Publications
254 results found
Hatziargyriou N, Milanovic J, Rahmann C, et al., 2021, Definition and classification of power system stability - revisited & extended, IEEE Transactions on Power Systems, Vol: 36, Pages: 3271-3281, ISSN: 0885-8950
Since the publication of the original paper on power system stability definitions in 2004, the dynamic behavior of power systems has gradually changed due to the increasing penetration of converter interfaced generation technologies, loads, and transmission devices. In recognition of this change, a Task Force was established in 2016 to re-examine and extend, where appropriate, the classic definitions and classifications of the basic stability terms to incorporate the effects of fast-response power electronic devices. This paper based on an IEEE PES report summarizes the major results of the work of the Task Force and presents extended definitions and classification of power system stability.
Liu J, Singh R, Pal B, 2021, Distribution system state estimation with high penetration of demand response enabled loads, IEEE Transactions on Power Systems, Vol: 36, Pages: 3093-3104, ISSN: 0885-8950
Demand-side operations incentivize utility customers to take part in various grid services. A demand response enabled load (DREL) is a flexible grid asset that schedules electricity consumption in response to a time-of-use (TOU) energy price. Consequently, its energy profile differs from that of a conventional load that is insensitive to price. This difference may cause new challenges for distribution system state estimation (DSSE). It is well known that DSSE often needs to use pseudo-measurements based on historic load profiles to increase system observability. However, historic profiles of conventional loads are not representative of DREL behaviors. The inaccuracy impacts DSSE results and other DSSE-dependent operations. In this paper, we propose an online pseudo-measurement generation approach for DSSE with DRELs. We formulate an optimization model to represent DRELs self-adjusting actions. Sampling-based stochastic optimization techniques are proposed to account for uncertainties in DRELs. A set of representative DREL behavior data corresponding to the samples are used to characterize DREL pseudo-measurements. Case studies with modified IEEE 123-bus test system verify the validity of the proposed work.
Cifuentes N, Pal BC, 2021, A new approach to the fault location problem: using the fault’s transient intermediate frequency response, IEEE Open Access Journal of Power and Energy, Vol: 8, Pages: 510-521, ISSN: 2687-7910
The fault location problem has been tackled mainly through impedance-based techniques, the travelling wave principle and more recently machine learning algorithms. These techniques require both current and voltage measurement. In the case of impedance-based methods they can provide multiples solutions. In the case of the travelling wave approach it usually requires high sampling frequency measurements together with sophisticated identification algorithms. Machine learning techniques require training data and re-tuning for different grid topologies. This paper proposes a new fault location method based on the fault’s transient intermediate frequency response of the system immediately after a fault occurs. The transient response is characterized by the travelling wave phenomenon together with intermediate frequencies of oscillation, which are dependent on the faulted section and the fault location. In the proposed fault location solution, an offline methodology identifies these intermediate frequencies and their dependency on the fault location is fitted using a polynomial regression. The online fault location is performed using those polynomial regressions together with voltage measurements from the system and simple signal processing techniques. The full method is tested with an EMT simulation in PSCAD, using the exact frequency dependent model for underground cables.
Zhao J, Netto M, Huang Z, et al., 2021, Roles of dynamic state estimation in power system modeling, monitoring and operation, IEEE Transactions on Power Systems, Vol: 36, Pages: 2462-2472, ISSN: 0885-8950
Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems and novel system monitoring, control and protection tools to achieve better reliability and resiliency.
Karbouj H, Rather Z, Pal B, 2021, Adaptive voltage control for large scale solar PV power plant considering real life factors, IEEE Transactions on Sustainable Energy, Vol: 12, Pages: 990-998, ISSN: 1949-3029
This paper presents an accurate and realistic estimation of reactive power capability of solar photovoltaic (PV) inverters considering ambient temperature, solar irradiance, and terminal voltage. Based on the accurate estimation of reactive power capability, a self-adaptive voltage controller is proposed to enable solar PV power plant participation in voltage control ancillary service. The proposed accurate and realistic estimation has revealed the possibility of solar PV power plant failing to comply with grid code requirements under extreme weather conditions. On the other hand, the proposed control strategy has shown significantly better effectiveness to utilise solar PV inverter capability, and provide better voltage control support service to the grid.
Pawar B, Saikat C, Batzelis E, et al., 2021, Grid-Forming Control for Solar PV Systems with Real-Time MPP Estimation, IEEE PES GM
Ali H, Pal B, 2021, Model order reduction of multi-terminal direct-current grid systems, IEEE Transactions on Power Systems, Vol: 36, Pages: 699-711, ISSN: 0885-8950
This paper proposes a methodology to develop a linear low-order model of a multi-terminal direct-current (MTDC) system connected to practically-sized offshore wind farm systems. The method individually linearizes the model of wind farm systems and subsequently performs model order reduction (MOR) using iterative rational Krylov algorithm (IRKA). This is, therefore, a modular approach and expandable to any number of wind farm connections. On the other hand, the model order and non-linearity of other components are retained. Effectiveness of the proposed method is demonstrated on an MTDC system connected to two large-scale wind farm models by comparing the responses obtained from the full order model (FOM) and reduced order model (ROM). From the simulation studies, it can be seen that the ROM obtained from proposed method is able to maintain high degree accuracy of FOM responses at a much faster simulation time, and hence this can help power system operation planning. Various control functionalities and strategies, different operating conditions and faults of the MTDC system are also considered to investigate robustness of the proposed method.
Ul Nazir F, Pal BC, Jabr RA, 2021, Approximate Load Models for Conic OPF Solvers, IEEE-Power-and-Energy-Society General Meeting (PESGM), Publisher: IEEE, ISSN: 1944-9925
Yu Y, Nduka O, Pal B, 2020, Smart control of an electric vehicle for ancillary service in DC microgrid, IEEE Access, Vol: 8, Pages: 197222-197235, ISSN: 2169-3536
This article presents a two-stage framework for optimal Electric Vehicle (EV) charging/discharging strategy for DC Microgrid (MG) with Distributed Generators (DGs). A multi-objective optimisation task aimed at minimising system losses and EV battery degradation with Vehicle-to-Grid (V2G) peak shaving service has been realised. This coordinated EV integration into the DCMG was formulated as a directed weighted single source shortest path problem that was solved using a modified Dijkstra’s algorithm. The weights of the edges were obtained using primal-dual interior point method. The proposed framework has been experimentally verified using simulations with a test DCMG system with practical IEEE European low voltage test feeder load profiles. Results show realisation of peak demand shaving leveraging on EV discharge with minimal on-board battery degradation as well as reduced system losses. It is also shown that the proposed two-stage framework reduces the battery state of charge (SOC) sample space requirements in the analysis, thus, reducing the computational burden.
Chen Y, Mazhari SM, Chung CY, et al., 2020, Rotor angle stability prediction of power systems with high wind power penetration using a stability index vector, IEEE Transactions on Power Systems, Vol: 35, Pages: 4632-4643, ISSN: 0885-8950
This paper proposes a methodology for predicting online rotor angle stability in power system operation under significant contribution from wind generation. First, a novel algorithm is developed to extract a stability index (SI) that quantifies the margin of rotor angle stability of power systems reflecting the dynamics of wind power. An approach is proposed that takes advantage of the machine learning technique and the newly defined SI. In case of a contingency, the developed algorithm is employed in parallel to find SIs for all possible instability modes. The SIs are formed as a vector and then applied to a classifier algorithm for rotor angle stability prediction. Compared to other features used in state-of-the-art methods, SI vectors are highly rec-ognizable and thus can lead to a more accurate and reliable prediction. The proposed approach is validated on two IEEE test systems with various wind power penetration levels and compared to existing methods, followed by a discussion of results.
Ul Nazir F, Pal B, Jabr R, 2020, Approximate load models for conic OPF solvers, IEEE Transactions on Power Systems, Vol: 36, Pages: 549-552, ISSN: 0885-8950
The global optimum of the optimal power flow (OPF) problem can be sought in various practical settings by adopting the conic relaxations, such as the second order cone programs (SOCPs) and semi-definite programs (SDPs). However, the ZIP (constant impedance, constant current, constant power) and exponential load models are not directly amenable with these conic solvers. Thus, these are mostly treated as constant power loads in the literature. In this letter, we propose two simple methods to approximate these static loads with good accuracy. The proposed methods perform much better than the traditional constant power approximation.
Kumar CS, Rajawat K, Chakrabarti S, et al., 2020, Robust distribution system state estimation with hybrid measurements, IET Generation, Transmission and Distribution, Vol: 14, Pages: 3250-3259, ISSN: 1350-2360
With growing connection of distributed energy resources, availability of demand side response technologies, deployment of smart meters, the distribution system needs advanced network automation for running the system efficiently. State estimation is the core driver of network automation. While the output from SMs will make the state estimation more accurate, advanced metering infrastructures come with several challenges such as noisy, erroneous measurement including lost or missed measurements, exposure to cyber attack and so on. This study proposes a three-phase unbalanced distribution system state estimation which is robust against noisy distribution system measurements, bad data attacks and missing or delayed measurements. This method considers measurement from hybrid sources such as SCADA, micro-phasor measurement units (μμPMUs) and SMs. Kalman smoother is used to fill the missing measurements and expectation-maximisation based forecasting is used to interpolate the hybrid measurements to a common timestamp and compensate for the delay in SM measurements. Extensive numerical comparisons are made on IEEE 13, 37 and 123 bus systems to test the robustness of the proposed DSSE against delayed SM measurements and bad or noisy data. An IEEE 24 bus system is modelled and real-time measurement devices are interfaced to it in Hypersim. The data from the hybrid measurement devices of IIT Kanpur smart grid is also used to test the robustness of the proposed method.
Gupta Y, Doolla S, Chatterjee K, et al., 2020, Optimal DG allocation and volt–var dispatch for a droop based microgrid, IEEE Transactions on Smart Grid, Vol: 12, Pages: 169-181, ISSN: 1949-3053
Unequal reactive power sharing amongst distributed generators (DG) is a significant concern while operating a droop based microgrid. The reasons for this unequal reactive power sharing include the difference in feeder impedances, uneven distribution of loads and DGs in terms of size and locations. In this paper, a mixed-integer linear programming (MILP) problem applicable for a droop based microgrid has been proposed to achieve proportional reactive power sharing amongst DGs while maintaining very low line losses. Firstly, the optimal sizing and placement of DGs are investigated. This includes a detailed discussion on the linearisation of various nonlinear terms involved in the formulation. Subsequently, a day–ahead dispatch is generated for these DGs for a given load profile. Additionally, network reconfiguration has been incorporated for further improvement in performance. The effect of considering a practical constant impedance-current-power (ZIP) load model, instead of simply considering constant impedance loads, has also been assessed. The proposed formulation has been tested on a 33 bus network which has been modified to represent an islanded microgrid. The results obtained validate the accuracy of the proposed planning and dispatch method and demonstrate its utility in achieving proportional reactive power sharing amongst the DGs while incurring very low line losses.
Nsengiyaremye J, Pal BC, Begovic MM, 2020, Microgrid protection using low-cost communication systems, IEEE Transactions on Power Delivery, Vol: 35, Pages: 2011-2020, ISSN: 0885-8977
Power electronics interface of renewable energy to system is now the trend in both transmission and distribution segments of power network. Unlike synchronous generators, the fault feeding and control characteristic of these renewable generators are different and mostly influenced by the topology, switching, and control deployed in power electronics interface. So, the network protection design and operational requirements are now challenged in the absence of large fault current. Although the differential current principle still works, its implementation is limited by the significant cost associated to its communication system. This paper proposes a differential line protection scheme based on local fault detection and comparing binary state outputs of relays at both ends of the line thus requiring a simple, flexible and low bandwidth communication system. The performance of the proposed scheme is assessed through simulation of an example system with several scenarios.
Merritt NR, Chakraborty C, Bajpai P, et al., 2020, A unified control structure for grid connected and islanded mode of operation of voltage source converter based distributed generation units under unbalanced and non-linear conditions, IEEE Transactions on Power Delivery, Vol: 35, Pages: 1758-1768, ISSN: 0885-8977
This manuscript develops a unified control structure for Distributed Generation (DG) units based on Voltage Source Converters considering unbalanced and non-linear operating conditions. This control structure works for both the Islanded and the Grid-connected modes of operation of the Micro-Grid (MG). The objective of this control scheme is to regulate the line currents of the DG unit in such a manner that the voltage at the Point of Common Coupling (PCC) remains balanced despite the line currents of the DG unit being unbalanced and distorted. Multiple adaptive P-R controllers have been proposed for the current control loop of the Voltage Source Converter (VSC). These controllers have been implemented with resettable integrators so as to limit the DC components in the post fault current of the VSC. The Battery Energy Storage System (BESS) is interfaced to the DC link of the VSC through bi-directional dc-dc converters. An improved control structure for the bi-directional dc-dc converter has been developed. The effectiveness of these control structures have been presented and tested in PSCAD/EMTDC in an IEEE 34 node distribution system model being fed by two identical DG units.
X H, Hua G R L, Pal BC, 2020, Transient stability analysis and enhancement of renewable energy conversion system during LVRT, IEEE Transactions on Sustainable Energy, Vol: 11, Pages: 1612-1623, ISSN: 1949-3029
Grid-connected renewable energy conversion systems (RECSs) are usually required by grid codes to possess the low voltage ride through (LVRT) and reactive power support capabilities so as to cope with grid voltage sags. During LVRT, RECS's terminal voltage becomes sensitive and changeable with its output current, which brings a great challenge for the RECS to resynchronize with the grid by means of phase-locked loops (PLLs). This paper indicates that loss of synchronism (LOS) of PLLs is responsible for the transient instability of grid-connected RECSs during LVRT, and the LOS is essentially due to the transient interaction between the PLL and the weak terminal voltage. For achieving a quantitative analysis, an equivalent swing equation model is developed to describe the transient interaction. Based on the model, the transient instability mechanism of RECSs during LVRT is clarified. Furthermore, a transient stability enhancement method is proposed to avoid the possibility of transient instability. Simulations performed on the New England 39-bus test system verify the effectiveness of the method.
Pal B, 2020, Successful publications: where the best intentions of all meet [Leader's Corner], IEEE Power and Energy Magazine, Vol: 18, Pages: 12-16, ISSN: 1540-7977
Reports on the Open Access (OA) initiative and efforts by IEEE to launch OA publications.
Nazir FU, Pal BC, Jabr RA, 2020, Distributed solution of stochastic volt/VAr control in radial networks, IEEE Transactions on Smart Grid, Vol: 11, Pages: 5314-5324, ISSN: 1949-3053
This paper presents a fully distributed algorithm for the stochastic Volt/VAr control (VVC) problem in active distribution networks. Exact convexification of the VVC problem is achieved through the use of second-order cones on the continuous relaxation of the original optimization structure. The global optimum solution of the relaxed problem is obtained through the application of the alternating direction method of multipliers (ADMM). In order to minimize the effect of rounding off on the final solution, an adaptive threshold discretization technique is used. A two-stage control strategy is adopted where the discrete controllers, like load tap changers and switched capacitors, are dispatched at the beginning of the optimization interval and the continuous controllers, like distributed generation (DG) inverters, are adjusted in real time according to an optimized decision rule. The superiority of the proposed algorithm is demonstrated through numerical simulations on the UKGDS-95 and the IEEE-123 bus systems.
Nduka O, Yu YUE, Pal BC, et al., 2020, A robust augmented nodal analysis approach to distribution network solution, IEEE Transactions on Smart Grid, Vol: 11, Pages: 2140-2150, ISSN: 1949-3053
The ambition to decarbonize the source of energy for heat and transport sector through electricity from renewable energy has led to significant challenge in the way power distribution networks (DNs) are planned, designed and operated. Traditionally, DN was put in place to support the demand passively. Now with renewable generation, storage and demand side management through automation, provision of network support services have transformed the character of the DNs. Active management of the DN requires fast power flow analysis, state estimation, reactive power support etc. This paper proposes a method of power flow analysis which incorporates the challenges of distributed generator (DG) characteristics, demand side management and voltage support. The proposed approach reformulated the Jacobian matrix of the well-known modified augmented nodal analysis (MANA) method; thus, improving the robustness and solvability of the formulation. Reactive powers of the DGs, node voltages and currents of ‘non-constitutive’ elements were the chosen state variables. The performance of this method is compared with the MANA. Results are discussed and the effectiveness of the proposed approach is demonstrated with two example case studies.
Ul-Nazir F, Kumar N, Pal BC, et al., 2020, Enhanced SOGI controller for weak grid integrated solar PV system, IEEE Transactions on Energy Conversion, Vol: 35, Pages: 1208-1217, ISSN: 0885-8969
This paper presents a two-stage three-phase solar photovoltaic (PV) system, which is controlled through a novel enhanced second order generalized integrator (ESOGI) based control technique. The proposed ESOGI is used for fundamental component extraction from nonlinear load current and distorted grid voltages. The proposed integrator effectively and simultaneously manages to address the DC offset, inter-harmonic and integrator delay problems of the traditional SOGI. In addition, the proposed control technique provides power factor correction, harmonic elimination, and load balancing functionalities. The ESOGI controller is used to generate reference grid currents for controlling the voltage source converter (VSC), interfacing the PV panel with the grid. Extensive simulation and experimental results, on a developed prototype in the laboratory, depict that the total harmonic distortion (THD) of the grid injected currents and voltages are found well under IEEE-519 standard.
Batzelis EI, Anagnostou G, Chakraborty C, et al., 2020, Computation of the lambert W function in photovoltaic modeling, Electrimacs 2019, Publisher: Springer International Publishing, Pages: 583-595, ISSN: 1876-1100
Recently, the Lambert W function has emerged as a valuable mathematical tool in photovoltaic (PV) modeling and other scientific fields. This increasing interest is because it can be used to reformulate the implicit equations of the single-diode PV model into explicit form. However, the computation of the Lambert W function itself is still not clear in the literature; some studies use the iterative built-in functions in MATLAB or other computational platforms, while others adopt their own approximation formulae. This paper takes a deeper look at the ways the Lambert W function is evaluated in PV models and carries out a comparative study to assess the most commonly used methods in terms of accuracy, computational cost, and application range. These alternatives are implemented in a modern computer and a typical microcontroller to evaluate their performance in both simulations and embedded applications. The analysis concludes that some series expansions are good options for PV modeling applications, requiring less execution time than the built-in MATLAB lambertw function and exhibiting negligible approximation error.
Rois H, Kunjumuhammed LPK, Pal BC, et al., 2020, A trajectory piecewise-linear approach to nonlinear model order reduction of wind farms, IEEE Transactions on Sustainable Energy, Vol: 11, Pages: 894-905, ISSN: 1949-3029
This paper presents a method to develop computationally efficient dynamic model of a wind farm suitable for large disturbance simulation. The method based on a Trajectory Piecewise Linear (TPWL) approximation uses single and multiple training trajectory to develop a nonlinear reduced order model (ROM). Simulation results using a small demonstration wind farm system and a large practical wind farm system are discussed to demonstrate the effectiveness of the model in capturing dynamic behaviour of wind farm following large disturbances.
Nduka OS, Kunjumuhammed L, Pal B, et al., 2019, Field trial of coordinated control of PV and energy storage units and analysis of power quality measurements, IEEE Access, Vol: 8, Pages: 1962-1974, ISSN: 2169-3536
Trends support low voltage distribution networks will soon experience significant uptake of customer-owned low-carbon technology (LCT) devices especially rooftop photovoltaics (PVs) and small-scale energy storage (SSES) systems. This paradigm shift will introduce some significant challenges in modern distribution network planning and operations owing to the temporal nature of modern demand.Therefore, it became relevant to investigate the UK low voltage (LV) network operations considering high uptake of PVs and SSESs through both field measurements and desktop studies. The aim was to validatethrough field trials, the flexibility benefits of peak demand reduction and reverse power flow mitigation through smart control of customer-owned SSESs. It was shown that peak demand of up to 60% could beachieved in UK distribution network through the smart control of these devices. In tandem with the demand reduction, the study revealed that type-tested SSES power interface units do not pose significant powerquality risks even for 100% customer penetration.
Kumar S, Singh B, Pal BC, et al., 2019, Energy efficient three-phase utility interactive residential microgrid with Mode transfer capabilities at weak grid conditions, IEEE Transactions on Industry Applications, Vol: 55, Pages: 7082-7091, ISSN: 0093-9994
This article presents an energy efficient autonomous grid-synchronized photovoltaic (PV) array battery energy storage (BES) based microgrid with power quality improving capabilities under weak grid conditions. The microgrid is developed to supply consumer loads even at disappearance of the weak grid. The BES is not only beneficial on daily energy saving but it is also sized to furnish smoothening facilities to the PV-BES microgrid. A pseudolinear synchronization scheme is used, which is based on extraction of fundamental positive sequence components from the polluted grid voltages. The islanded controller furnishes reliability by maintaining the voltage and frequency and continuous power to the consumer load. The multivariance generalized adaptive controller is proposed to control the microgrid and to improve the power quality aspects. The effectiveness of microgrid is demonstrated experimentally with estimation of phase and frequency at grid synchronization and desynchronization with polluted grid conditions.
Kunjumuhammed L, Kuenzel S, Pal BC, 2019, Simulation of Power System with Renewables, Publisher: Academic Press, ISBN: 9780128111871
The book presents a step-by-step approach to modelling implementation, including all major components used in current power systems operation, giving the reader the opportunity to learn how to gather models for conventional generators, wind ...
Anagnostou G, Puthenpurayl Linash K, Pal B, 2019, Dynamic state estimation for wind turbine models with unknown wind velocity, IEEE Transactions on Power Systems, Vol: 34, Pages: 3879-3890, ISSN: 0885-8950
This paper proposes a novel Kalman filtering based dynamic state estimation method, which addresses cases of models with a nonlinear unknown input, and it is suitable for wind turbine model state estimation. Given the complexity characterising modern power networks, dynamic state estimation techniques applied on renewable energy based generators, such as wind turbines, enhance operators’ awareness of the components comprising modern power networks. In this context, the method developed here is implemented on a doubly-fed induction generator based wind turbine, under unknown wind velocity conditions, as opposed to similar studies so far, where all model inputs are considered to be known, and this does not always reflect the reality. The proposed technique is derivative-free and it relies on the formulation of the nonlinear output measurement equations as power series. The effectiveness of the suggested algorithm is tested on a modified version of the IEEE benchmark 68-bus, 16-machine system.
Zhang L, Kerrigan E, Pal B, 2019, Optimal communication scheduling in the smart grid, IEEE Transactions on Industrial Informatics, Vol: 15, Pages: 5257-5265, ISSN: 1551-3203
This paper focuses on obtaining the optimal communication topology in the smart grid architecture, i.e., what is the optimal communication setup of smart meters in a smart building. The fact that smart meters also consume energy, more often than not, gets ignored by researchers and engineers. In this paper, we will show that smart meter networks can consume significantly less energy with optimal scheduling. Numerical results show that the overall energy consumption can be reduced by implementing the optimal communication architecture and transmission rate setup, rather than implementing a straightforward communication architecture with uniform channel bandwidth.
Su D, Batzelis E, Pal B, 2019, Machine learning algorithms in forecasting of photovoltaic power generation, 2019 International Conference on Smart Energy Systems and Technologies (SEST), Publisher: IEEE
Due to the intrinsic intermittency and stochastic nature of solar power, accurate forecasting of the photovoltaic (PV) generation is crucial for the operation and planning of PV-intensive power systems. Several PV forecasting methods based on machine learning algorithms have recently emerged, but a complete assessment of their performance on a common framework is still missing from the literature. In this paper, a comprehensive comparative analysis is performed, evaluating ten recent neural networks and intelligent algorithms of the literature in short-term PV forecasting. All methods are properly fine-tuned and assessed on a one-year dataset of a 406 MWp PV plant in the UK. Furthermore, a new hybrid prediction strategy is proposed and evaluated, derived as an aggregation of the most well-performing forecasting models. Simulation results in MATLAB show that the season of the year affects the accuracy of all methods, the proposed hybrid one performing most favorably overall.
Batzelis E, Anagnostou G, Cole I, et al., 2019, A state-space dynamic model for photovoltaic systems with full ancillary services support, IEEE Transactions on Sustainable Energy, Vol: 10, Pages: 1399-1409, ISSN: 1949-3029
Large-scale photovoltaic (PV) integration to the network necessitates accurate modeling of PV system dynamics under solar irradiance changes and disturbances in the power system. Most of the available PV dynamic models in the literature are scope-specific, neglecting some control functions and employing simplifications. In this paper, a complete dynamic model for two-stage PV systems is presented, given in entirely state-space form and explicit equations that takes into account all power circuit dynamics and modern control functions. This is a holistic approach that considers a full range of ancillary services required by modern grid codes, supports both balanced and unbalanced grid operation, and accounts for the discontinuous conduction mode (DCM) of the dc/dc converter of the system. The proposed dynamic model is evaluated and compared to other approaches based on the literature, against scenarios of irradiance variation, voltage sags and frequency distortion. Simulation results in MATLAB/Simulink indicate high accuracy at low computational cost and complexity.
Singh AK, Pal BC, 2019, Rate of change of frequency estimation for power systems using interpolated DFT and Kalman filter, IEEE Transactions on Power Systems, Vol: 34, Pages: 2509-2517, ISSN: 0885-8950
This paper presents a new method for estimating rate of change of frequency (RoCoF) of voltage or current signals measured using instrument transformers. The method is demonstrably superior to currently available methods in literature, in terms of estimation-latency and estimation-error. The estimation is performed in two steps. In the first step, the analog voltage or current signal obtained from an instrument transformer is statistically processed using interpolated discrete Fourier transform in order to obtain the means and variances of the signal parameters. These means and variances are then given as inputs to the second step, in which Kalman filtering is used to find the final RoCoF estimate. Accurate mathematical expressions for the means and variances of signal parameters have been derived and used in the second step, which is the main reason behind the superior performance of the method. The applicability of the method has been demonstrated on a benchmark power system model.
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