The integration of Distributed Generation (DG) units in the existing power system has made the reliable operation of the system more complex. This has necessitated a comprehensive approach in planning the expansion of the system with the incorporation of DG units for effective and reliable operation of the system. In this study, a robust Hybrid Islanding Detection Technique (HIDT) has been proposed for identifying the islanding event early and accurately in the distribution networks with DGs installed by a two-step Genetic Algorithm (GA) process. As the reliability of power supply to the customer is of utmost importance, a priority-based load shedding scheme is proposed. The proposed load shedding scheme sheds only the vulnerable loads in the island for regaining the frequency and voltage stabilities. By the proposed methods, a comprehensive solution for system planning and emergency control actions can be obtained for effective operation of the system with DG units. The proposed methods are investigated on standard IEEE 33 and 69 bus distribution systems under different loading conditions. The results obtained show that the proposed methods are able to identify the islanding event more effectively and also regain the stability in the island with less amount of load shedding.

The integration of distributed wind farm leads to additional fluctuation of power flow in a high-voltage distribution network, which has become a major concern in automatic voltage control. This study proposes a slack optimal control method to determine the tolerance band of gateway reactive power (GRP) which takes into account voltage constraints, energy loss and excessive operations of control devices. Analysis of network characteristics shows that the GRP control band should be set according to both load levels and the outputs of distributed wind farm. Based on the analysis, slack optimal active loss difference strategy is proposed to set the slack optimal band of GRP. A slack optimal band matrix is defined and a partitioning intersection strategy is proposed to implement the differential setting of the slack optimal control band parameters of GRP. Simulation studies are conducted on a practical distribution network in China and the results show that the proposed method performs well in energy saving, control device regulating, voltage profile keeping, and reactive power balancing in a simple and practical way.

Centralised operation of distribution system suffer from inherent difficulties like increased complexities with increased system size, consequent frequent upgradation, delayed decision making and so on. Paradigm shift towards decentralised operations overcomes the aforesaid problems and assist in automated grid operations. Load flow is an indispensable tool, where the system operator does centralised calculation of state variables. This study proposes a novel approach towards decentralised load flow computation for weakly meshed distribution system. Agent technology is employed to design the framework which is based on agent relaying concept. The agents are located on system buses, and have limited access to information pertaining to system topology and nodal injections. By coordinating with neighbouring agents, they aim towards the fulfilment of their own goal, i.e. bus voltage calculation. To achieve this, several behaviours such as forward sweep, backward sweep, break point calculations and scenario generation are incorporated in the proposed system design. The solution thus obtained is decentralised in nature. The agent designing is done under JAVA environment on JADE platform. Two case studies considering 15 bus and 69 bus radial distribution systems are simulated with the proposed concept to show the validity and applicability of the proposed framework for smart grid management systems.

In this study, an operation window constrained strategic energy management (OWCSEM) for microgrid operational scheduling is examined. The scheduling problem is formulated as cost minimisation/benefit maximisation of distribution resources. The scheduling operation of distributed resources is evaluated for various perspectives such as customer driven, micro grid operator (MGO) driven and MGO driven with utility constraints. The MGO driven scheduling operation considers the distribution network loss minimisation in addition to economic benefits of distributed resources. The loss estimation of distributed network/microgrid is performed using forward-backward sweep algorithm, considering the ill-natured radial network. Thereafter, the optimisation is performed using modified gradient-based search method, considering the linear nature of the problem. The simulation results are presented and discussed for the three scheduling scenarios proposed under operation window constraints. The customer driven scheduling of distributed resources resulted in highest profit among all the scheduling alternatives. On the other hand, the MGO driven scheduling horizon resulted in lower line loss cost component at a compromise of distribution resource benefit. The utility constrained MGO driven scheduling objective attained a compromise solution in terms of loss component and customer benefit. Thus, it is identified as best practice for overall welfare maximisation of microgrid/distribution network.

The increased complexity of the modern distribution system caused by the installation of a large number of distributed energy resources, dictates the necessity for novel, decentralised schemes for the grid operation. In this study, a fully distributed method for the economic dispatch (ED) problem is proposed that takes into account distribution losses. The solution is reached using only local computations and exchange of messages between adjacent nodes without the need of a central coordinating entity. The algorithm presents plug-and-play capabilities and is self-triggered. More specifically, the ED is formulated as a resource allocation problem and a fully distributed algorithm is employed to acquire the solution that is based on the replicator equation model. It takes into account the technical constraints of the generators and it is extended in order to integrate the distributed calculation of active power losses using distributed estimation of the loss penalty factors. Guarantees for the convergence and optimality of the proposed algorithm are provided along with numerical results that demonstrate the effectiveness and efficiency of the algorithm.

In this study, an efficient load frequency controller (LFC) for standalone two-area hybrid microgrid system (HμGS) is addressed. Social-spider optimiser (SSO) is applied to fine tune the proposed proportional–integral–derivative (PID) controllers by generating their optimal settings. The integral time multiplied summation of absolute deviations and the gains of PID controllers define the fitness function and control variables, respectively. The performance of the proposed SSO-based method is demonstrated on an isolated HμGS complete with variety of energy storage systems under number of scenarios. The scenarios include load fluctuations, variations in wind speed, and sun irradiance employing real site measurements. In this study, photovoltaic generating arrays and wind turbine generators are not participating in system frequency regulations due the proposal of their maximum power tracking operation strategy. The signatures of time-domain dynamic responses and cropped numerical results ascertain that the proposed SSO-based LFC scheme is promising in diminuting the signal deviations and in short time. Further validations for cropped results produced by SSO are made compared with powerful optimisation tool such as genetic algorithm which signify the tuned PID gains.

Vehicle-to-grid (V2G) control of electric vehicles (EVs) has the potential to provide frequency regulation for power system operation. The authors study the frequency droop control with EVs’ participation. The challenge is to simultaneously suppress frequency fluctuation and satisfy transportation usages of EV owners. A V2G control consisting of frequency droop control and scheduled charging is developed to overcome this challenge. Frequency droop control can suppress frequency fluctuation by responding to frequency deviation signal, while scheduled charging can achieve the charging demands of EV owners. Although uncertain regulation may result in deviation of the battery energy levels from the expected, the scheduled charging made based on the departure time, the real-time, the real-time battery energy levels, and the expected battery energy levels can compensate this change in real time. The proposed V2G control can ensure different types of charging demands such as holding battery energy levels and elevating battery energy levels, unlike existing methods in which different V2G control strategies have to be developed. Simulations on a two-area interconnected power grid using real power grid data in China validate the effectiveness of the proposed V2G control in suppressing frequency fluctuation and achieving the charging demands of EV owners.

Two important and upcoming technologies, wind resources and microgrids, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. However, traditional droop control does not allow the microgrid to maximise the power available from the wind. This study proposes a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. Simulation results show that power from the wind can be maximised, while maintaining the system's bus voltage around a nominal value using a distributed multidimensional droop approach. Selection of the optimal droop relationship is discussed and simulation results are presented.

Congestion management is one of the core enablers of smart distribution systems where distributed energy resources are utilised in network control to enable cost-effective network interconnection of distributed generation (DG) and better utilisation of network assets. The primary aim of congestion management is to prevent voltage violations and network overloading. Congestion management algorithms can also be used to optimise the network state. This study proposes a hierarchical and distributed congestion management concept for future distribution networks having large-scale DG and other controllable resources in MV and LV networks. The control concept aims at operating the network at minimum costs while retaining an acceptable network state. The hierarchy consists of three levels: primary controllers operate based on local measurements, secondary control optimises the set points of the primary controllers in real-time and tertiary control utilises load and production forecasts as its inputs and realises network reconfiguration algorithm and connection to the market. Primary controllers are located at the connection point of the controllable resource, secondary controllers at primary and secondary substations and tertiary control at the control centre. Hence, the control is spatially distributed and operates in different time frames.

This study proposes a single stage solar photovoltaic (SPV) system utilising a linear coefficient function (LCF) based control approach. The main aim is to develop a cost effective, reliable and efficient SPV system. For estimation of peak power from the SPV array, an adaptive perturb & observe based approach is utilised. Whereas, to control the gating signals of the voltage source converter, a linear coefficient function based approach is used. The proposed system injects the estimated power from the SPV array to the grid. Moreover, it is also used for mitigation of harmonics of the load current, unity power factor operation and load balancing. The proposed SPV system has used a SPV feed forward term to reduce the burden on the proportional integral controller and improves the dynamic response under atmospheric changes. The SPV system is modelled and experimentally verified the control under different operating conditions.

This paper investigates the planning and operational processes of modern distribution networks hosting distributed energy resources (DERs). While in the past the two aspects have been distinct, a methodology is proposed in this paper to co-optimise the two phases by considering the operational flexibility offered by DERs already in the planning phase. By employing AC optimal power flow (OPF) to analyse the worst-case scenarios for the load and distributed generator injection, the optimal set-points for the DERs are determined such that the network's security is ensured. From these results, the optimised individual characteristic curves are then extracted for each DER which are used in the operational phase for the local control of the devices. The optimised controls use only local measurements to address system-wide issues and emulate the OPF solution without any communication. Finally, the proposed methodology is tested on the Cigre LV benchmark grid confirming that it is successful in mitigating with acceptable violations over- and under-voltage problems, as well as congestion issues. Its performance is compared against the OPF-based approach and currently employed local control schemes.

A decentralised control method that deals with current sharing issues in dc microgrids (MGs) is proposed in this study. The proposed method is formulated in terms of ‘modified global indicator’ concept, which was originally proposed to improve reactive power sharing in ac MGs. In this work, the ‘modified global indicator’ concept is extended to coordinate dc MGs, which aims to preserve the main features offered by decentralised control methods such as no need of communication links, central controller or knowledge of the microgrid topology and parameters. This global indicator is inserted between current and voltage variables by adopting a virtual capacitor, which directly produces an output current sharing performance that is less relied on mismatches of the multi-bus network. Meanwhile, a voltage stabiliser is complementary developed to maintain output voltage magnitude at steady state through a shunt virtual resistance. The operation under multiple dc-buses is also included in order to enhance the applicability of the proposed controller. A detailed mathematical model including the effect of network mismatches is derived for analysis of the stability of the proposed controller. The feasibility and effectiveness of the proposed control strategy are validated by simulation and experimental results.

A novel general distributed secondary control (DSC) scheme is proposed to implement coordination control for both droop-controlled and active power and reactive power (PQ)-controlled distributed generator (DG)-clusters in multi-microgrids (MMGs), using cluster concept. It not only reduces the steady-state derivation caused by primary droop control, but also brings the whole MMG into a new optimised operation state in the secondary control. The implementation of the DSC is accomplished based on the protocol combining pinning control and in-group and inter-group information exchange of multi-agent system. Accordingly, the DSC of the MMG is converted to the distributed multiple DG-clusters control, and the control process is tuned to tracking group synchronisation to pinning-based anticipative consensus in DG-clusters. In this way, the implementation of many MMG functions, such as global coordination among MGs, local autonomy in an MG, reliability, scalability, and self-healing are all simplified. Meanwhile, the dimensions of control and the number of controllers are dramatically reduced by pinning control. In addition, the requirements for a central controller and complex communication topologies are obviated. Simulation results are presented and discussed to illustrate the effectiveness, adaptability and advantages of the proposed control.

This study presents a comprehensive delay-dependent stability analysis of a micro-grid system with constant communication delays. First, an exact method that takes into account both gain and phase margins (GPMs) is proposed to determine stability delay margins in terms of system and controller parameters. The method implements an elimination procedure to transform transcendental characteristic equation into a standard polynomial of the crossing frequency. The real roots of this new standard polynomial exactly match with the purely imaginary roots (crossing frequencies) of the original characteristic equation with transcendental terms. Second, an effective and simple graphical method is implemented to compute all stabilising proportional integral (PI) controller gains for a given time delay. The approach is based on extracting stability region and the stability boundary locus in the PI controller parameter space having user defined GPMs, and relative stability. The time-domain simulation studies indicate that the proposed schemes give better desired dynamic performance as compared with the recently developed schemes for micro-grid with communication delays.

Photovoltaics (PV) are a technology that is becoming increasingly prevalent in the residential sector. The impacts of this new type of generation are not always desirable from a distribution system standpoint, as large penetration levels can lead to voltage increases, considerable unbalance, and excessive tap operations. Recent standard changes have allowed the inverters that are used to grid connect PV systems, to utilise their reactive power capability for voltage regulation. Although this new capability is desirable, it is important to ensure that it is being applied in the most beneficial way. The work in this study makes use of a three-phase optimal power flow method to find optimal volt–var curves for grid-connected rooftop PV inverters, which can perform autonomous voltage control. A number of scenarios are applied to produce a sufficient range of voltages, and the resulting reactive power settings are utilised to determine the volt–var curve for each PV system on a test feeder. An active control scheme is also presented, and the results are compared with the proposed autonomous scheme for a test 24 h period.

This study proposes an approach for off-grid micro-hybrid system model to represent the locally available sustainable and renewable energy sources (RESs). This model is comprised of wind and solar energy as primary sources along with a pumped storage unit (PSU) as backup. The proposed PSU is modelled with pico-hydro turbines (PHTs) and an open well. The ground water in the open well is effectively utilised along with agriculture and domestic needs in rural areas. The depth of the open well is exploited as the working head for the PHT. The power dispatch of two PHTs at a constant operating head, using the standard lambda iteration method, is obtained ensuring optimal utilisation of the stored water. The performance of the proposed model is tested using solar irradiance and wind speed data during winter and rainy seasons. The ratio of expected input energy and load demand on the succeeding day is used to control the water discharge on the current day. This model taps the unused potential of the open well as an energy storage system. Thereby, it limits the usage of batteries in satisfying the basic load demand of domestic consumers who do not have access to grid electricity.

Multi-terminal dc (MTDC) grids are expected to be built and experience rapid expansion in the near future as they have emerged as a competitive solution for transmitting offshore wind generation and overlaying their ac counterpart. The concept of inertia sharing for the control and operation of MTDC grids, which can be achieved by the proposed unified reference controller. The control objectives of the MTDC grids voltage source converter (VSC) stations are no longer limited to the stabilisation of MTDC grid, instead, the requirements of ac side are also met. The interaction dynamics between the ac and dc grid is analysed to illustrate the proposed concept. In addition, the voltage source converter stations can work in different operation modes based on the proposed unified control structure, and can switch among the operation modes smoothly following the secondary control commands. Simulation results exhibit the merits and satisfactory performance of the proposed control strategy for stable MTDC grid operation.

Because of the uncertainty of renewable energy generation and load, batteries as energy storage devices play an important role in ensuring the safety and reliability of microgrid. To take full advantage of the batteries, the battery lifetime characteristics are analysed, and a weighted Wh throughput method is proposed to estimate the battery lifetime. To improve the economy of microgrid, an economic scheduling model of microgrid in grid-connected mode is established with the consideration of battery lifetime. For fast and efficiently solving the model, a technique is developed to convert the optimisation problem into a mixed integer linear programming problem and a mixed integer linear programming algorithm is applied to solve it. The proposed method has been validated on a microgrid, which consists of a wind turbine, a photovoltaic system, a micro turbine, a fuel cell, a diesel engine and a battery energy storage system (BESS). The simulation results show that the BESS is managed rationally and the total operation cost of microgrid over scheduling period is decreased by applying the proposed scheduling method.

Electric vehicle (EV) charging can have various impacts on low-voltage distribution systems, along with increasing the uncertainty of network load levels. One method for capturing the statistical uncertainty is probabilistic load flow (PLF). A primary concern of such an approach is determining the correlation between the input variables. Since data are limited, a 1 min resolution bottom-up time-variant load model, capturing the changing voltage dependencies of the load, is used for modelling household electrical demand to provide pseudo-meter data for the three-phase PLF analysis of a residential distribution network. The correlation between the household and EV charging loads are implicitly taken into account by modelling the EV plug-in and departure times with the corresponding occupancy model. Two autonomous plug-and-play charging scenarios are compared with a standard charging arrangement at both unity and 0.95 capacitive power factors. Four different PLF input correlation scenarios, varying from fully correlated to fully independent, are considered. The proposed charging scenarios and reactive power provision reduce the likelihood of system voltage violations introduced by EVs. The PLF results are verified against those from the initial time-series analysis providing valuable insight into the uncertainty introduced by EVs and the correlation between household and EV loads.

In the environment of active distribution network, more distributed control devices are deployed to enhance the system reliability and flexibility. The master station of the distribution automation system is required to transfer real-time topology information to numerous field devices for implementing the distributed operations. To reduce the computational burden of the master station and to make it more autonomous for the distributed agents to utilise the topology information, this study proposes a fully distributed solution to topology processing for the distributed applications. It reduces the grid topology to an undirected graph, divides it into subgraphs and executes a distributed adaptation of graph connectivity algorithm to solve the problem. The algorithm uses the Lagrange multiplier method to optimise the subtask allocation and neighbour-to-neighbour communications to compute the graph connectivity. The configuration technique and the usage are presented to illustrate the distributed approach. The algorithm is applied in a fault location, isolation and service restoration scheme to demonstrate its effectiveness. It is compared with the centralised method to highlight the improved performances. Test results show that the algorithm can recognise changes in real-time topology correctly and has significant advantages.

With the rapid growth of distributed energy resources (DERs) and microgrids (MGs), the volatility of renewable generations will impact the economical and secure operation of the power system. To exert the grid-friendly manner of MGs, an optimal joint-dispatch scheme of energy and reserve is proposed in this study for combined cooling, heating and power (CCHP)-based MGs. In the scheme, the total operation cost of the MG is minimized under pre-defined reserve requirements. The energy demands are satisfied via dispatching various DERs. Distinguished from the electric demand balanced at any given instant, the unbalance between thermal supply and demand is acceptable because the temperatures can be maintained due to the thermal inertia. When the electric supply is in shortage, the energy provided for the thermal systems can be temporarily reduced so that more energy can be utilised to support the electrical systems. The dynamics of the MG is modelled by discretising thermal balance differential equations. With the coordination of CCHP systems, the reserve capability of the MG is fully utilised, thereby ensuring the security of the bulk power system. Case studies based on an industrial park in Chicago, USA validate that the proposed scheme can provide more reserve capability.

The increasing penetration of small-scale renewable power sources into the passive distribution networks brings direct deteriorated impacts on operation of microgrids due to the lack of inertia and damping property, e.g. unexpected voltage rise, increased fault level. To this end, this study presents a novel virtual synchronous generator (VSG) based multi-loop control solution aiming to efficiently manage the embedded inverter-based renewable distributed generators (DGs) in a plug-and-play fashion. With such multi-loop control structure, the virtual flux oriented control is adopted to avoid the harmonic interference and guarantee accurate control of vector orientation process in the U/I closed-loop feedback based vector control. The VSG based control is able to obtain timely current response and carry out static error free tracking control of output voltage. The pre-synchronising control aligned to the outer loop to ensure smooth transition from island to grid-connected mode is also studied. The proposed control solution is assessed through a set of simulation experiments in a microgrid for both island and grid-connected scenarios, and the numerical result confirms its technical benefits.

Efficient and well-timed investment in distributed generation (DG) in distribution networks in the electricity market environment presents a big challenge for distribution companies. In this study, a real option valuation framework is proposed to determine the optimal investment strategies for DG including the investment location, size, and timing. Within the proposed framework, the profit from investing in DG is modelled, where the benefits include the operation cost savings and capacity update deferral benefit compared with a no-DG-investment scenario over the study period. Future power demands and electricity prices are modelled as stochastic variables. The candidate DG investment plans are considered as multiple mutually exclusive options, and the corresponding managerial flexibility for seizing opportunities and mitigating risk of loss upon an unfavourable unfolding of future uncertainties is assessed with real option analysis using the extended least square Monte Carlo method. The distribution of future investment strategies and optimal initial investment threshold levels under various scenarios are analysed in a case study to demonstrate the characteristics of the proposed framework and methodology.