This study proposes a new application of micro-phasor measurement units (µPMUs) for adaptive coordination of overcurrent relays in microgrids. Mis-coordination of overcurrent relays usually arising from the variation of relays fault current and it can cause damage to equipment of network and raise operating costs. Fault current injection and direction to microgrid are highly dependent on network uncertainties; therefore, fault current is affected by line and power plant outages. This study proposes an algorithm to detect these uncertainties in online operation. Then, microgrid overcurrent relays coordination is optimised again. Uncertainties are line and power plant outages in transmission network and microgrid side and two distinct methods are used for each. For online detection of uncertainties in the transmission side, it is assumed that a µPMU is installed between transmission network and microgrid point of common coupling; so, the topology changes such as line outage is detected by monitoring of Thevenin impedance estimation that is obtained by µPMU measurements. Uncertainties detection in a microgrid is done by signals that are sent by µPMUs and installed all over the microgrid. All data are gathered and analysed in phasor data concentrators and then overcurrent relays coordination is updated with such changes.

This study deals with the faults’ detection and classification in AC transmission lines based on power spectral density (PSD), introducing PSD in time and frequency for analysing transient information under faulted conditions. The discrete wavelet transform is used for scaling current signals in time–frequency at different decomposition levels by approximation and detail coefficients. Then, a wavelet-covariance matrix is shaped with the aim to obtain its PSD, being this the key to detect and classifying faults. Results show that the proposed method attains the detection in a short time and the classification is accomplished via the Hellinger distance, whose straightforward implementation is carried out in this study. The classification process is compared adopting different classifiers to cope with a set of signals in a time frame. Finally, the proposal is extensively assessed using real and simulated signals stemming from multiple fault cases of radial and interconnected power grids.

Presently, the penetration of residential distributed energy resources (DER) that produce (photovoltaics, wind generators) or consume (electric heat pumps, electric vehicles) electric power, is continuously increasing in an uncoordinated fashion. If the appropriate steps are not taken to ensure their smooth integration, issues such as violations of voltage and thermal limits occur, especially at higher DER penetrations. This study investigates the impact of each DER on low-voltage (LV) networks, and subsequently, multiple large-scale demand side flexibility (DSF) schemes are proposed per DER type, based on the cooperation of system operator and residential customer, to combat said issues and to significantly increase DER penetration. A rule-based approach is used for each DSF scheme, to highlight their effectiveness in ‘raw’ form, and to assess whether they merit further practical consideration. Using data on real LV feeders and real DER profiles, through a Monte Carlo simulation framework considering the stochastic behaviour of the various network elements, DER impact and DSF performance are measured. The results include a major improvement in delivered power quality, highly increased DER accommodation capacity, a thorough comparison of the technical performance of each DSF scheme, and a conclusion on the effectiveness of each DSF scheme.

Distance protection is the most widely used protection technique for transmission line protection due to its enhanced selectivity towards fault, fast response, and availability of various relay programming algorithms. However, when faults are detected in zone 2 of a relay, instantaneous tripping is not possible and are cleared after an inherent time delay. Sometimes, this increased disturbance duration may lead to system instability, power quality problems, or may result in increased plant damage. To address this issue, communication-assisted accelerated distance protection has been employed. To have this communication for tele-protection through standardised and interoperable means, an IEC 61850 GOOSE-based communication-assisted distance protection scheme is employed. This IEC 61850 GOOSE-based accelerated scheme must meet the stringent performance requirements. Thus, this study presents the experimental validation and performance evaluation of IEC 61850 GOOSE-based accelerated protection scheme by transporting GOOOSE messages through tunnelling in inter-substation for accelerated distance protection scheme. A system-in-the-loop platform has been developed to analyse the end-to-end delay performances of GOOSE messages under different WAN scenarios here. It has been found that for worst-case scenario, there is a significant operating time saving in the proposed scheme.

Aimed at the status of distribution networks with a high penetration of renewable energy starved of flexible-regulation resources for improving their ability to absorb renewable-energy sources, this study puts forward flexibility-supply and flexibility-demand indexes for distribution networks and establishes a bi-level programming model for the distribution of flexible-regulation resources within the system-flexibility-balance constraints. The lower-level planning model seeks the lowest annual operating cost, lowest annual network loss, and lowest annual abandonment of wind and solar sources; in addition to the traditional power balances and constraints of various control variables and state variables, the requirement to balance constraints involving the flexibility of the system's supply and demand is even more crucial. The upper-level model aims to minimise the annual investment and operational costs. Combining the models, a double-layer iterative optimisation algorithm for flexible-regulation-resource allocation is proposed. Simulation results for an actual distribution network show that the proposed bi-level programming model can increase the capacity to absorb renewable energy and reduce system losses with the lowest investment and operational cost.

An optimisation technique employing artificial bee colony algorithm has been proposed for determining the droop parameters of the distributed generators in a micro-grid, operating in isolated mode. The proposed method minimises the active power loss and maintains a flat voltage profile. The bus interfacing the main and the micro-grid has been treated as a voltage regulated bus so as to facilitate seamless transfer from the autonomous to the grid-connected mode of operation and conversely.

The development of a new dissolved gas analysis (DGA) method often requires a comparative study to assess the accuracy of the proposed technique. This is faced with the following challenges: (i) the time and effort required to implement and validate the implementation of existing DGA methods, adds to the comparative study cost; (ii) the output states of different DGA methods are not similar, which makes it difficult to put methods side by side in a comparative study; and (iii) the availability of test data is limited. In this study, a user-friendly graphical user interface software package, DGALab, is developed to overcome these challenges. DGALab implements a unified DGA diagnosis framework to map the output states of DGA methods to uniform specifications. DGALab includes a library implementing most common DGA techniques, and includes a repository for input datasets available in the literature and collected directly from laboratories. DGALab simplifies the addition of new DGA techniques written in virtually any programming language. As a result, the process of developing a new DGA technique is greatly simplified using DGALab. To evaluate the software package results, the datasets and methods implemented therein were used to regenerate the results published in earlier research papers.

As it is known the load of distribution cables is not constant with respect to the daytime, increasing the current in some hours may lead to an increase of soil surrounding the cable resistivity due to the migration of soil moisture content. Formation of dry zones may cause failure of cable insulation. Also because the soil thermal properties change with time according to the weather conditions of different seasons, the current capacity changes significantly from time to time. This paper studies the effect of dry zone formation during load cycling of underground cables on their temperature rise and the temperature distribution in the surrounding which is not considered by IEC 60853-2. The thermal model of the cables using the thermoelectric equivalent method is modified by including the thermal soil resistivity variation with soil temperature and moisture content. The finite element method is used also in this study to obtain heat map of the cable and surrounding soil. Additionally, experimental work of three soil types was investigated to study the effect of temperature and moisture content variation on the soil thermal resistivity and the dry zone formation of each soil type. Field measurements of temperature distribution surrounding the cables are done.

As electric vehicles (EVs) penetration level is increasing, charging infrastructure should expand. This study concentrates on the economic aspects of EV charging stations (EVCSs). When CS capacity is not enough to simultaneously charge all EVs, the EVs will wait in queues to get service. This study presents a model for EVCS and a profit-based algorithm for charging scheduling (ChSc) of EVs from viewpoint of EVCS owner. The objective function is to maximise long-term profit of EVCS owner and to minimise delay time of EVs. The charging prices of queues are different from each other, which are determined by the EVCS owner, considering energy price. The time needed to charge an EV from the minimum state of charge to fully charge is considered as a time interval. It is shown that maximising profit at each interval, named as short-term profit maximisation (STPM), does not necessarily maximise long-term profit of the EVCS owner. Then, another ChSc strategy, referred to as long-term profit maximisation (LTPM), is proposed. Simulation results confirm that with LTPM, the owner of EVCS obtains more profit in long term. Also, in comparison to STPM, the incurred average delays of EVs in queues are much less.

The hierarchical control structure is widely investigated for a microgrid. Conventionally, the tertiary control layer and the primary and secondary control layers are studied independently since they are separated in time scale. It is difficult for distributed generation (DG) units to directly track the optimal power references provided by the tertiary control because they are controlled to behave as voltage sources by the primary and secondary controls. Moreover, even if the DG unit can realise power tracking, improper coordination among the primary, secondary and tertiary controls may still lead to instability of the microgrid. To fill the gap among the three control layers, this study proposes a method for realising their distributed joint operation. With the proposed method, DG units can track the optimal power references in a distributed manner. Regarding the stability issues, this study also presents (i) a detailed stability analysis of the system based on the constructed small-signal dynamic model and (ii) an adaptive regulation strategy of control parameters for enhancing the system stability. Finally, numerical studies and time-domain simulation results are provided to validate the proposed method's ability to realise a distributed optimal and stable operation for a hierarchically controlled microgrid.

The quality of electric power has become an important issue for electric utility companies and their customers. With the extensive application of micro-grid technologies, power quality (PQ) disturbances are more likely to affect users; thus, research on the recognition of PQ disturbances has attracted increased attention. This study presents a novel PQ disturbance-recognition algorithm, based on time-frequency (TF) analysis and a decision tree (DT) classifier. The proposed method requires fewer feature statistics compared to the S-transform-based approach for PQ disturbance identification. In this study, feature statistics extracted using TF analysis are trained by a DT classifier to perform the automatic classification of PQ disturbances. As the proposed methodology can efficiently identify PQ disturbances, the performance of the DT classifier can be ensured. In addition, the influence of noise is investigated, and 12 types of noisy disturbance, with signal-to-noise ratios of 30–50 dB, are considered for the classification problem. Finally, the proposed method is compared with other popular proposed disturbance-recognition algorithms in terms of detection accuracy. The experimental results reveal that the proposed method can effectively detect and classify different PQ disturbances.

By effectively adjusting the appliance usage patterns of customers, demand response (DR) is expected to bring significant economic and environmental benefits to the future smart grid. Two kinds of appliances should be considered for DR, i.e. shiftable appliances such as dishwashers and laundry machines, and non-shiftable appliances such as lights and stoves. Although the shiftable appliances can be well controlled by energy management systems, the random usage patterns of non-shiftable appliances will result in uncertainties to electrical demands and thus, affect the efficiency and reliability of smart grid operation. A two-stage stochastic programming problem is formulated, for which the distribution system operation cost is minimised in the first stage, by considering various distribution system operation constraints. The scheduling of shiftable appliances is optimised in the second stage, by considering the random usage patterns of non-shiftable appliances. To reduce the computational complexity caused by a large number of home appliances in distribution systems, scenario reduction technique is applied to reduce the number of possible scenarios while still retaining the essential features of the original scenario set. Extensive simulations are performed to evaluate the proposed DR scheme in IEEE 33-bus and 119-bus test distribution systems based on real appliance usage pattern data.

Incentive regulations of reliability have made a link between distribution companies' revenue and their service reliability. The companies have to decide how much to spend on various projects to provide an acceptable level of reliability while anticipation of load growth. Planners and decision makers require a comprehensive framework to optimally allocate available budgets to different plans with the highest benefits considering implementation of incentive regulation. This paper proposes a decision framework for the optimum share of expansion and reliability oriented plans in presence of reward–penalty mechanisms. A two-layer optimization model is introduced, where in the outer layer, an iterative algorithm is applied to determine the optimal set of long-term projects including Distributed Generations (DGs) installation. A heuristic optimization algorithm is employed in this layer. Considering long-term plans, in inner optimization layer, the optimal set of mid-term plans including feeder reinforcement, and preventive maintenance actions are determined using algorithms such as Branch-and-Cut and dynamic programming techniques. The model is further implemented on a test distribution network and the results are investigated through various case studies. Obtained results show the strong influence of incentive regulation on reliability indices.

The wide use of power flow controllers (PFCs) in transmission and distribution grids is becoming imperative. Power transistor-assisted Sen transformer (TAST) is a very recently introduced novel PFC that bridges the gap between most versatile flexible AC transmission systems controllers. It proved to possess closely comparable technical characteristics to that of the unified power flow controller (UPFC) at an installation cost that is less than the half. It is thus an attractive substitute of the UPFC for many utility applications. Nonetheless, since the TAST is a newly introduced PFC, it is of great importance to develop its steady-state model for its implementation in modern power systems analysis. The main contribution of this study is presenting two accurate steady-state models of the TAST: a simplified Simulink model (SSM) and a comprehensive Newton–Raphson model (CNRM) for its representation in the load flow analysis. The presented SSM and CNRM of the TAST are novel. A standard five-bus system and a modified IEEE-30 bus power system are used for demonstration of the effectiveness and validation of the SSM and the CNRM. Very closely comparable results are obtained when a TAST or more is used to increase and decrease the power flow in transmission lines.

Renewable energy integration to the power grid has seen a tremendous rise in last few years. A novel hybrid AC and DC bus layout (i.e. medium-voltage DC bus of 380 V and low-voltage DC bus of 48 or 12 V DC) for the residential consumer premises has been proposed in this study. This would enable the consumer to directly connect DC loads to the system, without the need of an individual power conversion device. This study summarises the strategical operational modes of the proposed hybrid power conditioning system (HPCS) for multiple distributed energy resources (DER) integrated residential premises located within urban/rural area. Modified HPCS converter control strategy has been proposed, such that the system operation is efficient and self-adaptive in both, grid forming (or, islanded) and feeding (or, grid connected) modes. System is configured by using a single power conditioning unit, capable of performing wide range of operations, such as, multiple DER interface, battery power management, grid power control and accessibility to AC and DC household loads at the desired voltage levels. Performance of the designed system has been tested via simulation and experimental studies.

System operators still rely on deterministic criteria such as the (i.e. the system would be able to withstand the outage of any single component without any load shedding) to hedge the system against contingencies. While simple and practical, this criterion miscalculates the actual amount of reserve required since it ignores the probability of contingency occurrence. Therefore, this criterion may lead to suboptimal reserve procurement and economic performance of the system. This study presents a multiperiod probabilistic security-constrained unit commitment (UC) model that includes the probabilities of generation and transmission contingencies for optimal reserve sizing, sourcing, allocation, and timing. The ability of energy storage systems (ESS) to provide contingency reserve is explicitly modelled. Benders’ decomposition and linearisation techniques are applied to solve the proposed probabilistic UC, which would be intractable otherwise. The impact of ESS on the contingency reserve procurement and deployment in post-contingency states are analysed on a modified version of the IEEE One-Area Reliability Test System.

The determination of the appropriate number and location of the phasor measurement units (PMUs) has raised the issue of the system monitoring as the main challenge. In this study, the problem of optimal PMU placement (OPMUP) is carried out in order to achieve a fully observable power system under normal and contingency conditions considering network expansion.‏ For this purpose, network expansion is investigated considering two fixed and flexible PMU placement scenarios. The contingency index is introduced through the modelling process of N − 1 contingency states. This index is inserted as a new term in the objective function by compromising the observability confidence level and the number of PMUs. Other goals including minimising the number of PMUs, measurement channels and redundancy are considered along with the OPMUP process. The IEEE 57-bus standard network in the MATLAB is studied during the expansion time horizon with the proposed algorithms to achieve the above goals.

Continuation power flow (CPF) analysis has been used in the literature to determine the voltage collapse point from active power versus voltage curves (PV curves) for steady-state voltage stability assessment. Affine arithmetic-based (AA) CPF analysis to determine PV curve bounds under uncertainty in power generation was introduced in the literature to overcome the problem of large computational time with Monte Carlo (MC) simulations, by getting a faster solution with a reasonably good accuracy. However, AA operations lead to more noise terms and hence overestimation of bounds. In the present work, a modified AA (modAA)-based CPF analysis is proposed to determine PV curve bounds by considering uncertainties associated with active and reactive power injections at all buses in the system. The proposed method reduces the overestimation caused by the AA operations and gives more accurate solution bounds. The proposed modAA-based CPF analysis is tested on 5-bus test case, IEEE 57, European 1354 and Polish 2383-bus systems. The simulation results with the proposed method are compared with MC simulations and AA-based CPF analysis to show the efficacy of the proposed method.