Showing papers in "Iet Generation Transmission & Distribution in 2014"
TL;DR: This study presents a scheduling algorithm for EVs under a real time pricing scheme with uncertainty that explicitly takes into account the cost of battery degradation not only when used to provide services to the system but also in terms of the EV utilisation for motion.
Abstract: It is expected that electric vehicles (EVs) will soon represent a large share of the demand for electricity. Several research works have extolled the advantages of these devices as flexible demands, not only to charge their batteries when it is cheaper to do so, but also to provide services in the form of vehicle-to-grid (V2G) power injections to the system. These services, however, could reduce the useful life of the battery and thus introduce a cost that needs to be taken into account when scheduling the charging of these vehicles. This study presents a scheduling algorithm for EVs under a real time pricing scheme with uncertainty. The objective function explicitly takes into account the cost of battery degradation not only when used to provide services to the system but also in terms of the EV utilisation for motion. The results show that the scheduling of the V2G services is sensitive to the electricity prices uncertainty and to the degradation costs derived from the energy arbitrage. Also, the optimal energy state of charge of the batteries is highly dependent on whether the cost of battery degradation is taken into account or not.
276 citations
TL;DR: In this paper, a differential scheme for microgrid protection using time-frequency transform such as S-transform was proposed to register the fault patterns in the microgrid at grid-connected and islanded mode.
Abstract: The study presents a differential scheme for microgrid protection using time-frequency transform such as S-transform Initially, the current at the respective buses are retrieved and processed through S-transform to generate time-frequency contours Spectral energy content of the time-frequency contours of the fault current signals are calculated and differential energy is computed to register the fault patterns in the microgrid at grid-connected and islanded mode The proposed scheme is tested for different shunt faults (symmetrical and unsymmetrical) and high-impedance faults in the microgrid with radial and loop structure It is observed that a set threshold on the differential energy can issue the tripping signal for effective protection measure within four cycles from the fault inception The results based on extensive study indicate that the differential energy-based protection scheme can reliably protect the microgrid against different fault situations and thus, is a potential candidate for wide area protection
187 citations
TL;DR: In this article, a probabilistic power flow (PPF)-embedded genetic algorithm (GA)-based approach is proposed in order to solve the optimisation problem that is modelled mathematically under a chance constrained programming framework.
Abstract: The scope of this study is the optimal siting and sizing of distributed generation within a power distribution network considering uncertainties. A probabilistic power flow (PPF)-embedded genetic algorithm (GA)-based approach is proposed in order to solve the optimisation problem that is modelled mathematically under a chance constrained programming framework. Point estimate method (PEM) is proposed for the solution of the involved PPF problem. The uncertainties considered include: (i) the future load growth in the power distribution system, (ii) the wind generation, (iii) the output power of photovoltaics, (iv) the fuel costs and (v) the electricity prices. Based on some candidate schemes of different distributed generation types and sizes, placed on specific candidate buses of the network, GA is applied in order to find the optimal plan. The proposed GA with embedded PEM (GA-PEM) is applied on the IEEE 33-bus network by considering several scenarios and is compared with the method of GA with embedded Monte Carlo simulation (GA-MCS). The main conclusions of this comparison are: (i) the proposed GA-PEM is seven times faster than GA-MCS, and (ii) both methods provide almost identical results.
170 citations
TL;DR: In this article, a cuckoo search optimisation-based approach has been developed to allocate static shunt capacitors along radial distribution networks to minimize the system operating cost at different loading conditions and to improve the system voltage profile.
Abstract: In the present work, a cuckoo search optimisation-based approach has been developed to allocate static shunt capacitors along radial distribution networks. The objective function is adopted to minify the system operating cost at different loading conditions and to improve the system voltage profile. In addition to find the optimal location and values of the fixed and switched capacitors in distribution networks with different loading levels using the proposed algorithm. Higher potential buses for capacitor placement are initially identified using power loss index. However, that method has proven less than satisfactory as power loss indices may not always indicate the appropriate placement. At that moment, the proposed approach identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated with minimum number of effective locations and with lesser injected VArs. The overall accuracy and reliability of the approach have been validated and tested on radial distribution systems with differing topologies and of varying sizes and complexities. The results shown by the proposed approach have been found to outperform the results of existing heuristic algorithms found in the literature for the given problem.
156 citations
TL;DR: It is observed that the optimum gains of the proposed fuzzy PID controller need not be reset even if the system is subjected to variation in loading condition and system parameters, and the superiority of hybrid DEPSO algorithm over differential evolution and particle swarm optimisation algorithm has been demonstrated.
Abstract: A novel fuzzy proportional–integral derivative (PID) controller is proposed in this study for automatic generation control (AGC) of interconnected power systems. The optimum gains of the proposed fuzzy PID controller are optimised employing a hybrid differential evolution particle swarm optimisation (DEPSO) technique using an integral of time multiplied by absolute value of error criterion. The superiority of hybrid DEPSO algorithm over differential evolution and particle swarm optimisation (PSO) algorithm has also been demonstrated. The results are also compared with some recently published approaches such as artificial bee colony and PSO based proportional–integral/PID controllers for the same interconnected power systems. Furthermore, performance of the proposed system is analysed by varying the different parameters such as loading condition, system parameters and objective functions. It is observed that the optimum gains of the proposed fuzzy PID controller need not be reset even if the system is subjected to variation in loading condition and system parameters. Finally, the study is extended to a three area system considering generation rate constraint to demonstrate the ability of the proposed approach to cope with multiple interconnected systems. Comparison with previous AGC methods reported in the literature validates the significance of the proposed approach.
156 citations
TL;DR: An analytical method for placement and sizing of distributed generation on power distribution systems for loss reduction is introduced in this paper, which is non-iterative, direct, and involves no convergence issues even for systems with high R/X branch ratios.
Abstract: An analytical method for placement and sizing of distributed generation on power distribution systems for loss reduction is introduced. The proposed analytical method is developed based on a new formulation for the power flow problem, which is non-iterative, direct, and involves no convergence issues even for systems with high R/X branch ratios. Further, this power flow solution is extremely useful whenever fast and repetitive power flow estimations are required. A priority list based on loss sensitivity factors is developed to determine the optimal locations of the candidate distributed generation units. Sensitivity analysis is performed to estimate the optimal size and power factor of the candidate distributed generation units. Various types of distributed generators (DGs) have been dealt with and viable solutions are proposed to reduce total system loss. The proposed method has been tested on 33-bus and 69-bus distribution systems, which are extensively used as examples in solving the placement and sizing problem of DGs. Exhaustive power flow routines are also performed to verify the sizes obtained by the analytical method. The test results show that the proposed analytical method could lead to optimal or near-optimal solution, while requiring lower computational effort.
135 citations
TL;DR: In this article, an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators is presented, which considers reliability, operation cost and loss simultaneously.
Abstract: Power loss reduction can be considered as one of the main purposes for distribution system operators. Reconfiguration is an operation process used for this optimisation by means of changing the status of switches in a distribution network. Recently, all system operators tried their best in order to obtain well-balanced distribution systems to decrease the operation cost, improve reliability and reduce power loss. This study presents an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators. The conventional distribution feeder reconfiguration (DFR) problem cannot meet the reliability requirements, because it only considers loss and voltage deviation as objective functions. The proposed approach considers reliability, operation cost and loss simultaneously. By adding the reliability objective to the DFR problem, this problem becomes more complicated than before and it needs to be solved with an accurate algorithm. Therefore this study utilises an Enhanced Gravitational Search Algorithm called EGSA which profits from a special mutation strategy in order to reduce the processing time and improve the quality of solutions, particularly to avoid being trapped in local optima. The proposed approach has been applied to two distribution test systems including IEEE 33 and 70-node test systems.
132 citations
TL;DR: In this article, an up-down operation model of a hybrid AC-DC microgrid is proposed which consists of system-and device-level controllers for balancing the generation and load considering the interconnection of AC and DC subgrids for minimizing total operating cost of the system in a 24-hour period.
Abstract: Hybrid AC-DC microgrid is introduced as the future distribution network to utilise both benefits of alternative and direct currents. In such hybrid microgrid, AC and DC loads, renewable-based distributed generators (DGs), controllable DGs and energy storage systems are connected through separate AC and DC links. An up-down operation model of such hybrid microgrid is proposed which consists of system- and device-level. In the system-level, a mixed integer linear model is suggested to balance the generation and load considering the interconnection of AC and DC subgrids for minimising total operating cost of the system in a 24-hour period. In the device-level, a controller is suggested for power converter-based resources (i.e. intergrid inverter and battery) for controlling the voltage variations in AC and DC subgrids. The effectiveness of the proposed up-down operation model is demonstrated through simulation studies on a test hybrid microgrid.
129 citations
TL;DR: In this article, a multi-objective stochastic optimal planning method for a stand-alone microgrid consisting of diesel generators, wind turbine generators, photovoltaic generation system and lead-acid batteries is presented.
Abstract: To achieve economic and environmental benefit for the stand-alone microgrid consisting of diesel generators, wind turbine generators, photovoltaic generation system and lead-acid batteries, a multi-objective stochastic optimal planning method and a stochastic chance-constrained programming model are presented. In the model, the optimal objective is to simultaneously minimise the total net present cost and carbon dioxide emission in life cycle; the type and capacity of distributed generation units have been selected as the optimal variables; the loss of capacity is adopted as probability index constraint; the coordinated operation strategies between diesel generators and battery, the multi-unit operation constraints of diesel generators and the reserve capacity have been considered in the hard-circle operation strategy. Considering the uncertainties of wind speed, clearness index and load demand, Markov process transition probability matrix is adopted to synthesise those time series data. Optimal planning for an island microgrid system has been carried out by the planning system for microgrid (PSMG), a self-developed optimal planning software based on the multi-objective stochastic optimal planning method for stand-alone microgrid system.
123 citations
TL;DR: In this paper, the authors proposed a methodology to assess the effect of wind power production on the flexibility requirements of a power system and demonstrated that they are best captured by non-parametric statistics, which is used to determine simultaneously the hourly flexibility requirements at a given probability level for large and small, continuous and discrete disturbances.
Abstract: This study proposes a methodology to assess the effect of wind power production on the flexibility requirements of a power system. First, the study describes the probabilistic characteristics of the intra-hour net load variability and demonstrates that they are best captured by non-parametric statistics. Then, this non-parametric approach is used to determine simultaneously the hourly flexibility requirements at a given probability level for large and small, continuous and discrete disturbances. This approach allocates the required flexibility among primary, secondary and tertiary regulation intervals. The usefulness of this method is then illustrated using actual 1 min resolution net load data, which has been clustered to take advantage of seasonal and daily differences in flexibility requirements.
113 citations
TL;DR: In this paper, a hierarchical control structure is discussed for interconnecting the neighbor autonomous MGs where the introduced primary control level is the main focus of this study, which demonstrates how the parallel DERs in the system of multiple interconnected autonomous MG can properly share the load of the system.
Abstract: To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.
TL;DR: In this paper, a voltage stability constrained optimal power flow (VSC-OPF) approach based on static line voltage stability indices was proposed to simultaneously improve voltage stability and minimise power system losses under stressed and contingency conditions.
Abstract: Voltage stability improvement is a challenging issue in planning and security assessment of power systems. As modern systems are being operated under heavily stressed conditions with reduced stability margins, incorporation of voltage stability criteria in the operation of power systems began receiving great attention. This study presents a novel voltage stability constrained optimal power flow (VSC-OPF) approach based on static line voltage stability indices to simultaneously improve voltage stability and minimise power system losses under stressed and contingency conditions. The proposed methodology uses a voltage collapse proximity indicator (VCPI) to provide important information about the proximity of the system to voltage instability. The VCPI index is incorporated into the optimal power flow (OPF) formulation in two ways; first it can be added as a new voltage stability constraint in the OPF constraints, or used as a voltage stability objective function. The proposed approach has been evaluated on the standard IEEE 30-bus and 57-bus test systems under different cases and compared with two well proved VSC-OPF approaches based on the bus voltage indicator L - index and the minimum singular value. The simulation results are promising and demonstrate the effectiveness of the proposed VSC-OPF based on the line voltage stability index.
TL;DR: A probabilistic load flow (PLF) method using Copula and improved Latin hypercube sampling is proposed and the accuracy of probability distribution of correlated input random variables established by Copula theory is evaluated by adopting the power output of wind farms located at New Jersey.
Abstract: A probabilistic load flow (PLF) method using Copula and improved Latin hypercube sampling is proposed. The stochastic dependence between input random variables is considered. Copula theory is adopted to establish the probability distribution of correlated input random variables. Based on discrete data, an improved Latin hypercube sampling is proposed. The accuracy of probability distribution of correlated input random variables established by Copula theory is evaluated by adopting the power output of wind farms located at New Jersey. The performance of the proposed PLF method is investigated using IEEE 14-bus and IEEE 118-bus test systems.
TL;DR: In this article, the potential impacts of demand response on major attributes of service reliability in a residential distribution network are comprehensively assessed and the proposed framework is applied to Finnish distribution system and the obtained results demonstrate the efficiency and applicability of the proposed approach in real world systems.
Abstract: Demand response (DR) as a key integral part of the future smart grid is gaining a great and still growing focus of attention in nowadays electric power industries. However, many potential benefits of DR, although they have been envisioned to be significant, have not been yet thoroughly and quantitatively investigated. DR provides network operators with the opportunity to mitigate operational limit violations by load modification in place of load shedding when network reliability is jeopardised. This paper aims to comprehensively assess the potential impacts of DR on major attributes of service reliability in a residential distribution network. For doing so, firstly, load profiles for major residential appliances are extracted from grossly metered consumptions. Secondly, the flexibility associated with individual load profiles is estimated using the statistical data gathered through surveys and questionnaires. Thirdly, for every contingency, appliance level load profiles are modified based on their flexibilities such that the least possible interruption cost is realised. The obtained results are finally combined to calculate service reliability indices. The proposed framework is applied to Finnish distribution system and the obtained results demonstrate the efficiency and applicability of the proposed approach in real-world systems.
TL;DR: In this article, a multi-objective tabu search algorithm is proposed to solve the multistage planning problem of a distribution system formulated as a multiobjective dynamic mixed integer non-linear programming problem.
Abstract: This study presents a multiobjective tabu search algorithm to solve the multistage planning problem of a distribution system formulated as a multiobjective dynamic mixed integer non-linear programming problem. Multiobjective problems do not have a specific solution, but a set of solutions that allows us to observe the trade-off among the analysed objectives. Taking into account this concept, the objective functions of the model proposed in this study are: costs (investment and operational) and reliability. The actions deemed in this model for each period of the planning horizon are: increase in the capacity of existing substations (or construction of new ones), exchange of cables in existing lines (and construction of new feeders), reconfiguration of the network, allocation of sectionalising switches and construction of tie lines. The system's reliability is evaluated by means of the non-supplied energy under contingencies using the n − 1 criterion. By line switching and the use of tie lines, part of the loads affected by a contingency can be restored, thus, the non-supplied energy can be evaluated by solving a distribution network restoration problem. Numerical results are presented for a 54-bus system.
TL;DR: In this paper, a tractable mixed-integer linear programming model for multi-year transmission expansion planning (TEP) problem coping with the uncertain capital costs and uncertain electricity demands using the information gap decision theory (IGDT) is presented.
Abstract: This study presents a novel tractable mixed-integer linear programming model for multiyear transmission expansion planning (TEP) problem coping with the uncertain capital costs and uncertain electricity demands using the information-gap decision theory (IGDT). As the uncertain capital costs and electricity demands compete to occupy the permissible uncertainty budget, the proposed IGDT-based TEP (IGDT-TEP) framework employs the augmented e-constraint method to solve a multi-objective optimisation problem maximising the robust regions against the uncertain variables (i.e. capital costs and electricity demands) centred on their forecasted values. This framework enables the system's planner to control the immunisation level of the optimal expansion plan regarding the enforced planning uncertainties using a certain uncertainty budget. Also, a Latin hypercube sampling-based post-optimisation procedure is introduced to evaluate the robustness of an expansion plan obtained from the proposed IGDT-TEP framework. Simulation results demonstrate the effectiveness of the IGDT-TEP model to handle the uncertain nature of capital costs and electricity demands.
TL;DR: In this paper, a scalable real-time scheduling scheme for EV charging in lowvoltage residential distribution system is proposed, which shifts from voltage safety-oriented to loss-minimisation-oriented, or vice versa, on demand of the EV penetration level.
Abstract: Unscheduled charging of plenty of electric vehicles (EVs) might exert an adverse effect on the existing power grid, especially when the charging coincides with daily peak load at distribution level. In this study, a scalable real-time scheduling scheme for EV charging in low-voltage residential distribution system is proposed. Since most often, voltage drop would become a binding constraint when a distribution feeder is subject to a high EV penetration level, a scheduling method is first developed to increase the voltage safety margin. Then, a novel factor is derived to allow the scheduling to shift from voltage-safety-oriented to loss-minimisation-oriented, or vice versa, on demand of the EV penetration level. A number of charging scenarios were simulated to evaluate the proposed scheduling scheme. Simulation results verified that the proposed scheduling scheme is fast and efficient with circuit losses close to optimal at a low EV penetration level and voltage drops maintained within the tolerable limit at a high EV penetration level. The high scalability and effectiveness of the proposed scheme has made it suitable for coordinating large number of EV charging activities in real-time.
TL;DR: In this paper, a new adaptive digital relaying scheme for power distribution network containing distributed generations (DGs) is presented, which circumvents miscoordination between recloser and fuse.
Abstract: Nuisance fuse blowing because of miscoordination between fuse and recloser in power distribution network is very critical issue particularly when distributed generations (DGs) are incorporated. This study presents a new adaptive digital relaying scheme for power distribution network containing DG, which circumvents miscoordination between recloser and fuse. It is based on calculation of the ratio of feeder current and recloser current. With the help of this philosophy, the proposed scheme automatically modifies the time dial setting of the relay and hence enhances margin between fuse and recloser in order to avoid miscoordination between fuse and recloser. The proposed scheme has been extensively tested for various types of faults in radial distribution network containing DG. Fault data are generated by modelling an existing part of 11 kV Indian power distribution network using PSCAD/EMTDC software package. Furthermore, the impact of different DG capacities on the margin (coordination) between fuse and recloser are also analysed. It has been observed that the proposed scheme maintains proper coordination between fuse and recloser for all types of fault. Moreover, it also provides satisfactory operation during high resistance single line-to-ground faults.
TL;DR: In this paper, the authors present a step-by-step tutorial on modal analysis of a doubly-fed induction generator (DFIG)-based series compensated wind farm, which includes a wind turbine aerodynamics, a second-order two-mass shaft system, a fourth-order order series compensated transmission line, an eighth-order rotor side converter (RSC) and grid-side converter (GSC) controllers, and a first-order DC-link model.
Abstract: This paper first presents a step-by-step tutorial on modal analysis of a doubly-fed induction generator (DFIG)-based series compensated wind farm. The model of the system includes a wind turbine aerodynamics, a sixth-order order induction generator, a second-order two-mass shaft system, a fourth-order order series compensated transmission line, an eighth-order rotor-side converter (RSC) and grid-side converter (GSC) controllers, and a first-order DC-link model. Then, using modal analysis and time-domain simulations, it is shown that a fixed-series compensated DFIG is highly unstable due to the sub-synchronous resonance (SSR) mode. In order to damp the SSR mode, the wind farm is interfaced with the gate-controlled series capacitor (GCSC) - which is a new series flexible AC transmission system (FACTS) device. A SSR damping controller (SSRDC) is designed for the GCSC using residue-based analysis and root locus diagrams, and an effective input control signal (ICS) to the SSRDC is identified in order to simultaneously increase damping of both the SSR and super-synchronous (SupSR) modes. The IEEE first benchmark model on SSR is adapted with an integrated DFIG-based wind farm to perform studies. Matlab/Simulink is used as a tool for designing process, and PSCAD/EMTDC is used for time-domain simulations.
TL;DR: In this article, a combined economic emission dispatch (CEED) is employed to investigate the effectiveness of using plug-in electric vehicles and integrating renewable energy sources (RESs) from different aspects.
Abstract: Transportation and electricity industries are considered as major sources of greenhouse gases (GHGs) emission. Different methods have been proposed to deal with the increasing rate of the emission, such as employing plug-in electric vehicles (PEVs) and integrating renewable energy sources (RESs). However, it is important to scrutinise different scenarios of incorporating the mentioned elements to decrease the concerning emission rate while considering the economic constraints. In this study, a combined economic emission dispatch (CEED) is employed to investigate the effectiveness of using PEVs and RESs from different aspects. A sensitivity analysis is executed to survey the influence of emission and cost coefficients. Two test cases each including different scenarios are simulated to determine the efficacy of different types of integration in the proposed model. To have a more accurate and realistic survey, an extended model of the wind farm's cost function is employed in economic dispatch calculations. The particle swarm optimisation algorithm is applied to solve the CEED non-linear problem. The obtained results indicate that the integration of PEVs cannot necessarily reduce the net emission of two industries. In fact, the optimum solution should include the incorporation of PEVs along with RESs to return the desired results.
TL;DR: In this article, a real-time transient stability assessment (TSA) approach based on prediction of area-based center-of-inertia (COI) referred rotor angles from phasor measurement unit (PMU) measurements is presented.
Abstract: Several smart grid applications have recently been devised in order to timely perform supervisory functions along with self-healing and adaptive countermeasures based on system-wide analysis, with the ultimate goal of reducing the risks associated with potentially insecure operating conditions. Real-time transient stability assessment (TSA) belongs to this type of applications, which allows deciding and coordinating pertinent corrective control actions depending on the evolution of post-fault rotor-angle deviations. This study presents a novel approach for carrying out real-time TSA based on prediction of area-based centre-of-inertia (COI) referred rotor angles from phasor measurement unit (PMU) measurements. Monte Carlo-based procedures are performed to iteratively evaluate the system transient stability response, considering the operational statistics related to loading condition changes and fault occurrence rates, in order to build a knowledge database for PMU and COI-referred rotor-angles as well as to screen those relevant PMU signals that allows ensuring high observability of slow and fast dynamic phenomena. The database is employed for structuring and training an intelligent COI-referred rotor-angle regressor based on support vector machines [support vector regressor (SVR)] to be used for real-time TSA from selected PMUs. Besides, the SVR is optimally tuned by using the swarm variant of the mean-variance mapping optimisation. The proposal is tested on the IEEE New England 39-bus system. Results demonstrate the feasibility of the methodology in estimating the COI-referred rotor angles, which enables alerting about real-time transient stability threats per system areas, for which a transient stability index is also computed.
TL;DR: In this paper, the application of energy storage connected to the lowvoltage microgrid by coupling inverter for simultaneous energy management and ancillary services that include the compensation of power quality disturbances is discussed.
Abstract: The study deals with the application of energy storage connected to the low-voltage microgrid by coupling inverter for simultaneous energy management and ancillary services that include the compensation of power quality disturbances. The usefulness of storage equipment as a solution to various problems that accompany microgrid development is discussed. Then, the idea is presented to join different tasks the storage can perform in one application. Control algorithm is presented for storage inverter, which enables storage unit to be charged or discharged according to assumed schedule and to contribute to power quality improvement through the compensation of reactive power, current harmonics and unbalance. Effectiveness of compensation is examined on the simulation model of test microgrid. Moreover, the results of tests performed in real test microgrid configured in the Laboratory of Distributed Generation at the Lodz University of Technology are presented in the study.
TL;DR: In this paper, the authors proposed a fault location method for power distribution system (PDS) in which the measured and recorded samples of voltages at the beginning of feeder for actual fault are compared with the stored samples from simulating of fault at the possible fault points.
Abstract: In this study, a practical method is proposed for determining the distance and the section of fault in power distribution system (PDS). In the suggested method, at first the possible fault points are determined using a novel impedance-based fault location method. Since the number of these points may be more than one, thus two methods are proposed for determining the real location of fault. In the first method, the measured and recorded samples of voltages at the beginning of feeder for actual fault are compared with the stored samples of voltages which are obtained from simulating of fault at the possible fault points. The one with highest matching is the real location of fault. In the second method, frequency spectrum (FS) of voltage is defined as a suitable criterion for this purpose. Therefore the real fault point is determined by comparing and matching the FS of voltages obtained from the simulated faults and the recorded voltage for actual fault. The performance of the proposed method is evaluated in a real feeder in distribution network of Iran considering different types of faults, fault resistances, fault inception angles, real instrument transformer models and X/R ratio changes of upstream PDS network. The obtained results show that the performance of the proposed method is quite satisfactory and its accuracy is very high.
TL;DR: In this article, a heuristic-based approach to allocate static capacitors along radial distribution networks using an accelerated particle swarm optimisation algorithm is introduced, where the algorithm identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated.
Abstract: This study introduces a heuristic-based approach to allocate static capacitors along radial distribution networks using an accelerated particle swarm optimisation algorithm. In general practice, high potential buses for capacitor placement are initially identified using power loss indices. However, that method has proven less than satisfactory as power loss indices may not always indicate appropriate placement. In the proposed approach, the algorithm identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated. The result is enhancement of the overall system voltage stability index and potential achievement of maximum net savings. Sizing of fixed and switchable capacitors has been considered for different loading conditions. The overall accuracy and reliability of the approach have been validated and tested on radial distribution systems with differing topologies and of varying sizes and complexities. In this study, the results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of producing high-quality solutions with good performance of convergence and demonstrated viability.
TL;DR: In this article, a measurement-based methodology employing a novel signal decomposition theorem based upon the Hilbert transform was proposed for electromechanical modes identification. But the proposed approach is inherently simple, reliable and consistent in performance as well as characterised by low computational burden.
Abstract: This study tackles the issue of electromechanical modes identification through a measurement-based methodology employing a novel signal decomposition theorem based upon the Hilbert transform. The methodology aims to answer in a simpler and more pragmatic manner to the main weaknesses of the Hilbert-Huang transform with respect to the major refinements in the relevant literature. These weak points are discussed with sufficient detailed degree in the study. The main contribution of this study consists in combining a recent signal decomposition theorem for separating an assigned signal into elemental ones, each of them characterised by a single frequency component and a robust preliminary non-linear spectral analyser, named L
p
periodogram. This procedure's results are very appropriate for analysing some critical cases of electromechanical oscillations, because of the L
p
periodogram robustness against heavy-tailed noise and also its intrinsic ability in estimating closely spaced frequency components. The proposed approach is found to be inherently simple, reliable and consistent in performance as well as characterised by low computational burden. Some numerical applications validate the methodology and assess its own performance on synthetic signals, near real-life signals acquired by IEEE test networks and on a real measured signal from a wide-area monitoring system currently in operation.
TL;DR: A two-stage method is presented to optimise the network reconfiguration strategy, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path.
Abstract: Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.
TL;DR: In this article, a new protection scheme for the VSC-based high-voltage direct current (HVDC) transmission system is proposed based on the first carrier frequency harmonic (FCFH) currents.
Abstract: Based on the inherent characteristic of the carrier-based pulse-width modulation converters, the response of the first carrier frequency harmonic (FCFH) current in the voltage source converter (VSC)-based high-voltage direct current (HVDC) transmission system is analysed under different fault conditions in this paper. A new protection scheme for the VSC-based HVDC transmission systems is proposed based on the FCFH currents. By extracting the harmonic currents at both the endings of the DC transmission cable, the fault type can be identified. The VSC-based HVDC test system is modelled in the PSCAD/EMTDC and the proposed protection scheme is evaluated with a variety of values of the fault resistance and the fault locations. Comprehensive test studies show that the performance of the proposed protection scheme is inspiring. It can recognise the internal and the external faults correctly.
TL;DR: In this article, the authors define the theoretical principles that regulation should pursue in electric distribution tariff design and introduce the reader to the most relevant practical approaches that have been proposed or implemented.
Abstract: Electricity tariffs convey information on internal system operation to the actors involved. Electricity pricing is, then, of major importance both in liberalised and regulated systems. Most electricity consumers interact with the industry only through the price they pay for the service. Consequently, good tariff design reflects industry regulation as a whole and is the instrument used to provide consumers with the right signals. The objective of this study is to define the theoretical principles that regulation should pursue in electric distribution tariff design and introduce the reader to the most relevant practical approaches that have been proposed or implemented. Although distribution costs are usually the largest part of the access tariff (or use of system charge), there is not a universally accepted methodology for distribution pricing. The earliest attempts at cost allocation conformed what is now known as the accounting approach, based on business accounting. In recent years, the proposals have focused on two approaches: the application of long-term marginal (or incremental) costs and the cost-causality principle. Although the former aims to achieve a better economic signal, because of the difficulties surrounding its implementation, the most usual solution applied in practice draws more heavily from the causality principle.
TL;DR: In this paper, a trust region sequential quadratic programming (TRSQP) method was proposed to solve the optimal power flow problem for distribution networks with the integration of distributed generation (DG).
Abstract: This study investigates the optimal power flow (OPF) problem for distribution networks with the integration of distributed generation (DG). By considering the objectives of minimal line loss, minimal voltage deviation and maximum DG active power output, the proposed OPF formulation is a multi-object optimisation problem. Through normalisation of each objective function, the multi-objective optimisation is transformed to single-objective optimisation. To solve such a non-convex problem, the trust-region sequential quadratic programming (TRSQP) method is proposed, which iteratively approximates the OPF by a quadratic programming with the trust-region guidance. The TRSQP utilises the sensitivity analysis to approximate all the constraints with linear ones, which will reduce the optimisation scale. Active set method is utilised in TRSQP to solve quadratic programming sub-problem. Numerical tests on IEEE 33-, PG&E 69- and actual 292-, 588-, 1180-bus systems show the applicability of the proposed method, and comparisons with the primal-dual interior point method and sequential linear programming method are provided. The initialisation and convergence condition of the proposed method are also discussed. The computational result indicates that the proposed algorithm for DG control optimisation in distribution system is feasible and effective.
TL;DR: In this paper, the authors considered the impact of wind farms installation on grid frequency, especially during frequency drops, and proposed a robust and practical operation algorithm to maintain and improve the present conventional systems performance.
Abstract: Wind energy high penetration levels in power systems require robust and practical operation algorithms to maintain and improve the present conventional systems performance. Thus, several studies consider the impact of wind farms installation on grid frequency, especially during frequency drops. The proposed algorithm makes the wind turbine provide promising support during frequency deviations through two operation modes, namely, normal and support. Normal mode controls wind turbine output by adjusting rotational speed and pitch angle according to the incident wind speed category. Novel normal operation secures wind turbine positive contribution in frequency deviations curtailment regardless of poor accompanying wind speed conditions. The innovative concept of merging pitch de-loading and rotational speed overproduction deceleration is implemented to avoid continuous de-loading; hence wasted wind energy is reduced. Wind turbine generator is overloaded when frequency drop occurs during high wind speed. Major algorithm parameters are tuned based on wind turbine specifications and dominant wind speed conditions at wind turbine location. The amount of supportive excess energy during frequency deviation clearance is estimated at different wind speed circumstances, including serious wind speed drop events. An islanded medium capacity hypothetical benchmark system is implemented to examine the proposed algorithm through MATLAB and Simulink simulation environments.