural Network but is constructed in such a way that the resulting dispatch is guaranteed to satisfy the system's constraints. The proposed policy is experimentally shown to achieve a performance close to the optimal-in-hindsight solution, significantly outperforming state-of-the-art policies based on stochastic programming and plain machine-learning approaches. • We present a data-driven distributed policy for decisions in a distribution system. • The decisions are made online and under uncertainty. • Decisions are assisted by a Neural Network but satisfy system constraints. • The policy performs close to the optimal, outperforming state-of-the-art policies. [ABSTRACT FROM AUTHOR]

This paper first designs a holistic coordination framework between transmission system operator (TSO) and distribution system operators (DSOs) to modernize traditional top-to-down (from transmission system to distribution systems) power flexibility provision mechanism to a bi-directional power flexibility provision mechanism between TSO and DSOs. More specifically, it empowers TSO and DSOs to exchange both active and reactive power flexibility without having to reveal their confidential grids data. Above all, it allows TSO to take advantage of the potential active and reactive power flexibility of the proliferating number of distributed energy resources (DERs) installed in distribution systems. Secondly, it develops a linearized power flow model for transmission networks. Leveraging the designed framework along with the developed linearized power flow model, it finally offers a two-stage linear stochastic optimization method to help TSO optimally book its required active and reactive power flexibility from both power plants and distribution systems. In particular, it considers constraints and active/reactive power losses of the transmission network. The performance of the proposed framework is evaluated considering a real-world transmission network, i.e. the Swiss transmission network. • It designs a holistic TSO–DSO coordination framework where TSO and DSOs establish their collaboration on the basis of the FPC areas. This framework facilitates the TSO and DSO collaboration, thereby, boosting unlocking the potential active/reactive power flexibility of DERs. • It develops a decision making tool for TSOs to help them optimally book their required active and reactive power flexibility via FPC areas. Leveraging a linearized AC power flow model, it is able to account for grid's active and reactive power losses and, most notably, the nodal voltage magnitude constraints. Therefore, it can ensure that power plants accomplish their voltage regulation task against all uncertainties and contingencies without reaching their maximum/minimum reactive power limits. Accordingly, it helps TSOs steer their grids far from risks associated with under-voltage/over-voltage issues triggering voltage collapse. • It allows TSO to take advantage of all existing power flexibility resources including dispatchable power plants and DERs located in distribution networks. • It follows the sequential energy and flexibility market structure, thus, it is a tailored tool for most of European TSOs. • It evaluates the efficiency of the developed framework and decision making tool on a real-world transmission network, i.e. the Swiss transmission network operated by Swissgrid. [ABSTRACT FROM AUTHOR]

• Linear OPFs are requested for the most recent challenges of distribution systems. • Traditional linear OPFs for distribution grids do not manage closed-loops and OLTCs. • Linear OPF can be improved to manage modern distribution system challenges. • Improved OPF preserves accuracy and numerical performance of the traditional one. • Stability and scalability properties of improved linear OPF are experimented. Modern distribution systems face new challenges due to the rise of small-scale renewable energy resources and the electrification of energy demand. Additionally, the complexity of network management increases with the exchange of flexibility services between distribution and higher voltage levels. The system operator's role involves optimizing the planning and operation of the distribution network. In current scenarios, this includes managing flexibility resources (such as generators, demand response, and on-load tap changers) and implementing new operating strategies (such as closed-loop topologies and dynamic reconfiguration). This paper proposes a reformulation of one of the most used linear approximations of the Optimal Power Flow model for distribution networks. The novelty of this reformulation lies in integrating equations to handle tap-changing transformers with closed-loop/meshed network operation, while preserving the original linear formulation and computational tractability. [ABSTRACT FROM AUTHOR]

This paper uses convex inner approximations (CIA) of the AC power flow to tackle the optimization problem of quantifying a 3-phase distribution feeder's capacity to host distributed energy resources (DERs). This is often connoted hosting capacity (HC), but herein we consider separative bounds for each node on positive and negative DER injections, which ensures that injections within these nodal limits satisfy feeder voltage and current limits and across nodes sum up to the feeder HC. The methodology decomposes a 3-phase feeder into separate phases and applies CIA-based techniques to each phase. An analysis is developed to determine the technical condition under which this per-phase approach can still satisfy network constraints. New approaches are then presented that modify the per-phase optimization problems to overcome conservativeness inherent to CIA methods and increase overall HC, including selectively modifying the per-phase impedances and iteratively relaxing per-phase voltage bounds. Discussion is included on trade-offs and feasibility. To validate the methodology, simulation-based analysis is conducted with the IEEE 37-node test feeder and a real 534-node unbalanced radial distribution feeder. [ABSTRACT FROM AUTHOR]

Recently, online feedback optimization (OFO) emerges as a promising approach for real-time distribution grid management. OFO offers several advantages, including not requiring precise grid models or real-time load metering and demonstrating robustness against inaccurate problem data. However, one important limitation is that OFO does not consider the intertemporal relationships and short-term planning capabilities of assets, thus not harnessing the full potential of a variety of distributed energy resources (DER) such as batteries and electric vehicles. To address this limitation, this paper proposes a multi-timescale coordinated control framework. In the slower timescale, local optimization problems are solved to provide real-time OFO controllers with reference setpoints. The overall approach thereby maintains minimal model, computation, and communication requirements while enforcing grid limits. Case studies based on a 96-bus unbalanced low-voltage grid with a high DER penetration level and second-scale data demonstrate its effectiveness and solution quality benchmarked with a centralized optimal power flow approach. • Combining local optimization with online feedback optimization. • Real-time control of distributed energy resources with intertemporal relationships. • Offline optimization provides online optimization reference setpoints. • Reduced PV curtailment compared to benchmark ideal optimal power flow. • Efficient utilization of existing distribution grid capacities. [ABSTRACT FROM AUTHOR]

This paper discusses the modeling of inverters used in distributed energy resources in steady state. Modeling the interaction between distribution grids and inverter-based resources is crucial to understand the consequences for the network's operational and planning processes. This work highlights the limitations of existing models and emphasizes the need for better representations of inverters and their control laws in decision-making contexts. Improved steady-state grid-following and grid-forming inverter models are presented, including both three-leg and four-leg converter variants. The advantages of these improved models in mathematical optimization contexts are showcased by investigating the power quality improvement capabilities of the inverters. Numerical studies integrating the proposed inverter models in a four-wire unbalanced optimal power flow engine are presented, and trade-offs between modeling detail and computational intensity are illustrated. • Review of algebraic inverter models and formulation improvements. • Derive (algebraic) nonlinear programming models for both the inverters and control laws, and perform numerical experiments through IPOPT [10]. • Demonstrate the integration of these models into unbalanced optimal power flow engines, up to four-wire [11]. • Illustrate how inverter model approximations can lead to sub-par decisions. [ABSTRACT FROM AUTHOR]

This paper proposes an uncertainty modeling method for the aggregated power flexibility of DERs. Basically, both outer and inner approximated power-energy boundary models are utilized to describe the aggregated flexibility of controllable DERs. These power and energy boundary parameters are uncertain because the availability of controllable devices, such as electric vehicles and thermostatically controlled loads, cannot be precisely predicted. The optimal operation problem of the aggregator is thus formulated as chance-constrained programming (CCP). Then, a flexibility envelope searching algorithm based on the ALSO-X+ method is proposed to solve the CCP, the result of which is a conservative approximation of the original CCP but not as conservative as the Conditional Value-at-Risk approximation. After optimizing the aggregated power of the group of DERs, the decision at the aggregator level is disaggregated into the flexibility regions of individual DERs. Finally, the numerical test demonstrates the effectiveness and robustness of the proposed method. • Uncertainty modeling of the aggregated flexibility of DERs. • Chance constraint approximation based on the ALSO-X+ approach. • Comparative analysis of costs, risk levels, and feasibility with Conditional Value at Risk. • Comparison between the outer and inner approximated flexibility aggregation models. [ABSTRACT FROM AUTHOR]

Although several approaches have been proposed in the literature to utilize inverter-based distributed energy resources (DERs) in the secondary frequency control (SFC), challenges related to practically implementing SFC with inverter-based DERs have not been considered. These challenges include response time of DERs, the communication environment, and emulation of the actual Automatic Generation Control (AGC). This paper develops and implements a coordinated operation and control for below the substation resources such as inverter-based DERs and a utility-scale battery energy storage system (USBESS) to participate in the secondary frequency control. A linearized optimization problem is formulated to simultaneously determine optimal setpoints of participating resources and satisfy AGC requests in real time for the secondary frequency control. To mimic the actual process of AGC, a hardware- and software-in-the-loop-based experimental setup is developed with the integration of real-time digital simulators (RTDS), a centralized controller at the substation, and gateways as IoT devices, which are commonly used in practice to interface DERs to control and monitoring systems. The controller remains in listening mode until it receives an AGC signal. When it receives an AGC signal, it optimally dispatches the USBESS and DERs and monitors the change in power flow at the substation. The controller iteratively dispatches the participating resources considering their response time until the AGC request is satisfied. The proposed control is implemented on an actual feeder configuration located in Las Vegas, Nevada, in collaboration with NV Energy—the largest public utility in Nevada. The results illustrate that USBESS and DERs can be coordinated and dispatched to satisfy AGC requests for SFC. • Novel linearized optimization-based secondary frequency controller • High fidelity prototype for practical implementation of AGC on real system • Combined hardware-and software-in-the-loop-based real-time laboratory setup for AGC [ABSTRACT FROM AUTHOR]

To ensure the continuous operation of a microgrid, proactive planning is essential, especially when contemplating possible dynamic events that alter the scheduled scenarios for the islanded operation or during its transition from connected to islanded mode. This paper introduces an innovative mathematical programming model for the AC optimal power flow (AC-OPF) with dynamic security constraints (DSCs), considering two scenarios: the islanded operation and the transition. This model uses positive-sequence equations to represent the inverter-based resources (IBRs) for grid-forming and grid-following roles, along with a fourth-order synchronous generator model equipped with excitation and frequency control systems. They assess the dynamic response to specific events such as short-circuits, decreases in PV generation, increases in load demand during the islanded operation, and the transition itself. The DSCs are applied to dispatchable distributed energy resources (DERs), which react to variations in the microgrid, considering generation and opportunity costs to minimize the discrepancy between planned and secure operating points. The mathematical programming model is implemented using AMPL, and solutions are obtained through the nonlinear optimization solver IPOPT. The tests are conducted in an adapted version of the microgrid being developed at the University of Campinas that includes a synchronous generator, photovoltaic (PV) generation, and a battery energy storage system (BESS). Results demonstrate the model's effectiveness in adjusting generation dispatch to withstand defined events and optimizing generation resources, even when limits are not reached. [ABSTRACT FROM AUTHOR]

Active distribution networks integrate distributed energy resources into traditional power grids, mainly guided by the intention of addressing climate change concerns. However, integrating distributed energy resources has introduced several challenges for traditional overcurrent protection, including variations in pre-fault and fault current magnitudes and bidirectional power flows. These challenges make it difficult to guarantee reliable protection of active networks in grid-connected and islanded modes. In response to the challenges posed by these new networks, this paper presents an adaptive protection approach that leverages local measurements and data clustering to identify the network operating states accurately. In this approach, reference relay coordination is obtained by considering all distributed energy resources that supply the network during the grid-connected operating state, providing optimal settings for each relay. Next, based on the current operating state, the adaptive relay pickup current is estimated based on local measurements, which is used to adjust the time dial setting of each directional overcurrent relay. The proposed approach is contrasted with the conventional relay, considering several operating states, including DER switching, grid-connected, and islanded modes, for single-phase and three-phase faults and several fault resistances, using the IEEE 34-node test feeder. The results demonstrate the proposal's high performance in avoiding relay miscoordination. Finally, the proposed approach is also simple and suitable for immediate implementation in existing digital relays, as it has a low computation burden and does not require communication systems. • Proposes an approach for communication-less adaptive protection to update the relay settings adequately. • The approach detects the ADN OS originated by the connection/disconnection of DERs, starting from a reference case and using clustering and classification approaches. • The relay parameters are online estimated from the local pre-fault current and voltage measurements. • The proposed solution does not use a centralised computation scheme. • The protection approach uses straightforward computation, resulting in a low computational burden. [ABSTRACT FROM AUTHOR]

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. In this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations. • Bilevel optimization minimizes number of sensors capturing all voltage violations. • Conservative linear approximations tackle power flow nonlinearities. • MILP reformulation proves tractable across various test cases. • Post-processing minimizes false alarms, validated through testing. [ABSTRACT FROM AUTHOR]

With the growing adoption of renewable energy resources in the power grid, co-optimizing the operation of water and power distribution networks (WDNs and PDNs) increases the flexibility of both systems. The optimal water power flow problem (OWPF) is formulated to manage resource utilization across the WDNs and multi-phase PDNs. The nonlinear WDN hydraulic constraints and PDN ac power flow equations render the OWPF problem nonconvex. This paper formulates a convex optimal water power flow (C-OWPF) problem adopting successive approximations in WDNs and branch-flow relaxations in PDNs. The C-OWPF problem is a mixed-integer semidefinite program, which is computationally challenging even for small instances. Additionally, privacy considerations of WDN and PDN operators motivate the need for solving the C-OWPF in a distributed fashion. This paper develops a C-OWPF solver based on Benders decomposition that overcomes computational complexity challenges and preserve the privacy of the respective operators. The merits of the Benders decomposition-based solver are demonstrated on the IEEE 4-bus PDN coupled with a 3-node WDN and the IEEE 123-bus PDN coupled with the 36-node WDN. • Optimal pump scheduling in multi-phase distribution networks is studied. • Monomial approximations for water flow hydraulics are considered. • SDP relaxations and approximations for power flows are compared. • Optimal reactive power dispatch for PV inverters is included. • A novel multi-period optimization method is put forth via Benders' decomposition. [ABSTRACT FROM AUTHOR]

• Data and simulation analysis on a real and large-scale distribution power grid. • Introduction of three charging scenario to analyse the impact of EV. • 20 % EV penetration with uncoordinated charging causes congestion. With the considerable increase of Distributed Energy Resources (DER), reliable and cost-effective operation of distribution grids becomes challenging. The efficient operation relies on computationally dependable and tractable optimisation solvers, which may handle: 1) non-linear AC power flow constraints, and 2) time-linking variables and constraints and objectives of DER, over the operational horizon. In this paper, we introduce an application of a high-performance MultiPeriod AC Optimal Power Flow (MPOPF) solver, called "BATTPOWER", to simulate active distribution grids for a near-future scenario. A large-scale Norwegian distribution grid along with a large population of Electric Vehicles (EV) are here taken as the case-study. We suggest and analyse three operational strategies (in terms of control of charge scheduling fleet of EV) for the Distribution System Operator (DSO): (a) uncoordinated charge scheduling, (b) coordinated charge scheduling with the objective of energy cost-minimisation without operational constraints of the grid, and (c) coordinated charge scheduling with the objective of energy cost-minimisation along with the operational constraints of the grid. The results demonstrate that the uncoordinated charging would lead to: 1) overloading of lines and transformers when the share of EVs is above 20%, and 2) higher operational costs than the proposed control strategies of (b) and (c). In strategy (b) operational line/transformer limits are violated when the populations of EVs are growing above 36%. This implies that current market design must be altered to allow active control of a large proportion of DERs within grid operational limits to achieve cost minimization at system level. To our knowledge, the work presented in this paper is the first ever attempt to do a comprehensive analysis of the impact of EV charging demand on a real Norwegian distribution grid. Moreover, the inference of the analysis says that the Norwegian distribution networks are more prone to congestion problems than the voltage problems for the EV demand which includes a smart charging scheme accounting for grid conditions. [ABSTRACT FROM AUTHOR]

• A novel stochastic-robust approach is developed for energy communities. • Individual and collective assets are considered and analysed. • The problem is solved using a novel three-stage procedure. • Operating cost is incremented 77$ when the degree of robustness grows. • Collective storage systems help to reduce unserved demand and wasted generation. This paper presents an extended model for aggregation of operational settings of droop-controlled Distributed Energy Resources (DERs) in Microgrid (MG) planning, thus deriving in a novel problem named Optimal Siting, Sizing and Setting (OSSS) of DERs. The proposed approach precisely deals with the power flow formulation for autonomous MG as an essential constraint for accurate results. Furthermore, the proposed OSSS model considers the frequency and voltage dependence characteristic of loads. The problem casts in multi-objective formulation to consider different technical, power quality and controlling aspects. This will help the designer to provide efficient decision for allocation of DERs. The effects of realistic load model as well as power sharing error index are elaborately investigated in simulation results. The model is thus further validated and its usefulness demonstrated. Finally, the performance of multi-objective OSSS model is verified by comparing the results with the previous simplified models presented in the recently published literatures. [ABSTRACT FROM AUTHOR]

• The proposed method derives a non-iterative holomorphic embedding load flow method (HELM) for area interchange control in the multi-area interconnected system. • Based on the participation factor of each regulating bus, all of the generators can take part in the adjustment even though only one variable is added for each control area. • The proposed approach is compared with the conventional NR approach by studying cases on the 4-bus system, IEEE 118-bus system, the Polish 3012-bus system and 25,000-bus system under different operating conditions. • The results show that the proposed approach is superior to the conventional NR approach in terms of computation efficiency in small and midsize system. This paper proposes a new approach to realize area interchange control based on the non-iterative holomorphic embedding load flow method (HELM) in a multi-area interconnected system. In this approach, the area interchange equations are firstly incorporated into the power flow equations and then the extended power flow equations are embedded by holomorphic functions. Furthermore, the adjustable generators participating in automatic generation control are considered as active power resources to control interchange among areas. A participation factor matrix is integrated into the HELM to distribute active power injections among multiple adjustable generators. To evaluate the performance of the proposed approach, comparative studies were conducted on various power systems, including the 4-bus system, IEEE 118-bus system, Polish 3012-bus system, and 25,000-bus system, under diverse operating conditions. The obtained results demonstrate the effectiveness and computational efficiency of the proposed non-iterative area interchange formulation in small and midsize power systems, in comparison with traditional iterative methods such as Newton's method. However, for large-scale systems, further improvements in computational efficiency and convergence performance are required. [ABSTRACT FROM AUTHOR]

• Random-fuzzy multi-objective optimal power flow. • Transmission and distribution interaction. • Security region constraints. In order to deal with the static voltage stability region problem of the power system caused by the penetration of distributed energy resources, this paper presents an interactive random-fuzzy optimal power flow method for transmission-distribution network considering security region constraints. Firstly, based on the random-fuzzy theory, the output of wind power and multi-energy coupling energy hub connected to transmission-distribution network are obtained. On this basis, the security region model of transmission-distribution network is established. As the interaction and cooperation between multiple distribution networks and transmission network throughout the system are described, the global random-fuzzy model of transmission-distribution interaction is established. Then, the security domain opportunity constraints are incorporated into the multi-objective optimization model of transmission-distribution network. Finally, based on the improved IEEE30 bus transmission system and IEEE33 bus distribution system, the power flow of transmission-distribution interactive network under the proposed model is calculated. The simulation results validate the effectiveness of the proposed model and algorithm. The safe operation distance of the power grid system can be improved and the active power network loss and power generation cost can be reduced. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a rule based comprehensive approach to study distribution network reconfiguration (DNRC). The DNRC model with line power constraints is set up, in which the objective is to minimize the system power loss. In order to get the precise branch current and system power loss, a power summation based radiation distribution network load flow (PSRDNLF) method is applied in the study. The rules that are used to select the optimal reconfiguration of distribution network are formed based on the system operation experiences. The proposed rule based comprehensive approach is implemented in distribution network in Guiyang South Power Supply Bureau. For the purpose of illustrating the proposed approach, two distribution network systems are tested and analyzed in the paper. [Copyright &y& Elsevier]

Abstract: Reconfiguration involves changing the status (OFF/ON) of switches, and reconfiguration for restoration involves changing the switch status to maximize the supply to loads that are left unsupplied after fault removal. Shipboard Power Systems (SPS) need automated reconfiguration for restoration schemes to restore vital loads quickly and efficiently in order to improve fight-through and survivability capabilities. The restoration in this paper is achieved using optimization with multiple objectives—maximizing the restored load and giving priority to vital loads. A restoration scheme for SPS with an integrated power system (IPS) and distributed generation (DG) involving islanding has been developed. This formulation includes a hybrid power system that has both ac and dc parts. The restoration formulation in this paper also considers the unbalanced nature of SPS operation with mutual coupling. [Copyright &y& Elsevier]

• A PSO-based optimization method for VRCD coordination control parameters of shipboard MVDC system is proposed. • Models of gas turbine and MVDC power system are established, leading to the quantification of evaluation indicators considering gas turbine capacity and HESS configuration. • The simulation results validate the effectiveness of the proposed control strategy and optimization method, contributing to improved transient power flow. Supplying power for large pulsed power load with shipboard MVDC system has continued to be a challenge. Due to limited grid capacity and power ramp rate of prime movers, the high-power load mutation will cause intolerable impact, which is an essential issue to be solved. In this paper, hybrid energy storage system is configured for transient power compensation, and the distributed virtual resistive capacitive droop is introduced to power coordination for MVDC sources. The transient flow evaluation function considering the speed state of the genset and the configuration cost of hybrid energy storage system is defined, models of the gas turbine and MVDC power system are established, and the optimization method of control parameters and system flow based on PSO and model simulation is proposed. The effectiveness of the proposed control strategy and optimization method is verified by MATLAB/Simulink simulations. [ABSTRACT FROM AUTHOR]

The Non-Utility Distributed Energy Resources (nDERs) are those not responsible for supporting the distribution system operation. These resources are crucial for improving the Energy mix's sustainability due to their majority renewable nature. However, integrating these resources into distribution systems has become a challenge for Distribution Companies (DisCos) due to their intermittent behavior. This challenge is even more significant when a gap in distribution system modernization (smart meters and communication systems) exists. This paper proposes an approximate method to evaluate the nDERs' impact on the distribution system's steady-state voltage. The method is based on a linear approximation of voltage drop/rise and the impedance matrix. It has been validated on two distribution systems considering five scenarios. Numerical comparison with exact solution has shown good results in four scenarios with maximum absolute errors around 0.01 p.u. in low-risk and high-risk voltage violation situations. The proposed method can be used in the planning or operation stage as a first estimation where no real-time monitoring is available, or the power-flow calculation is difficult to obtain. • The method does not require running a power flow simulation for each analysis. • The nDERs' voltage impact can be easily estimated by matrix/vector operation. • The DisCo can define power limits for operation without real-time monitoring. • A first estimation of nDERs' voltage impact in common scenarios. [ABSTRACT FROM AUTHOR]

A fundamental requirement of the electric power system is to maintain a continuous and instantaneous balance between generation and load. The intermittency and uncertainty introduced by renewable energy generation requires expanded ancillary services to maintain this balance. In this paper, we examine the potential of thermostatically controlled loads (TCLs), such as refrigerators and electric water heaters, to provide generation following services in real-time energy markets (1–5 min). Previous research in this area has primarily focused on the development of centralized control schemes with an aggregate TCL model. An objective of our approach is to enable each TCL to model and control its dynamics independently and to use distributed convex optimization techniques to allow a central aggregator to influence, but not directly control, the behavior of the population. To control the non-linear dynamics of hysteretic dead-band systems in a manner suitable for convex optimization, we introduce an alternative control trajectory representation of the TCLs and their discrete input signals. This approach allows us to approximate the control of a TCL as a convex program and to produce a solution that can be interpreted stochastically for implementation. To perform distributed optimization across large populations of TCLs, we apply a variation of the alternating direction method of multipliers (ADMM) algorithm. The objective of the distributed optimization algorithm is to enable an aggregator to coordinate with a population of TCLs and to increase or decrease the total power demand according to a control signal. We include experimental results in which different populations of TCLs with varying levels heterogeneity are optimized to provide 5-min ahead generation following services. We numerically demonstrate the algorithm's potential for controlling a TCL population's power demand within a definable error tolerance. [ABSTRACT FROM AUTHOR]

• Cascading jam-congestion and source-load mechanism in ET-DN was demonstrated. • Combined the DTA model of TN based on DVI with the multi-period AC OPF model of DN based on MISOCP. • Jam/Congestion in ET-DN may cause undesirable chain propagation and source-load mismatch problem. • A joint optimization scheme of ET-DN with dynamic distribution network reconfiguration is proposed, to eliminate jam-congestion deterioration and improve the operation of ET-DN system. The development of dynamic wireless charging technology and photovoltaic distributed generation sources provides a solution to eliminating the mile anxiety of electric vehicles (EVs), however which strengthens the spatio-temporal coupling in electrified transportation-distribution network (ET-DN). In this paper, by combining the dynamic traffic assignment model of transportation networks (TNs) with the multi-period AC optimal power flow model of distribution networks (DNs), the dynamic coupling model for ET-DN is established to depict the spatio-temporal distribution of EV charging load and jam-congestion cost. We found that coordinating the EVs charging and active/reactive power resources helps to alleviate jam in TNs and congestion in DNs, while source-load spatio-temporal mismatching may lead to the deterioration of jam-congestion in ET-DN, even there are sufficient active/reactive power resources, which has an adverse impact on the system security and economy. To overcome the source-load spatio-temporal mismatching problem, a joint optimization scheme of ET-DN with dynamic distribution network reconfiguration is proposed to eliminate jam-congestion deterioration and improve the operation of ET-DN system. [ABSTRACT FROM AUTHOR]

The Virtual Microgrid (VM) method is a solution for addressing challenges in Conventional Distribution Network (CDN), such as power fluctuations or load mismatches, by actively partitioning the CDN into interconnected Microgrid-style VMs. Previous studies have fewer discussions about the mutual interaction between the grid's partition performance and Distributed Energy Resources (DERs) allocation. This paper proposes a new approach for dividing a large power grid into clusters by using the complex network theorem. The approach integrates power flow dynamic, line impedance, generator-load relations and power generator cost-efficiency into a single static weighted adjacency matrix. Meanwhile, a multi-objective Genetic Algorithm (GA) planning structure is also denoted for transforming a CDN to VMs with mutual interaction between partition and DER allocation. The proposed metric is tested in both transmission and distribution networks. The IEEE 118-bus system test shows that even with a higher value of the proposed indicator, there are fewer power exchanges between sub-networks. Meanwhile, in the 69-bus radial system tests, the GA-based co-planning method outperforms previous methods in forming more self-sufficient and more efficient interconnected VMs. An intermediate solution is suggested by implementing a trade-off between inter-VM power exchange and the operation cost. • Concurrent plan of Power Grid partitioning and Distributed Generation allocation. • New model for power network by complex network theory. • New metric to evaluate quality of power grid partitioning. • New solution for transforming distribution network to clustered Virtual Microgrids. [ABSTRACT FROM AUTHOR]

To improve the resilience of electric distribution systems, this paper proposes a stochastic multi-period mixed-integer linear programming model that determines where to underground new distribution lines and how to coordinate mobile generators in order to serve critical loads during extreme events. The proposed model represents the service restoration process using the linearized DistFlow approximation of the AC power flow equations as well as binary variables for the undergrounding decisions of the lines, the configurations of switches, and the locations of mobile generators during each time period. The model also enforces a radial configuration of the distribution network and considers the transportation times needed to deploy the mobile generators. It is shown that long-term line undergrounding decisions which are cognizant of short-term mobile generator deployments yield superior results relative to undergrounding decisions made without considering mobile generators. Using an extended version of the IEEE 123-bus test system, numerical simulations show that combining the ability to underground distribution lines with the deployment of mobile generators can significantly improve the resilience of the power supply to critical loads. • Resilience can be improved via mobile generators and underground lines. • Stochastic optimization for siting underground lines and operating mobile generators. • Show benefits from jointly considering undergrounding and mobile generator decisions. [ABSTRACT FROM AUTHOR]

With the increase of distributed energy resources in the distribution grid, planning to ensure sufficient infrastructure and resources becomes critical. Planning at the distribution level is limited by the complexities of optimizing unbalanced systems. In this paper we develop a three-phase infeasibility analysis that identifies weak locations in a distribution network. This optimization is formulated by adding slack current sources at nodes in the system and minimizing their norm subject to distribution power flow constraints. Through this analysis we solve instances of power flow that would otherwise be infeasible and diverge. Under conditions when power flow is feasible, our approach is equivalent to standard three-phase power flow; however, for cases where power flow fails, the nonzero slack injection currents compensate for missing power to make the grid feasible. Since an uncountable number of injected currents can provide feasibility, we further explore the optimization formulation that best fits the solution objective through use of both a least squares and an L1 norm objective. Our L1 norm formulation localizes power deficient locations through its inherent sparsity. We show the efficacy of this approach on realistic unbalanced testcases up to 8500 nodes and for a scenario with a high penetration of electric vehicles. • A novel three-phase system optimization that is applicable to unbalanced systems. • Robust and scalable approach that is demonstrated up to 8500 nodes. • Application of slack variables with a physical meaning that provides grid insight. • An L1 norm formulation localizes solutions for grid improvement recommendations. [ABSTRACT FROM AUTHOR]

• A planning framework for low-voltage direct-current grids is proposed. • (Meta-)Heuristic methods are suitable for structure-dependent grid planning. • Cable trench costs are similar for radial, ring and meshed grids. • Line lengths and total annuity grid costs increase with higher meshing degree. Accompanied by further cost degression and technological development in the field of power electronic devices and DC technology, low-voltage DC (LVDC) grids for public power supply gain practical relevance for the future grid design, promising a solution to the technical challenges in the course of energy transition and digitization. In this paper, a comprehensive planning framework for urban public power supply LVDC grids is presented. Based on an analysis of degrees of freedom in such systems including potential for power flow control, the structural design of LVDC grids is investigated by explicitly planning radial, ring and meshed structures applying heuristic and metaheuristic algorithms on georeferenced supply data. Key to accuracy of the developed line courses is the orientation to existing traffic routes, establishing additional practical significance of the proposed approach. Three optimized LVDC grids as result of the case study are compared in terms of technical and economic aspects. [ABSTRACT FROM AUTHOR]

• In addition to load compensation, UPQC is enhanced to supply reactive power to grid. • The reactive power supplied is flexible as per the requirement from the grid. • UPQC-DG can participate in providing ancillary service in smart grid scenario. • Reactive power is regulated using additional PI controller in UPQC-DG control. • Power angle control is used to reduce additional VA burden on UPQC-DG. Unified Power Quality Conditioner with Distributed Generation (UPQC-DG) is combined equipment that not only compensates power quality issues but also integrates distributed generation into the grid. This paper proposes to incorporate additional functionality in UPQC-DG to provide reactive power support to the grid. The proposed functionality enables the UPQC-DG to not only compensate for load reactive power but also to export it to the grid in a controllable and regulated manner. The control method of the proposed UPQC-DG system is based on a combination of Synchronous Reference Frame (SRF) theory and Unit Vector Template Generation (UVTG) and utilizes an additional PI controller to control the reactive power flow to the grid. Since the UPQC-DG in the proposed research handles an increased quantity of reactive power, the work incorporates the Power Angle Control (PAC) method to share reactive power burden between series and shunt Active Power Filters (APFs) of UPQC-DG for reducing the overall rating. The proposed UPQC-DG system is validated using exhaustive real-time simulations in Opal-RT for steady-state and dynamic performance. [ABSTRACT FROM AUTHOR]

Variable energy resources (VER) penetration increases the cycling operation of conventional thermal plants, inducing an operating costs increase. In some cases, due to its impact on O&M costs, the cost of each start can significantly raise. The impact of this effect on spot prices depends on the pricing rules implemented: in some cases (non-linear pricing rules), these costs are compensated via discriminatory side payments and thus not included in the price formation while in others (aka linear) a single price per MWh is calculated to remunerate every single unit that is producing. These two alternative designs result lead for instance to a different remuneration for base-load plants. The first objective of this paper is to explore to what extent this remuneration difference might turn to be relevant as VER (and specifically solar PV) deployment develops. To do so, we also analyze the importance of properly allocating medium-term O&M costs in the short term, a hot topic in the regulation of a number of power markets today. We propose a way to properly calculate the start-up cost-adder component due to O&M and how this cost-adder is affected by cycling operation. [ABSTRACT FROM AUTHOR]

• A distributed OPF algorithm, tolerant to resource failures in the NCS, was developed • The integrated strategy fixes the voltages of affected DCUs to previous OPF solution • The algorithm provides feasible OPF solution despite failure in NCS • The algorithm converges irrespective of time-point, location and number of failures • The algorithm presents fast convergence, scalability and modularity • The OPF algorithm is suitable for system-level control of DC distribution grids In the future multi-terminal DC (MTDC) distribution grids, with high penetration of converter-interfaced distributed energy resources (DER), the system-level control is expected to be realised through a fully-distributed optimal power flow (OPF) algorithm that determines the voltage and power set-points for the converters. The OPF problem is divided to nodal OPF sub-problems, which are solved by distributed control units (DCUs) operating as a networked control system (NCS). This paper presents a fully-distributed OPF algorithm with an incorporated strategy, to survive failures in the NCS, such as permanent changes in the NCS topology due to the crash of a DCU or the loss of a communication link. By changing the constraints of the OPF sub-problems of the affected DCUs upon the detection of the failure in the NCS, the fully-distributed algorithm becomes tolerant to permanent changes in the NCS topology and converge to a feasible OPF solution. Simulation results in different IEEE networks and failure scenarios demonstrate the fast convergence, irrespective of the number and location of the failures in the NCS or the failure time-point during the execution of the algorithm. [ABSTRACT FROM AUTHOR]

Abstract: An important consideration in the operation of droop-controlled islanded microgrid (IMG) systems is its maximum loadability. This paper proposes the consideration of the system maximum loadability in droop-controlled IMGs optimal power flow (OPF) problems. Three Droop-controlled IMG OPF problems are investigated; (1) The OPF problem for maximum loadability assessment, (2) The OPF for maximizing system loadability, and (3) The bi-objective OPF problem for loadability maximization and generation cost minimization. A detailed microgrid model is adopted to reflect the special features and operational characteristics of droop-controlled IMG systems in the proposed OPF problems formulations. Numerical simulation studies have been carried out to demonstrate the importance and consequences of considering the system maximum loadability in the operational planning of droop-controlled IMGs. [Copyright &y& Elsevier]

Abstract: Specially connected transformers such as V–V, Scott and Le-Blanc transformers are used to convert a three-phase supply into one or two single-phase supplies. These transformers are commonly used in the electro locomotive traction systems. This paper investigates the harmonic cancellation characteristics of such transformers. The results show that when two harmonic-producing loads are connected to each single-phase side of the transformers, the harmonics produced by the loads will cancel out at the primary sides of the transformers. The amount of cancellation is affected by transformer type and harmonic order. The study is performed for seven types of specially connected transformers. [Copyright &y& Elsevier]

The protection of active distribution networks incorporating microgrids with high penetration of Distributed Energy Resources (DERs) can be challenging if traditional protective relays are used. This is mainly due to the changes in the power flow, fault current level, difficulty in protection coordination, changes in system topology, and system operating conditions. This paper proposes three new protection algorithms for active distribution networks with large penetration level of inverter-based DERs. These protection algorithms comprise of an adaptive differential protection algorithm, incremental transient energy-based directional protection, and a rate-of-change of current protection. The proposed protection algorithms were tested with a distribution network integrated with wind, solar, diesel generator, and battery storage DERs which are capable of operating in islanded mode forming local microgrids. The distribution system and the proposed protection functions modelled and simulated using the Real-Time Digital Simulator (RTDS®). The results obtained from tests validate the proposed algorithms; and their capability to correctly detect and timely isolate faults without resulting in nuisance tripping of the DERs. [ABSTRACT FROM AUTHOR]

• A new methodology for the Steady-state security region for the security assessment of distribution systems with the presence of DER. • Consideration of the intermittent characteristic of the DER generations. • The proposed methodology can be used in online or offline environments. • The proposed tool can be used in planning studies of distribution systems. • The proposed methodology can also be used for DER Regulation and Allocation in Distribution Networks: Volt/Var optimization and Congestion Relief. Modern Electric Power Systems are evolving from a centralized generation model toward a complex infrastructure with the presence of Distributed Energy Resources (DER). The transformative changes are especially pronounced at the level of the distribution system. The emergence of new generation technologies as solar, for example, affects the customer profile, expansion planning, and operation procedures of distribution utilities. Therefore, this paper describes a new methodology based on steady-state security regions concept for the security assessment of distribution systems with the presence of DER. The main objective of the proposed methodology is to allow an effective evaluation of the operating conditions of distribution systems with high penetration of DER, focusing on the intermittence of the new generation resources. The proposed methodology has been tested using two distribution systems. The first one is a tutorial 13-bus system, which is a small tutorial feeder, and the second one is a real large-scale model of a distribution network. The results presented indicate the effectiveness of the proposed technique in the distribution system security analysis. The proposed methodology is implemented using the Python language and uses the OpenDSS software as a power flow solver. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a decision tool for utilities to perform the optimal generation expansion planning in a deregulated electricity market. Combining the immune algorithm (IA) and Tabu search (TS) an refined immune algorithm (RIA) is developed to solve this problem. By considering the various load types (peak load, middle load, basic load) and independent power producers (IPPs) competition, the generation expansion planning model is established under the operational constraints, reliability constraints and CO2 constraints. RIA is conducted by an improved crossover and mutation mechanism with a competition and auto-adjust scheme to avoid prematurity. Tabu lists with heuristic rules are also employed in the searching process to enhance the performance. Testing results show that RIA can offer a better tool for generation expansion planning of utilities and promoted the competition ability of company. [Copyright &y& Elsevier]

• Modernization of the operation in distribution system. • Mathematical model for equipment, loads, and physical laws for the day ahead of operation in the distribution system. • Application of stochastic and deterministic models in the proposed approach. • The approach can be a powerful tool to reduce energy consumed and power demand. The new elements connected in electrical distribution systems increase the complexity of grids as well as planning and operating. The benefits of classical techniques, such as Conservation Voltage Reduction (CVR), combined with a coordinated operation of distribution elements, can contribute to increase efficiency and to reduce energy consumption of the distribution systems. This paper proposes an optimization model for a day-ahead operation of an unbalanced distribution system with photovoltaic distributed generation (DG) penetration. The CVR technique will be considered in deterministic, stochastic and robust approaches, considering the uncertainty of its parameters in the load modeling. The proposed optimization model aims to minimize energy consumption at the substation considering the operation of traditional elements, such as On Load Tap Changers (OLTC) at substation and capacitor banks (CB), but also modern elements, such as intelligent photovoltaic inverters. In the proposed approach, the mathematical problem, initially modelled as a mixed-integer non-linear programming problem, was converted into a continuous linear programming problem. The results were obtained using a modified IEEE123-bus test system indicating good results for utilities to save energy and reduce power demand in three optimization approaches: deterministic, stochastic and robust, and the last one proved to be better for being conservative for voltage violations and lower computational burden. [ABSTRACT FROM AUTHOR]

• The proposed method can exploit various electricity consumption patterns. • The model dramatically increases the accuracy of short-term load forecasting. • The reliabilities of load forecasting under various conditions are demonstrated. • The error statistics information provides confident levels of load forecasting. Due to high penetration of distributed energy resources, integration of intermittent renewable energy resources and deployment of demand-side management, highly accurate short-term load forecasting becomes increasingly important. This paper proposes a full wavelet neural network approach for short-term load forecasting, which is an ensemble method of full wavelet packet transform and neural networks. The full wavelet packet transform model is used to decompose the load profile and various features into several components with different frequencies and these components are used to train the neural networks. To perform load forecasting, the full wavelet packet transform model decomposes features into various components that are fed into the trained neural networks, and the outputs of the neural networks are constructed as the forecasted load. The proposed model is applied for load prediction in the electric market of Ontario, Canada. Simulation results show that the proposed approach reduces the mean absolute percentage error (MAPE) by 20% in comparison with the traditional neural network method. The proposed approach can be used by utilities and system operators to forecast electricity consumption with high accuracy, which is highly demanded for renewable energy integration, demand-side management and power system operation. Image, graphical abstract [ABSTRACT FROM AUTHOR]