Microgrids have become an attractive option for distributed generation (DG) with increase in renewable energy sources (RES) and storage systems. The existence of both AC and DC microgrids has led to a new concept of hybrid AC/DC microgrid which consists of both AC and DC grids tied by an interlinking converter (ILC). Such hybrid AC/DC microgrid has the advantages of both AC and DC with increased efficiency and less cost since the conversion between AC and DC is reduced. The management of power in such a grid becomes important for voltage and frequency control. Different voltage and frequency control strategies have been successfully implemented within AC and DC grids, but the control of hybrid microgrid requires further attention with focus on ILC. This study presents an overview of various control schemes used for voltage and frequency regulation in standalone and transition mode operation of hybrid microgrid. A detailed study on hybrid grid structure is presented with different modes of operation. Various ILC strategies based on droop and communication-based control are presented. Based on the analysis, some recommendations are presented for future research.

In this study, a novel technique for fast transient stability limit assessment is proposed. In the proposed method, first the whole power system is approximated with a single machine equivalent model independent of the type and location of the fault, and its parameters are identified using on-line measured data. Next, a graphical index based on transient energy approach is presented for the transient stability limit. The proposed method is tested on a real 247-machine power network to all devices in service, and the load flow matched with real recorded data. Simulation studies show very promising results. Furthermore, they show that the defined stability index can be evaluated immediately after the fault clearing and can be accurately estimated even if does not exist any prior knowledge about the operating condition. This new method can be used for preventive security assessment in smart power systems. The results show that the proposed graphical stability limit can be used accurately as a measure for ‘distance to critical clearing time’ of relays.

A methodology for obtaining an optimal portfolio for the generation of electricity at the lowest cost and risk is proposed. This methodology uses a mixture design of experiments (MDEs) as a strategy for building nonlinear models of risk and cost in portfolio optimisation for the generation of electricity. The result is compared with the traditional theory of Markowitz mean–variance (MVP). The following characteristics are also presented in this study: the seasonality and volatility of the time series were manipulated using moving windows and computational replicas in MDE; desirability functions were used to optimise multiple variables, leading to lower cost and risk; Shannon entropy index was used to handle better portfolio diversification. A case study based on the energy market of the state of California was used to illustrate the proposal. The results show that this methodology facilitates decision making.

Challenges of unprecedented proportions face the electric power industry who takes on the responsibility for scheduling spinning reserve of a wind-integrated power system in an economical and reliable way. This study proposed a cross-entropy (CE) based simulation method to evaluate two indices of loss of load probability and expected demand not supplied, as well as the empirical distribution of demand not supplied. The triple together could be used for predictively sketching a full picture of spinning reserve inadequacy risk of a wind-integrated power system at an imminent operating time instance. The stochastic feature of the concerned multi-state system is modelled with a discrete-state continuous-time Markov process. Case studies based on the RTS-79 were carried out to illustrate the spinning reserve adequacy fluctuation given different present states of a rapid-start unit combined with or without considering the wind power penetration. Meanwhile, the advantage of the proposed CE simulation method over the exact convolution method and classical Monte Carlo simulation method in case of adequate spinning reserve is also demonstrated.

This study proposes a method to determine the optimal communication architecture in advance metering infrastructures (AMI). The method starts by indicating suitable groups of meters that share similar characteristics such as distance to the secondary substation and mutual proximity. Then it connects each group of meters to the AMI-head end through a communication architecture formed by wireless and power line communication technologies. The optimality criterion takes into account the capital expenditures, operational expenditures and the quality of service in the communication architecture. The method is tested on a low voltage (LV) network based on real utility data provided by EU FP7 DISCERN project partners. These tests show that the method is consistent with planning foresight and can be useful to assist in the AMI communication architecture designing process.

The primary objective of the conventional optimal phasor measurement unit (PMU) placement problem is the minimisation of the number of PMU devices that, when placed in a power system, measure all bus voltages. However, due to advancements in the field of relay technology, digital relays can now act as PMUs. This has significantly reduced device costs. Moreover, although the goal is to observe all the buses, the devices themselves can only be placed in substations, whose upgrade costs are much higher than those of the devices. Considering these factors, the approach proposed here simultaneously optimises the number of substations where traditional PMUs and dual-use line relay PMUs can be placed. The general optimal substation coverage (GOSC) algorithm presented in this study is also able to incorporate practical requirements such as redundancy in the measurement of critical elements of the system, and estimation of the tap ratios of the transformers present. Simulation results indicate that the GOSC algorithm provides significant techno-economic benefits.

With the increasing penetration of wind power and electric vehicle (EV) into the power system, system operators face new challenges for system reliability and generation cost due to the intermittent of wind power. Furthermore, the randomly connected EVs at different time periods and locations add more uncertainty to the power system. In this study, uncertainties in wind power generation and EV charging load are modelled into the day-ahead dynamic economic dispatch (DED) problem, solution feasibility and robustness are discussed, and the bad scenario set is formulated for the day-ahead DED problem. In the obtained model, parameters can be used to adjust the positive bias or conservative bias, charging/discharging power of battery switch stations are also controlled to optimise the total cost of power system. To solve the optimisation problem, the multi-agent bacterial colony chemotaxis algorithm and a mutation strategy based on the cloud theory are developed. The simulation results show that the proposed method is effective, and battery switching station can help to reduce total cost by charging and discharging batteries.

This paper studies the power balancing control of a multi-terminal high voltage direct current (HVDC) system constructed by a multiport front-to-front type DC–DC converter (MF2F). Dynamics of the inner AC circuit of the MF2F is analysed which points out the natural instability of the MF2F under un-balanced power orders. To solve the instability problem, an inner power balance loop and an external power balance loop are proposed at each port of the MF2F. The inner balance loop ensures power balance inside the MF2F and the external balance loop ensures power balance between a port and its external DC system. Power balance control is also designed for external converters that are under constant power control. Limits of the integrators and the total output of the balance loops are specifically set to automatically disable the balance controllers in normal operation and automatically enable the balance controllers during power imbalance. To isolate the DC faults at external DC systems, self-blocking modular multilevel converters are used at each port of the MF2F. Efficacy of the proposed power balancing control is verified by extensive simulations under AC faults and DC faults that cause un-balanced power orders. The proposed controllers can be used as generic controllers for MF2F.

A new approach for coordinated design of a static VAR compensator-based stabiliser and a conventional power system stabiliser is proposed. The approach is based on the integration between genetic algorithm (GA) and rough-set theory. The role of rough set is to select the most dominant controller parameters that are involved in the optimisation process. The proposed approach aims to minimise the computational time and reduce the storage capacity required for the optimisation problem as well as improve the performance of power system stability of power system. The proposed rough-set-based GA is applied to select the controller parameters included in the optimisation process as well as search for their optimal setting. This study also presents a comparison between the system performances when utilising individual or coordinated controllers with those of system utilising the proposed approach. Single machine system is used to investigate the efficacy of the proposed approach and multi-machine system is used to demonstrate the applicability and scalability of the proposed method. The simulation results and comparison analysis show the effectiveness of the rough-set-based GA. In addition, a good reduction in optimisation time and size of information is achieved by applying the rough-set-based GA.

The concept of voltage source converter based multi-terminal high-voltage direct current (MTDC) grids, represents both challenges and opportunities for the future of large power transfer and integration of renewable energy sources. For this kind of grids, the control aspect is of great importance, with voltage-droop based methods considered as one of the most attractive solutions. All existing strategies are designed to maintain the level of voltage in the MTDC grid constant during unexpected events, thus sacrificing the power flow. The aim of this study is to propose a new droop controller structure that maintains the dc-grid voltage close to the nominal value and at the same time tries to preserve the power flow in the dc grid, following events such as faults or disconnection of stations. The control scheme is presented and simulations are carried out in a four- and five-terminal MTDC grid, proving the validity of the concept.

This study presents a validation study of an approximated model of the European power system in 2014. A lightweight and open-source power-flow tool is used for this study. The tool and the model are publicly available and can be adapted to study future impact of large investments in the power system, specifically large-scale integration of renewable energy. The input dataset is based on a prior work, but it has been substantially updated for 2014. To maintain all aspects of the model open-source, only publicly available data was implemented. The modelling approach and simplifications are explained. Comparison of the simulation results with actual data on cross-border flows and energy mix for 2014 shows acceptable correlation. The model is able to capture main characteristics of the power system, such as reservoir handling, hydro pump pattern, and seasonal variation on cross-border flows.

This study proposes a comprehensive power outage detection and service restoration framework for a distribution system with advanced metering infrastructure (AMI) meters and networked microgrids (MGs). To cope with the resilience challenge of communication networks in severe weather events, the authors propose a decentralised outage detection method which obtains the total number of customers and the total amount of lost load in the outage area via local information exchanges among AMI meters. To provide fast-response service restoration, the proposed framework incorporates the network reconfiguration and the local power support from the connected MGs. The optimal restoration problem is formulated as a mixed-integer quadratic programme that controls distributed generators and loads in MGs and line switches to maximise the restored critical loads. Case studies on a modified 69-bus distribution system with networked MGs demonstrate the effectiveness of the proposed methodology in both outage detection and service restoration.

Staircase transmission constrained unit commitment (TCUC) formulations have been used for decades and are considered as energy-based TCUC formulations (EbUC). Recently, it has been reported that EbUC formulations may result in undeliverable energy schedules. Some power-based TCUC formulations (PbUC) have been proposed to address this problem. However, exact continuous time-based power outputs of units are usually approximated in these PbUC formulations and ramp-rate capacities of units are not accurately modelled. Besides, the implicit coupling between ramp-rate constraints and spinning reserves is neglected in both EbUC and PbUC formulations, which may cause that scheduled spinning reserve levels are unavailable in some time periods. To address these problems, a new PbUC formulation is proposed in this study with continuous time-based power outputs. It is found that the formulation can be transformed into an equivalent mathematical program and a Lagrangian relaxation-based approach is presented. Numerical testing is performed for a 10-unit system and an IEEE 24-bus system. Results show that the model and the solution algorithm in this study are effective.

Current low-voltage (LV) network planning methods consist mostly of a static deterministic assessment of radial network alternatives. This straightforward approach does not take into account the uncertainty which comes with the introduction of photovoltaic generation, electric vehicles and other new technologies into the LV network. Moreover, these technologies may call for a change in network topology, from radially oriented networks to more meshed variants. The focus on cost-efficiency requires the implementation of risk-based asset management into the LV planning approach. The complete implementation of these two aspects into LV network planning methods would result in a too complex network planning formulation. By using heuristic optimisation methods to reduce the number of network alternatives and scenarios which need to be assessed in combination with simplifications on the risk-based assessment of power quality, losses and service availability, a computationally feasible LV network planning approach is developed in this work. A Greenfield case study based on an existing Dutch neighbourhood shows how this approach can be applied in practice to yield the optimal network structure. Though the initial investments and availability of a meshed network are worse, the meshed network structure generates a 10% lower overall cost, due to reduced losses and improved power quality.

This study presents the improved flashover dynamic model based on both, impedance criterion for the discharge propagation and energy balance criterion for estimating the discharge elongation. One main contribution is to study the electro-thermal model of flashover polluted insulators in DC case enabling to predict the instantaneous changes of the discharge characteristics such as leakage current, discharge temperature, arc resistance and the temporal evolution of their analytics parameters (A, N). To demonstrate the efficiency of the developed model, the authors applied it for flat plat insulators polluted only with NaCl and with mixed pollution (NaCl with insoluble materials). The recommended dynamic approach includes directly the temperature in the dynamic study of the flashover phenomenon since it is an essential parameter involved in the development of the discharge which has not been treated in the earlier studies for dynamic model. Of particular interest, it is important to note that both critical electrical parameters current (I _cr) and voltage (V _cr) calculated using the presented model are in good agreement with those of the experimental one.

Maloperation of distance relay under stressed conditions like power swing and voltage instability has been reason of various power system blackouts. Thus, it has become very important to make the decision making of the distance relay to be intelligent enough so that it is capable of differentiating between fault and other stressed conditions. There is no shortage of computational intelligent techniques suggested in the literature for this purpose. However, with the growing complexity of the power systems, there have been cases when various system parameters, system topology and so on suddenly change. This study suggests an online intelligent technique: online sequential extreme learning machine that gives accurate result on such circumstances owing to its features of being an online tool. The suggested technique based on wide area measurements consists of two levels of classifiers that segregate stressed conditions like power swing and voltage instability from fault. Performance of the online intelligent technique has been compared with other intelligent techniques defined in the literature. Moreover, by using synchronised phasor measurements, shortcomings of the conventional relay technology have been overcome.

Mixed AC-HVDC systems enable new perspectives in the fields of operation, control and security of AC transmission systems. Although a promising vision, meshed HVDC grids do not exist in a real setting. Research on HVDC grid operation is therefore in need of valid test systems for static and dynamic aspects. Besides the CIGRÉ test system, which focuses on offshore factors and which is consequently not an overlay HVDC grid, a publically available test system does not currently exist. Recent publications in this field adapt established standard AC test systems to their case-related requirements of an HVDC extension. This work introduces and provides a mixed AC-HVDC test system enabling the evaluation of optimal power flow and security constrained OPF algorithms. State-of-the-art literature for HVDC-OPF applications is assessed, applied AC standard test systems are evaluated and key indices are derived from the findings. With respect to this, the proposed test system’s validity and the AC grid’s reference to reality is ensured. The proposed system, comprising 67 AC nodes, 102 AC branches, 9 VSCs and 11 HVDC branches, contains 13 critical contingencies which can be removed by either preventive or corrective measures. The data describing the proposed system is provided.

Internal arc fault in switchgear is an especially challenging fault type. High-power faults may lead to a serious hazard to personnel, significant damage to equipment, and extensive system outage. As the nature of arc faults is explosive, very fast protection is required. This study first presents a state-of-the-art technology for effective arc protection and then focuses on communication in arc-flash protection systems. Developments based on IEC 61850 Generic Object Oriented Substation Event communication are introduced including verification of the performance of the new system architecture.

Directional overcurrent relays are often used in the protection of electrical power transmission and distribution systems. These devices are installed along the network, and they must be coordinated to operate as fast as possible and in the adequate sequence. However, the coordination of relays is a complex problem, due to its discrete non-linear nature and its hard constraint structure. A matheuristic algorithm to provide coordination of directional overcurrent is proposed in this work. The algorithm combines a differential evolution strategy and linear programming formulations. In addition, two local search procedures are proposed to improve convergence and to handle continuous and discrete relay setups. Results for five instances show that the proposed method is able to obtain identical or better solutions than those already reported in the literature with considerably lower computational cost. Furthermore, the algorithm can directly handle robust coordination by considering possible changes in the systems conditions.

The advance on smart grid calls for the development and application of distributed intelligent control strategies based on open platforms that provides interoperability. The distributed control must be able to ensure reliable and secure operation of the power systems and enhance supply quality to consumers. The development of a multi-agent system for automatic restoration system (MARS) applied to a real power distribution network is presented. The agents of the MARS are embedded in external hardware to the intelligent electronic devices (IEDs) and communicate with each other via standard Foundation for Intelligent Physical Agents open protocols. To evaluate the MARS performance, a computer simulator was developed in Java to represent the distribution system. Experimental tests were performed in laboratory with the simulator integrated to the MARS via TCP/IP. The tests results have shown that the MARS was able to locate and isolate branches under permanent fault condition and restore healthy branches efficiently through a given switching sequence taking into account the system operational constraints. The proposed MARS has proved the effectiveness of distributed control scheme based on multi-agent system that runs independently of the current technologies of the IEDs of control and protection.

Effective network partitioning becomes an essential step to realise self-sustained smart grid, which serves as a prerequisite for ‘self-healing’ enabled decentralised control. Splitting the power network (PN) into areas is the last resort to avoid the spread of disruption and to maintain as many network survivals as possible. This study aims to resolve the issue of multi-objective PN partitioning by deploying a newly proposed hybrid approach concerning both real power balance and voltage profile. The proposed approach combines the Laplacian spectrum and self-organising map, which adaptively attains self-sustained network partitions on different operating conditions. The resultant partitions are characterised by the minimal intra-area real power imbalance with a healthy voltage profile. The authors experimentally evaluate the partitioning effectiveness and computational efficiency in several case studies including on the New England 39-bus, IEEE 118-bus, and Polish 2383-bus transmission systems.

This study deals with a real-time implementation of solar photovoltaic (SPV) grid integrated system possessing distributed static compensator (DSTATCOM) capabilities with three-phase four-wire voltage source converter (VSC) topology using least mean eighth control algorithm. The proposed system has an SPV array, a VSC, three single-phase non-linear loads connected to the grid and a ripple filter. The SPV and VSC together behave as a DSTATCOM and additionally supplies SPV power to the grid. The DSTATCOM reduces the total harmonic distortion of the grid currents, maintains the voltage of point of common coupling and improves the power factor. The maximum extraction of incident solar power on SPV array is achieved through an incremental conductance maximum power point tracking technique. The behaviour of the system is studied by developing a prototype with an SPV array simulator.

This study presents a mixed integer linear multi-objective model based on information gap decision theory, which is used to solve coordinated multiyear generation and transmission expansion planning problems. The model maximises the robustness of each uncertain parameter while a maximum allowable budget range is set. Fuel transportation price is considered. The results provide a numerical tool for system planner to help him adjust the appropriate level of robustness for each uncertain parameter of the problem. Extra limits on security, gaseous emission and fuel availability are considered. A multi-objective method called the ɛ-constraint method is used here to maximise the robust region of load and investment costs simultaneously. The model is implemented on a six-bus Garver test system and 24-bus IEEE test system. The numerical results show the good performance of the model.

The most commonly used motor in industries is induction motor. This motor is exposed to various power quality disturbances. A frequent power quality disturbance which has an adverse effect on induction motor is voltage fluctuations. In this study, the behaviour of three-phase induction motors under voltage fluctuation conditions is studied. By using the theory of dynamic phasor, an innovative equivalent circuit in which the speed fluctuations are taken into account is presented. The currents, efficiency and power factor under voltage fluctuation conditions are evaluated by the proposed equivalent circuit. The variations of these quantities due to different voltage fluctuation characteristics are also investigated. The simulation results are validated by measurements on the laboratory test setup which comprises a 1.1 kW induction motor excited by a programmable power supply unit.

Distribution systems of the future will definitely encompass numerous distributed energy resources, and thereby, the physical connection and commercial contribution among virtual power plants (VPPs) will be inevitable. Accordingly, this study proposes a methodology to address the trading strategies of a VPP in cooperation with its neighbouring VPPs. This cooperation is modelled based on some available cross-regional contracts and the problem faced by the VPP is how to determine its bilateral contracting portfolio. To this end, a decision-making framework for medium-term self-scheduling of a VPP with the aim of exercising arbitrage between two different trading floors, i.e. bilateral contracts and the electricity market, is presented. Moreover, an efficient risk management approach based on the concept of first-order stochastic dominance constraints is used to enable informed decision making under different levels of uncertainty. The resulting model is formulated as a mixed-integer linear programming problem that can be solved using off-the-shelf software packages. The efficiency of the proposed model is analysed through a detailed case study, and finally relevant conclusions are duly drawn.

In this study, a new real-time optimisation method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain a solution by parts, using the dynamic programming method and Bellman equation. The proposed solution method is based on the fact that the microgrid is designed with a central feeder line to which clusters of generators and loads are connected, and is suitable for microgrids with ring topologies as well as radial ones. The optimisation problem is formulated with the cluster reactive powers as free variables, and the solution space is spanned by the cluster reactive power outputs. The optimal solution is then constructed by efficiently scanning the entire solution space, by testing every possible combination of reactive powers, using dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The study includes the results of two test-case networks.

Utilities have installed distributed generators to improve reliability of the power distribution system. Distributed generators at various sites provide additional circuit paths in case energy provision to the end user is interrupted by a blackout or equipment failure. When the microgrid is working on island and grid-connected modes, overcurrent protections in power lines must be adjusted to different distributed generator circuit paths and feeder fuses in the microgrid. This study presents an adaptive overcurrent protection that integrates technical and economic advantages of fuses and relays in a microgrid with distributed generators. This fuse relay adaptive overcurrent protection (FRAOP) scheme protects power lines and feeders by grouping identical inverse time overcurrent settings of relays, and logic gates of relay's breakers. Selectivity, reliability, and speed of the FRAOP was verified by a real-time simulator with relays in-the-loop.

A sequence networks-based methodology for investigating voltage unbalance in distribution networks with renewable generation is presented. The sequence networks are derived from the original asymmetrical three-phase network, and then interconnected to study sequence voltages and unbalance propagation through the network. The approach enables to analyse the influence of line impedance, load demand and network topology on voltage unbalance caused by distributed generation in the network. The critical factors which impact the unbalance severity and the propagation mode are also identified. The approach is validated by comparing calculated sequence voltages with the results obtained by phase voltage-based methodology.

This study presents the design of adaptive fuzzy critic based emotional learning control design for automatic generation control (AGC) of a two-area power system interconnected via parallel AC/DC tie-lines. The adaptive fuzzy critic evaluates the current system situation and provides the emotional signal so that the artificial neuro fuzzy regulator to modify its characteristic and reduce the critic stress. The adaptive fuzzy critic based emotional learning control design are implemented and the system dynamic responses are obtained considering 1% load disturbance in area-1. A comparative study of performance of proposed control, fuzzy logic and conventional integral based control is carried out and presented with and without considering the system non-linearities such as governor dead-band and generation rate constraint. The proposed control design technique has been demonstrated as a superior one as compared with other techniques used for the AGC design in the study. Furthermore, the sensitivity analysis of the proposed control is also examined by varying the system parameters over the wide range from the nominal system values.

This study investigates a novel multi-objective differential evolution (MDE) solution methodology for multi-objective optimal power flow (MOPF) problem. The MOPF problem is modelled with various technical and economical objective functions. These objectives are handled as mono, bi, tri, and quad-objective MOPF problems. For solving these MOPF formulations, a novel MDE algorithm is proposed. The novel MDE algorithm modifies the DE variant (DE/best/1) with Pareto ranking in the selection operator and develops a fuzzy-based best compromise solution for each generation to feed the mutation operator. This modification guarantees high convergence speed and enhances the search capability via exploring the neighbourhood of the best compromise solution in successive generations. The standard IEEE 57-bus power system is emulated to prove the effectiveness and competence solutions of the mono, bi, tri, and quad-objective MOPF at acceptable techno-economic benefits compared with other evolutionary methods. Similarly, the standard IEEE 118-bus test system is used to show the effectiveness of the proposed algorithm for solving the OPF problem in a large-scale power system.