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Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are revised according to their specific roles to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

DC is reappearing in the power system – it can be seen on the generation side as solar photovoltaics and wind farms with AC/DC/AC conversion; on the transmission side as HVDC lines and on the consumer side as a variety of modern electronic loads. Power distribution is an area where DC has not yet made any practically extensive appearance, this area is still in research phase. Related to DC distribution, the concept of DC microgrids is also witnessing a significant research contribution in the recent times. One of the research areas besides system control, protection etc., is the energy efficiency of the system. This paper gives an overview of the recent and relatively old research efforts in the field of efficiency/energy-savings analysis for the DC power distribution system. Furthermore, critical analysis of the previous research efforts has been provided and gap in the present body of knowledge related to this field has been identified. The requirements of a comprehensive analysis, mathematical modelling and system designing from a future study in this direction have been mentioned. The findings of this paper can serve as guidance for further investigation and research for the energy savings potential of DC power distribution networks.

The paper analyzes grid strength and grid impedance for systems with significant penetration of power electronics. The work shows that the traditionally employed Thévenin equivalent cannot capture the different saturation states of power converters and therefore some classical definitions of grid strength based on short-circuit power at the point of connection fail to describe the system behavior. The paper proposes to map the impedance for all the different possible voltages at the point of connection and analyzes how the impedance depend on the voltage and angle of derivation for different possible simplified systems (grid-following converter in parallel with a Thévenin equivalent and grid-forming converter) considering the different saturation states of the converter. Numerical results and case studies are included as examples of the conducted analysis.

Dynamic pricing strategy will play an increasingly important role in solving the contradiction between power supply and demand under the current electricity market environment. The performance of different users varies from the same pricing strategy, which further to exacerbate the difficulty of the optimal power dispatching. Therefore, a non-cooperative Stackelberg model based game theory is developed in this paper, which considers both the impact on load fluctuations in power grid and users’ dissatisfaction with electricity consumption. Firstly, users are divided into different types by induction and classification in this model to realize the comprehensive consideration of different types of electricity users. Secondly, two utility functions are set up in this model. The utility function of power supply side is set to represent the benefit obtained in the process of power supply by the power company. The utility function of the power demand side is set to express the dissatisfaction degree of electricity users. The developed model is solved by using the NSGA-Ⅱ algorithm in this paper. Finally, the developed model is applied to the actual case and the sensitivity analysis of relevant parameters is carried out to verify its effectiveness.

Adequate power system protection plays crucial role in ensuring reliability of electricity supply, thus it is a key challenge for distribution system operators to increase the effectiveness of protection schemes operation and protection equipment itself. The main goal of the paper is presenting a multi-criteria protection algorithm that may boost effectiveness of power lines’ short-circuit overcurrent relays in medium voltage networks in case of various two phase faults. The idea of enhancing protection performance is based on fault current symmetrical components’ analysis and specifically on using negative and zero sequence currents as criterial values for overcurrent line protection used against such faults. The paper describes in detail the proposed solution and analyses its performance based on medium voltage network simulations carried out using DIgSILENT PowerFactory software. Promising simulation results can be observed for definite time overcurrent protection relays used in reactance-earthed networks, as introduction of the proposed method proved to increase the zone of effective operation twice comparing to the traditional phase current based solutions. Moreover, in the proposed solution, coordination of protection settings for small earth-fault current values, which are identified by other protection relays, is not necessary. The proposed solution may complement the traditional algorithms for short-circuit protection (I≫) used in modern protection relays monitoring the level of negative and zero sequence current, and therefore may significantly improve the effectiveness of detecting various phase-to-phase faults in the considered MV line protection zone.

International audience; This paper tackles the problem of the classification of partial discharge (PD) and noise signals by applying unsupervised and semi-supervised learning methods. The first step in the proposed methodology is to prepare a set of classification features from the statistical moments of the distribution of the Wavelet detail coefficients extracted from a dataset of signals acquired from a test cell under 40 kVDC. In a second step, an unsupervised learning framework that implements the k-means algorithm is applied to reduce the dimensionality of this initial feature set. The Silhouette index is used to evaluate the number of natural clusters in the dataset while the Dunn index is used to determine which subset of features produces the best clustering quality. Since the unsupervised learning does not provide any method for result validation, then the third step in the methodology of this paper consists of applying a semi-supervised learning framework that implements Transductive Support-Vector Machines. The labeling of the test set that is required in this framework for the result validation is carried out by visual checking of the signal waveforms assisted by GUI tools such as the software PDflex. The results using this methodology showed a high classification accuracy and proved that both learning frameworks can be combined to optimize the selection of classification features.

Partial discharge is a prevalent phenomenon under high voltage (HV) where the discharge partially bridges the gap between two electrodes. At increasing voltage levels, physical dimensions and distances between the electrical parts become critical. Designing electrical components for such high voltages and planning of high voltage laboratories/tests need to deliberate this aspect as it could lead to possible complications such as partial discharges (PD) from the floating metal components. Floating electrodes under AC voltages are associated with a distinctive PRPD pattern. However, there is a lack of literature on the physical interpretation of this pattern. Likewise, under DC voltages, no consistent explanation towards the defect behavior has been reported. Therefore, this paper presents an in-depth study of the floating electrode defect configuration under AC and DC voltages. Subsequently, it provides the physical interpretation of the discharge patterns obtained through the stepwise description of the discharge stages under both conditions. By formulating criteria for repetitive discharges and presenting novel PD fingerprints for DC floating electrode configuration, the outcomes published in this paper contribute towards prospective PD defect identification tools under HVDC.

HVDC transmission is booming worldwide. Despite electrode systems are one of the frontiers of DC technology, being a key component of HVDC links, in the experience of the Authors many aspects of their manufacturing, design and operations are less known among the HVDC community with respect to other components, like cables and converters. Aiming at filling this gap, this paper is a survey on ground/sea return with electrode systems for HVDC links, particularly focused on the preliminary design. The configurations of HVDC systems (monopolar, homopolar, bipolar) are recalled first, highlighting the advantages of ground/sea return. Then, ground electrodes are treated, illustrating the basic parameters and geometrical arrangements for the design of ground electrodes. Later, shore and sea electrodes are illustrated. Considerations relevant to ground current close the paper.

The aim of this paper is to consider and analyze design of capacitive voltage divider for measuring ultrafast voltage occurrence. Measuring pulse voltages by means of a capacitive divider in nanosecond range is affected by problems related to the construction of the divider and materials used. However, an appropriate constructive solution could minimize the budget of measuring uncertainty of the measurement pertaining to parasitic inductivity and capacitance. Consequently, the right selection of dielectric materials could offset the effects of high-voltage and low-voltage frequency characteristics of the capacitor. Four types of capacitive dividers have been constructed for the purpose of this paper. The high-voltage capacitor of each divider is a gas capacitor (intended to avoid both electrostatic and electrodynamic influence on measurement uncertainty). Ultrafast pulse response is measured by dividers constructed in this way, and compared with the corresponding response obtained from numerical simulations.

The propensity to utilization of inexpensive, clean and distributed energy resources in the today's power systems structure are expanding due to various economic, political and sociological reasons. However, the power generated by these resources is extremely unpredictable, which is called uncertainty and exceptionally fluctuated drastically that is known as variability, during the operation epoch. So, exposure to these two features is great significance and value. This problem is known as the power system flexibility in the literature of electrical power system studies. Promoting flexibility in the system is too expensive and can be evaluated in different time frames. This paper studies the power system flexibility with the presence of uncertainty and variability of demand and supply side resources in a planning timeframe. This paper proposed an improved method for demand response uncertainty modeling with Z-number. This method is a hybrid possibilistic and probabilistic process. Furthermore, this paper applied an approved method for renewable generation uncertainty modeling with Monte Carlo. The scrutinies show, the most cost-effective way to consider the flexibility is planning timeframe, so this study proposed a novel paradigm for Flexibility-Constrained Integrated resource planning in presence of high penetration uncertain and variable demand-side and supply-side resources namely as FCIRPU/V-DSRs. The simulations are implemented with the proposed FCIRPU/V-DSRs methodology on a test system. The results show that this innovative framework provides a significant improvement in the power system flexibility at an inferior cost than other investigated methods.

This paper presents a new model for the self-scheduling problem using a home energy management system (HEMS), considering the presence of solar photovoltaic (PV) panels and an air conditioner (AC). The AC used in this study utilizes an inverter for controlling the temperature. The proposed model adopts the time-of-use (TOU) tariff for electricity, and minimization of the daily bill is the main objective of the proposed model. In the proposed model, there are some fixed and flexible loads, and optimal scheduling of the home appliances is modeled as a mixed-integer linear programming (MILP) problem to achieve the minimum daily bill. The HEMS in this paper incorporates a PV system, combined with the electrical energy storage (EES) system to deal with the uncertain solar power generation as well as optimally serving the loads during the peak hours, taking into account the charging and discharging control strategy of the installed EES. The indoor temperature can be held within a predefined margin and the settings of the AC system may be obtained according to the indoor-outdoor temperature model, which has been presented in this paper. During peak hours, the contribution of the AC in energy consumption to the daily bill is considerable. Therefore, optimal operation of the AC and other home appliances can effectively reduce the energy consumption and consequently, will result in reduced bills.

The presence of flexible ac transmission system (FACTS) controllers in transmission lines causes mal-operation of distance relays. The series-shunt FACTS devices have larger influence on the performance of the relays compare to the other FACTS controllers. Furthermore, high-resistance fault is another factor that relay become under-reach and cannot correctly identify the fault. In this paper, a method is provided based on synchrophasors to eliminate the effects of unified power-flow controller (UPFC) and fault resistance on the distance relay. In the presented method, the data of voltage and current signals of buses will be sent to system protection center (SPC). In SPC, an algorithm is provided based on active power calculation in buses which is able to eliminate the effects of both mentioned factors. The main advantage of the proposed method, in addition to the simplicity of the algorithm, is the ability to operate in all types of faults and in high-resistance faults. Furthermore, a technique is presented in this paper to calculate UPFC data. A comparison has been performed between this technique and another method where UPFC data is directly transmitted to SPC by communication channel. In modeling of UPFC, detail model is used based on 48-pulses voltage source converters. 1 2017 Elsevier Ltd Scopus

Hybrid HVDC system, which consists of the advantages of line commutated converter (LCC) and voltage source converter (VSC), is an emerging power transmission system. This paper presents a review of four LCC-VSC hybrid HVDC topologies. The first topology is the pole-hybrid HVDC system, in which the LCC and VSC form the positive- and negative-pole respectively. The second one is the terminal-hybrid HVDC system; in this topology one terminal adopts LCC and the other terminal adopts VSC. The series converter-hybrid HVDC system is the third topology wherein each terminal is formed by LCC and VSC in series. The fourth hybrid topology under consideration is a parallel converter-hybrid HVDC system with LCC and VSC connected in parallel in each terminal. The main contribution of this paper is a comprehensive analysis and comparison of the four mentioned hybrid topologies in terms of PQ operating zone, power flow reversal method, and DC fault ride-through strategy.

This paper presents a data-driven control approach for maximizing the total power generation of the offshore wind farm by using a recently developed learning model predictive control (LMPC) algorithm. The control is designed by coordinating yaw angle control actions of wind turbines to mitigate the wake interactions among the turbines for increasing the total farm power production, which is termed as wake redirection. This paper mainly focuses on designing the architecture and methodology of the LMPC for wind farm, including a unified wind turbine wake interaction model, the LMPC for minimizing an iteration cost function, the recursive feasibility, stability and convergence analysis. Extensive comparative studies are conducted to verify the performance of the LMPC in comparison with the existing model predictive control (MPC) method under the same wind speed conditions. The results show that the wind farm yields up to 15% more power production by using the LMPC than the conventional MPC.

The number of fully-rated converter wind turbine generators equipped with a Permanent Magnet Synchronous Generator (PMSG) has sensibly increased in the late years. The optimal utilization and controllability of a PMSG is achieved using a Pulse Width Modulation – Voltage Source Converter (PWM-VSC) that allows interfacing the electric machine with the distribution network by means of a DC link. The generator/Machine-Side Converter (MSC) controls the operation of the PMSG. This paper proposes a methodology to assess the feasibility of the steady-state working points of PMSG based wind turbines without running a set of time-consuming time-domain simulations. Three control objectives for MSC are usually considered: stator voltage control, unitary power factor control and torque control. The aim of the present paper is that of providing an analytical methodology to check the feasibility of the steady-state working points dictated by different control strategies of the MSC starting from the specific operational constraints provided by the wind power plants characteristics. The effectiveness of the proposed methodology is demonstrated comparing numerical results of a MATLAB® implementation against dedicated time-domain simulations. Simulations results demonstrated the appropriate performance of the proposed methodology characterized by the almost negligible computational time required.

Under the thermal storage strategies in present studies, the power generation unit (PGU) in combined cooling, heating, and power (CCHP) system is turned on/off only based on the state of storage tank; or the operation state of PGU is determined by thermal demand or/and electric demand, which has no relationship with the state of storage tank. For these traditional strategies, either energy demands or state of storage tank is considered for the operation of system. This paper proposes a novel thermal storage strategy (TSS2) for CCHP systems, which determines the operational state of the PGU based upon electric demand, thermal demand and the state of thermal storage device. In this paper, the operation principle of TSS2 is described and compared with the traditional strategies. A hospital in Shanghai was used to evaluate and compared the performance of the system operating under different storage strategies. The results show that TSS2 improves the performance of CCHP system more significantly compared with the traditional strategies. TSS2 can make both PGU and capacity of thermal storage tank be fully used by CCHP system to produce more electric and thermal energy to meet demands of building. Compared with system without thermal storage, the minimum and maximum increase rates of annual total cost saving for traditional strategies are 0% and 14.84%, respectively. However, for TSS2, they can reach 3.79% and 20.22%. Similar conclusions could be achieved for CO2 emission reduction and primary energy saving. The effect of TSS2 on the CCHP system performance is different under different operation strategies.

This paper discusses the losses analysis of low power high-frequency Wireless Power Transfer Systems (WPTSs). Ideal models for efficiency evaluation of WPTS can predict performances that are quite far from the real ones. The model proposed in this paper includes semiconductor devices losses, as well as modulation of duty-cycle and phase for the secondary side rectifier. The global influence of semiconductor devices and control parameters on the overall WPTS performances is numerically determined by solving the herein discussed non linear equations system. Experimental measurements realized on a 2 W@6.78 MHz WPTS demonstrate the validity of this analysis.

Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

This paper presents a simulation-based methodology for assessing the impact of employing different distribution system operator’s remuneration strategies on the economic sustainability of electrical distribution systems. The proposed methodology accounts for the uncertainties posed by the integration of distributed electricity generation resources, and the roll out of smart meters. The different remuneration strategies analysed in this paper include notably new distribution tariffs based on individual peak power consumption and time-dependent rates that are contingent on the time of energy consumption, both requiring smart meters to work. The distributed electricity generation resources are modelled through an optimisation framework and an investment decision process that gradually deploys household photovoltaic installations depending on their profitability and the electricity charges, including the distribution rates. The impact of the distribution system operator’s remuneration strategy is measured by an accurate modelling of the remuneration mechanism of this entity, which can adapt to various distribution tariff designs. We analyse this impact over a discrete time horizon. Our methodology is illustrated with several examples of distribution tariffs including old –based on energy consumption or on per-connection fees– as well as new –based on power consumption or time-of use fees– designs. Finally, we provide a comprehensive sensitivity analysis of the proposed simulation environment to the main parameters of the methodology.

Nowadays, the massive deployment of distributed energy resources in distribution networks poses more operational challenges such as network congestion to distribution system operators. To cope with these challenges in an economically efficient way, the distribution system operator can utilize demand-side flexibility traded in the local flexibility market to manage the distribution network. In the existing distribution-level flexibility market frameworks, the market operator is assumed to have access to network parameters in order to ensure the market clearing solution being technically feasible from the operational point of view. To protect the privacy of network parameters, this paper proposes an alternating direction method of multipliers -based market clearing strategy, in which the market operator communicates with the distribution system operator to clear the market such that the market clearing solution respects network operation constraints without revealing network parameters to the market operator. In addition, in the existing flexibility bid formulations, the energy payback condition is determined without considering operation constraints of flexibility resources and the flexibility cost has not been considered. To fill this gap, this paper formulates an optimal flexibility bidding model for aggregators, which carefully models the energy payback condition and enables the aggregator to receive the maximum revenue with flexibility costs considered. The case studies were conducted on the Roy Billinton Test System with electrical vehicles and heat pumps as flexibility resources. The results demonstrate that the proposed distribution-level flexibility market framework is effective to perform day-ahead congestion management of distribution networks and is profitable to aggregators and end-users.

By applying stepwise inertial control (SIC) on wind turbines (WTs), a secure system frequency response after large active power imbalances in the system can be achieved. In Part I of this paper (Ding et al., submitted for publication), a novel approach for determining when to terminate the SIC is presented. In this context, a new analytical expression for a fixed termination time (FTT) is derived. In order to optimally implement the FTT concept, both the parameters of the system frequency response (SFR) model and the incremental power during the SIC process must be known. This paper is providing answers to these questions and furthermore proposes an advanced application strategy for the FTT concept. The new strategy improves the frequency nadirs and prevents the WTs’ rotor speed from violating the lower permissible limit during the SIC process. Using the least squares algorithm, the unknown SFR model parameters are estimated from the frequency measured at the point of common coupling (PCC) of the wind farm. The incremental active power is determined considering the effect of the incremental power on the frequency nadirs and the releasable kinetic energy of the WTs. The performance of the proposed new application strategy is verified using a modified IEEE 39-bus test system.

To reduce the impact of wind power prediction error on power system operation, Credibility theory and Fuzzy chance constrained programming method are introduced while solving wind power inter-regional scheduling optimization problems. Firstly, the paper introduces the carbon trading (CT) and Tradable Green Certificates (TGC). Then, an energy independent external delivery model is constructed, which contains wind power independent delivery model and thermal power independent delivery model. Secondly, the paper put forward energy combined external delivery model considering CT and TGC. Meanwhile, Credibility theory and Fuzzy chance constrained programming method are used to deduce credibility distribution function of wind power prediction errors and define the feasible region under a certain confidence level, respectively. Since credibility distribution is applied as a measure function and the feasible region covers fuzzy event set, the optimal solution will be in the credible solution space. Thirdly, four scenarios are set according to CT and TGC. Finally, this paper uses six thermal power units and one wind farm as the simulation system. The simulation results show Credibility theory is applicable to overcome wind power uncertainty. Energy combined external delivery is better for improving system consuming wind power. CT and TGC could increase wind power grid-connection, but CT’s optimization effect is more obvious than TGC. The optimization effect reaches the optimum when both CT and TGC are implemented, and energy external delivery profits should be reasonable allocated for encouraging thermal power to participate in wind power delivery.

This paper introduces an approach based on stochastic data envelopment analysis (SDEA) for performance assessment of electricity distribution units. A new approach is applied for assessment of Iranian distribution units from 2001 to 2011 in this paper. There are usually incomplete and stochastic data or lack of data with respect to electricity distribution companies. Due to lack of information about some parameters, theory of probability is imported to the model. Different Iranian distribution units are considered as decision making units (DMUs). Network length, transport capacity and the number of employees are chosen as inputs while number of customers and total electricity sales are chosen as stochastic outputs. Then, the best electricity distributions units are selected with respect to efficiency scores in stochastic environment. Also, SDEA model is performed for each input, separately to identify the most important input indicators by comparing the results of associated efficiencies with SDEA model. The empirical results show that network length is the most important and influential input factor in this particular case study. To the best of our knowledge this is the first paper that examines stochastic outputs for assessment of electricity distribution units by SDEA in Iran.

Frequency Response Analysis is a well-known technique for the diagnosis of power transformers. Currently, this technique is under research for its application in rotary electrical machines. This paper presents significant results on the application of Frequency Response Analysis to fault detection in field winding of synchronous machines with static excitation. First, the influence of the rotor position on the frequency response is evaluated. Secondly, some relevant test results are shown regarding ground fault and inter-turn fault detection in field windings at standstill condition. The influence of the fault resistance value is also taken into account. This paper also studies the applicability of Frequency Response Analysis in fault detection in field windings while rotating. This represents an important feature because some defects only appear with the machine rated speed. Several laboratory test results show the applicability of this fault detection technique in field windings at full speed with no excitation current.

International audience; The HVDC links are increasingly used not only to interconnect asynchronous AC systems but are also embedded into a same meshed AC power system. Thanks to its speed and flexibility, the HVDC technology is able to provide transmission system advantages as transfer capacity enhancement and power flow control. In addition, studies have shown that the way of controlling the HVDC converters impacts the stability of the AC system. This can be particularly exploited to enhance the dynamic power system performances during transients. In this paper a robust multivariable control design for HVDC link converters is proposed. It is based on the coordination of the control actions of the HVDC converters and the use of a control model which takes into account the dynamics that mostly impact stability of the neighbor zone of the HVDC link. This new methodology was used to synthesize the controller for an actual grid 1000 MW HVDC link reinforcement project called ''Midi-Provence'' in the southern part of the French grid. The synthesis , implementation and validation processes are presented in detail. The new controller is tested in comparison with the standard vector control. A large-scale dynamic model of the whole European power system, currently used and updated by the European TSO's for the interconnection studies has been used with Eurostag simulation software. Ó 2015 Elsevier Ltd. All rights reserved. Introduction The HVDC link is a mean of transmission of electric power based on high power electronics. Thanks to its speed and flexibility, the HVDC technology is able to provide the transmission system advantages as transfer capacity enhancement and power flow control [1]. Initially, it was used in power systems to interconnect asyn-chronous AC systems. The ends of the HVDC link are electrically independent one from each other and this reduces significantly the propagation of perturbations between the two AC grids as it is the case of the England–France interconnection [2]. Nowadays, HVDC links are increasingly embedded into a same meshed AC system in order to enhance the grid's transmission capability and flexibility of the power system. In this context, the HVDC link co-exists with other AC system elements as for instance AC lines and generators. Several projects of insertion of this type of device in a meshed AC system are underway in Europe, as for instance France–Spain HVDC project [3], France–Italy interconnection and Midi-Provence HVDC project [4]. This latter is our case of study. In fact, a 1000 MW HVDC link will be inserted in France between the two areas Fos and Gaudière, in order to enhance capacity of power transmission and the stability of the Midi-Provence region. The need of such HVDC link is due to the fact that only one single 400 kV AC line interconnects the two areas (see Fig. 1). It was shown that the strategy used to control the HVDC converters can impact the stability of the system in which the link is embedded [5–12]. This conducted us develop a methodology which takes into account, in a control model, the neighbor zone of the HVDC link and the dynamics that most impact transient stability. This control model captures the dynamics that are relevant for the transient stability of the power system. The controller synthesis is done on the base of this control model. As a consequence, power system performances are enhanced in addition to local performances. Preliminary results have been presented in [13]. This approach is fully developed here in order to take into account some key critical fault situations at the synthesis stage using the robust H 1 theory. Also the methodology is adapted to handle realistic large-scale cases as the European power system. As a matter of fact, in other papers [14,15], the transient stability is considered as an a priori objective for the synthesis of coordinated controllers for HVDC. However, the effectiveness of these methods had not been proved in the case http://dx.

Standalone dc microgrid faces a significant reliability risk due to continuous variation in power from renewable energy generation and the load demand. Usually, the output power from the renewable generators fluctuates with the weather conditions. The load is also varying all the time. This leads to a continuous risk of power mismatch in the system. Thus, a complementary generation or a storage system is required for maintaining the power balance in the system. This paper introduces a supervisory power management strategy (PMS) for a standalone dc microgrid with multiple distributed generations, load, and a battery energy storage system. The PMS is designed based on the model predictive control (MPC) approach. The complete mathematical model of the system has been developed, and it has been utilized in the MPC controller to solve an optimization problem with operating constraints. A forecasting technique is also incorporated in the proposed MPC to predict the environmental and load demand parameters. Simulation results illustrate the effectiveness of the presented MPC-based power management approach. Accordingly, the proposed approach effectively manages the power among the generators, load, and the battery and stabilizes the dc voltage. The paper also evaluates the effects of various prediction methods on the controller performance.

The penetration of high-level wind power has significantly made the power system's operation complicated. The random power variation of the wind farms may deteriorate the power system's transient stability degree since it alters the operating state of the power system. In this paper, based on trajectory sensitivity and Extended Equal Area Criterion (EEAC) method, a new preventive control approach is proposed to optimally balance the wind power variation by rescheduling synchronous generators while maintaining the transient stability for credible contingencies. The whole problem is formulated to a programming problem with linear stabilization constraints. The proposed method is validated on the New-England 10-machine 39-bus system by using commercial simulation software Transient Security Assessment Tool (TSAT), and both single- and multiple-contingency cases are tested. Simulation results verify its satisfactory performance on control effectiveness, computational efficiency, transparency, and accuracy. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) The work in this paper was supported in part by Ministry of Education (MOE), Republic of Singapore, under grant AcRF TIER 1 2019-T1-001-069 (RG75/19), and in part by National Research Foundation (NRF) of Singapore under project NRF2018-SR2001-018. Y. Xu’s work is supported by Nanyang Assistant Professorship from Nanyang Technological University, Singapore.

Though extensive, the literature on electrical load forecasting lacks reports on studies focused on existing residential micro-neighbourhoods comprising small numbers of single-family houses equipped with solar panels. This paper provides a full description of an ANN-based model designed to predict short-term high-resolution (15-min intervals) micro-scale residential net load profiles. Since it seems especially relevant due to the specificity of local autocorrelations in load signal, in this paper we put stress on the systematic approach to feature selection in the context of lagged signal. We performed a case study of a real micro-neighbourhood comprising only 75 single-family houses. The obtained average prediction error was equivalent to 5.4 per cent of the maximal measured net load. The issues, i.e.: (1) the feasibility of micro-scale residential load forecasting taking into account renewable energy penetration, (2) the feasibility to predict net load with dense temporal resolution of 15 min, (3) the feature selection problem, (4) the proposed prosumption- and comparison-oriented prediction model key performance measure, could be of interest to engineers designing energy balancing systems for local smart grids. �� 2019 The Authors

This paper develops a novel hybrid algorithm for solving transmission expansion planning (TEP) problems in electric power networks. Raising the awareness about immense contaminants produced by fossil fuels as well as depleting these resources have pushed energy companies toward considering more renewable energy resources (RERs). The RESs are beneficial for the society and the power system utility, however, taking into account the uncertainties, which are inherent in RERs, increase the complexity of the optimization problems. In this work, a Monte-Carlo simulation (MCS) is used to address the intermittent nature of wind energy. To handle the resulted model, by modifying and combining three well-known evolutionary algorithms such as shuffled frog leaping algorithm (SFLA), particle swarm optimization (PSO), and teaching learning-based optimization (TLBO), a potent hybrid MSFLA-MPSO-MTLBO, namely combinatorial heuristic-based profound-search algorithm (CHPSA), is proposed. A self-adaptive probabilistic mutation operator (SAPMO) is employed to enhance the effectiveness and computational efficiency of the CHPSA. Ten commonly-used benchmark problems are introduced to corroborate the performance of the CHPSA, while the IEEE RTS 24-bus test system is used to validate the model. Results show that the proposed CHPSA is capable of obtaining better solutions than other algorithms, either implemented in this paper or borrowed from the literature.

This paper develops a methodology to determine the impacts of high penetration level of fully electric vehicles (FEVs) charging loads on the thermal ageing of power distribution transformers. The method proposed in this paper is stochastically formulated by modelling the transformer life consumption due to FEVs charging loads as a function of ambient temperature, start time of FEVs charging, initial state-of-charge and charging modes. FEVs loads are modelled using the results from an analytical solution that predicts a cluster of FEVs chargers. A UK generic LV distribution network model and real load demand data are used to simulate FEVs’ impacts on the thermal ageing of LV power distribution transformers. Results show that the ambient temperature, FEVs penetration level, and start time of charging are the main factors that affect the transformer life expectancy. It was concluded that the smart charging scenario generally shows the best outcome from the loss of life reduction perspective. Meanwhile, public charging which shifts a large percentage of charging load to commercial and industrial areas can significantly alleviate the residential transformer loading thus has little impact on the loss of life of transformers. The proposed method in this paper can be easily applied to the determination of the optimum charging time as a function of existing loads, and ambient temperature.

Because of their small scale and large share of intermittent power sources, islanded microgrids require additional means of flexibility, such as dedicated storage. For controlling the loads and distributed generation (DG) units in an islanded microgrid, the voltage-based droop (VBD) control has been developed. This controller determines the switching actions of these units’ power electronic interfaces in order to ensure a stable islanded microgrid operation. In this paper, the VBD control is extended for storage applications, taking into account the state of charge. As the VBD control automatically fixes the priority of power changes of the microgrid elements, the storage elements are included in this priority list without inter-unit communication. This benefits the coordinated integration of DG units in the system. Simulation examples are included illustrating the transient and dynamic response of the VBD control of all grid assets. The paper also provides an experimental validation of the VBD control for both the DG units and the storage elements in an islanded microgrid.

A power outage brings in economic losses for both the customers and the utilities. Studying these unwanted events and making solid predictions about the outcomes of the interruptions has been an attractive area of interest for the researchers for the last couple of decades. By making use of a customer survey study conducted in Finland, this paper benefits from both the reported cost data collected from customers and from the analytical data that are available and then presents a new hybrid approach to estimate the customer interruption costs of service sector customer segment. Making use of Value Added information of the customers is a common practice for the cost normalization purposes. This paper verifies the approach by comparing the findings of the customer survey and the econometric model suggested here. This study is a unique source in terms of providing a reliable, easy to apply, and a straightforward model for calculating the economic impacts of power outages.

It is often necessary to investigate the output power against load demand in a system having distributed generation (DG) resources connected to the existing conventional power system. In this paper, the load frequency control (LFC) problem is presented using different optimization algorithms for two types of power system configurations: (i) hybrid configuration of thermal power system (TPS) integrated with DG, comprising wind turbine generators (WTGs), diesel engine generators (DEGs), fuel cells (FCs), aqua-electrolyzer (AE) and battery energy storage system (BESS); (ii) two area interconnected power system with DG connected in area-1. The inclusion of wind energy system in DG, having high variability in its output power, results into a challenging task for the realization of an effective controller design. This difficulty is further enhanced with random variation of load demand. The control scheme proposed in this paper is based on linear matrix inequalities (LMI) with its parameters tuned by particle swarm optimization (PSO), as a new contribution to earlier studies. The robustness of this controller is thoroughly demonstrated in the above hybrid power systems with different conditions of load disturbances, wind power and parameter variations.

This survey paper is an excerpt of a more comprehensive study on Smart Grid (SG) and the role of Advanced Metering Infrastructure (AMI) in SG. The survey was carried out as part of a feasibility study for creation of a Net-Zero community in a city in Ontario, Canada. SG is not a single technology; rather it is a combination of different areas of engineering, communication and management. This paper introduces AMI technology and its current status, as the foundation of SG, which is responsible for collecting all the data and information from loads and consumers. AMI is also responsible for implementing control signals and commands to perform necessary control actions as well as Demand Side Management (DSM). In this paper we introduce SG and its features, establish the relation between SG and AMI, explain the three main subsystems of AMI and discuss related security issues.

Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific programs in the LMP values supports the manager decision concerning the DR use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 33-bus network with intensive use of DG.

Gravitational search algorithm (GSA) is based on law of gravity and the interaction between masses. In GSA, searcher agents are collection of masses and their interactions are based on Newtonian laws of gravity and motion. In this paper, to further improve the optimization performance of GSA, opposition-based learning is employed in opposition-based gravitational search algorithm (OGSA) for population initialization and also for generation jumping. In the present work, OGSA is applied for the solution of optimal reactive power dispatch (ORPD) of power systems. Traditionally, ORPD is defined as the minimization of active power transmission losses by controlling a number of control variables. ORPD is formulated as a non-linear constrained optimization problem with continuous and discrete variables. In this work, OGSA is used to find the settings of control variables such as generator voltages, tap positions of tap changing transformers and amount of reactive compensation to optimize certain objectives. The study is implemented on IEEE 30-, 57- and 118-bus test power systems with different objectives that reflect minimization of either active power loss or that of total voltage deviation or improvement of voltage stability index. The obtained results are compared to those yielded by the other evolutionary optimization techniques surfaced in the recent state-of-the-art literature including basic GSA. The results presented in this paper demonstrate the potential of the proposed approach and show its effectiveness and robustness for solving ORPD problems of power systems.

This paper presents a methodology for the integration of dispatchable and nondispatchable renewable distributed generation (DG) units for minimizing annual energy losses. In this methodology, analytical expressions are first proposed to identify the optimal size and power factor of DG unit simultaneously for each location for minimizing power losses. These expressions are then adapted to place renewable DG units for minimizing annual energy losses while considering the time-varying characteristics of demand and generation. A combination of dispatchable and nondispatchable DG units is also proposed in this paper. The proposed methodology has been applied to a 69-bus test distribution system with different scenarios. The results demonstrate that dispatchable DG units or a combination of dispatchable and nondispatchable DG units can lead to a substantial reduction in annual energy losses when compared to nondispatchable DG units. The results also show that a maximum annual energy loss reduction is achieved for all scenarios proposed with DG operation at optimal power factor. (C) 2013 Elsevier Ltd. All rights reserved.

Permanent Magnet Synchronous Machines (PMSMs) have several advantages, such as high ef¿ciency and low volume and weight, which make them attractive for aerospace applications and high performance servo drives. Matrix Converters (MCs) are an all-silicon alternative, with no bulky reactive elements, to the standard voltage source inverter. The most common control technique for such PMSM MC-fed drives is the so-called Field-Oriented Control (FOC), which requires the permanent magnet ¿ux position to achieve high dynamic performance. Encoders or resolvers are the most common sensing devices used for such a purpose, which not only increases the total cost of the PMSM drive but also adds extra electronics and cabling that may cause failures. This paper investigates and proposes an all range (from zero to full) speed hybrid sensorless FOC. The novelty of this paper relies on the use of a hybrid sensorless four quadrant FOC that averages the needed angle estimation from a model based angle estimator and a voltage pulse test injection angle estimator when feeding the PMSM with an MC instead of a standard voltage source inverter. Speed reversal and load impact simulation results are included, fully supporting the claims made in this paper

This paper investigates the critical parameters of power systems which affect the stability of the system. The analysis is conducted on both a single machine infinite bus (SMIB) system and a large multimachine system with dynamic loads. To further investigate the effects of dynamic loads on power system stability, the effectiveness of conventional as well as modern linear controllers is tested and compared with the variation of loads. The effectiveness is assessed based on the damping of the dominant mode and the analysis in this paper highlights the fact that the dynamic load has substantial effect on the damping of the system.

That the new generation power system control centers need a paradigm shift in their architectural design to meet new challenges, is an established conclusion of many researchers. However, literature on comprehensive architectural design towards this direction is scarce. In this paper, an information architecture design is proposed for the power system control centers. Appropriate adoption of open standards such as the common information model (CIM) is endorsed. Further, initial development of an event information model for modeling high level power system events is mentioned. Proposed architecture focuses on the desired features such as openness, interoperability, flexibility, scalability, vendor independence and event orientation. The architecture comprises services arranged in layers, viz., data integration and access, event processing and plug-in services. The details of this architecture along with the intricate relationships between various layers and services depicting how the technologies could be integrated into a coherent whole are described in this paper. An illustrative example, from the Indian power sector domain has been used to demonstrate the usefulness of the proposed architecture. (C) 2011 Elsevier Ltd. All rights reserved.

Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent®, GARP3® and DSA–GD software. A multi-objective approach based on the Bellman–Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder.

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

This is the post-print version of the final paper published in International Journal of Electrical Power & Energy Systems. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V. This paper proposes a new algorithm for estimating voltage security margin. The algorithm is based on the perturbation method and has significant computational efficiency. The proposed algorithm can be used for on-line voltage security evaluation. It has been validated using IEEE-14, IEEE-30 and IEEE-57 bus systems. Results from the tests show higher efficiency and smaller error margins compared to continuation power flow (CPF) method. Voltage collapse is a serious threat to the security of stressed power systems; therefore, voltage security (VS) has become a major challenge for management of power systems. The motivation for this research is a direct consequence of the deregulation of electricity industries and markets worldwide.

In restructured electricity markets, electricity retailers set up contracts with generation companies (GENCOs) and with end users to meet their load requirements at agreed upon tariff. The retailers invest consumer payments as capital in the volatile competitive market. In this paper, a model for quantifying price risk of electricity retailer is proposed. An IEEE 30 Bus test system is used to demonstrate the model. The Capital Asset Pricing Model (CAPM) is demonstrated to determine the retail electricity price for the end users. The factor Risk Adjusted Recovery on Capital (RAROC) is used to quantify the price risk involved. The methodology proposed in this paper can be used by retailer while submitting proposal for electricity tariff to the regulatory authority.

The new electric system restructuring requires more and more restrictive power quality requirements to be satisfied. The problem of disturbances compensation therefore becomes of noticeable importance, both in terms of device allocation and control strategy. The paper deals with active compensators, whose utilization is rapidly growing in modern power system, whereas power electronic devices play a fundamental role in controlling system behavior. An optimal control strategy for active compensators, particularly useful for distribution companies in a deregulated framework, is proposed with the aim of improving power quality. The proposed strategy is based upon a frequency domain approach for solving a linear quadratic regulator problem, without exceeding compensator rating. The proposed procedure is able to properly consider the buses sensitivity to different power quality disturbances. The methodology relies upon a Kalman filter based estimation technique, which enables an accurate tracking of relevant network state variables, as well as of harmonic disturbances injected into the power system. In the last part of the paper a numerical application with reference to a 18-busbar distribution network is presented, showing the feasibility and the effectiveness of the proposed methodology.

Recent developments indicate that Artificial Neural Networks (ANNs) may be appropriate for assisting dispatchers in operating electric power systems. The fault location algorithm being a key element in the digital relay for power transmission line protection, this paper discusses the potential applicability of ANN techniques for determination of fault location and fault resistance on EHV transmission lines with remote end in-feed. Most of the applications make use of the conventional Multi Layer Perceptron (MLP) model based on back propagation algorithm. However, this model suffers from the problem of slow learning rate. A modified ANN learning technique for fault location and fault resistance determination is presented in this paper. A reasonably small NN is built automatically without guessing the size, depth, and connectivity pattern of the NN in advance. Results of study on a 400 kV transmission line are presented for illustration purposes. Performance of the modified ANN is compared with the analytical algorithms and conventional MLP algorithm for different combinations of pre-fault loading condition, fault resistance and fault location. The results are found to be encouraging.

This paper develops a coarse-grain parallel genetic algorithm for solving a service restoration problem in electric power distribution systems. Service restoration is performed to restore electricity for out-of-service areas. Developing effective service restoration procedures is a cost-effective approach to improving service reliability and enhancing customer satisfaction. The main objective in service restoration procedures is to restore as much load as possible by transferring de-energized loads via network reconfigurations to other supporting distribution feeders without violating operating and engineering constraints. Details of the parallel genetic algorithm developed in this paper are described. The proposed method is implemented on transputers for parallel computations. The feasibility of the developed algorithm for service restoration is demonstrated on several distribution networks with promising results.

This paper presents the analysis and study of voltage collapse at any converter bus in an AC system interconnected by multiterminal DC (MTDC) links. The analysis is based on the use of the voltage sensitivity factor (VSF) as a voltage collapse proximity indicator (VCPI). In this paper the VSF is defined as a matrix which is applicable to MTDC systems. The VSF matrix is derived from the basic steady state equations of the converter, control, DC and AC networks. The structure of the matrix enables the derivation of some of the basic properties which are generally applicable. A detailed case study of a four-terminal MTDC system is presented to illustrate the effects of control strategies at the voltage setting terminal (VST) and other terminals. The controls considered are either constant angle, DC voltage, AC voltage, reactive current and reactive power at the VST and constant power or current at the other terminals. The effect of the strength of the AC system (measured by short circuit ratio) on the VSF is investigated. Several interesting and new results are presented. An analytical expression for the self VSF at VST is also derived for some specific cases which help to explain the number of transitions in VSF around the critical values of SCR.

Autonomous microgrids are a suitable solution for off-grid electrification in terms of costs and reliability. The correct sizing of its generation and storage systems ensures efficient utilization of the available energy resources. Generally, many sizing approaches assume optimized energy management strategies that rely on central control architectures. However, these architectures are not always available, especially in limited investment microgrid projects. For this reason, the study of operation scenarios based on decentralized control strategy such as droop control is relevant. Based on this, this paper aims to evaluate the impact of the droop control over the sizing results of a solar/wind/battery/diesel microgrid. For this purpose, a case study of a sizing problem is presented, including the formulation and modelling. Results are presented comparing an hourly optimized energy management scenario with multiple values of the droop control parameters. Simulations results indicate that a competitive total cost can be obtained if the droop parameters are calculated considering the microgrid sizing results. Based on this, a generalizable design methodology for this purpose is presented.

Data interruption may cause the centralized energy management system of a microgrid (MG) to collapse. To solve this problem, a hybrid prediction-based energy management strategy is proposed in this paper to predict interrupted data for the centralized dispatching process of an MG. This hybrid prediction method is designed following a combination of model predictive control and extreme learning machine techniques. Based on the predicted data of distributed energy resources and three types of loads from demand-side response, an optimization model is formulated to minimize the operational cost. If some predicted data are interrupted during transmission, then a prospect vulnerability assessment method is applied to select a neighboring device to predict the interrupted data. In the end, an improved particle swarm optimization algorithm is proposed with the help of genetic algorithms to accelerate convergence to global optimal solutions for the proposed MG energy management problem. The effectiveness of the proposed models and solution methods is also verified by a case study.