Voltage Dependent Load Research Articles

A modified backward and forward sweep method for microgrid load flow analysis under different electric vehicle load mathematical models

A power flow analysis under different electric vehicle (EV) load models based on the modified backward and forward sweep method is presented. Voltage-dependent loads (VDLs) were used to analyze the total power loss and load voltage deviation (LVD) under different EV load models and the general load of the electrical power system. The VDL was defined in the backward stage where the voltage ratio was between bus voltages per nominal voltage. The IEEE 33 bus radial distribution system was selected to be the test system. The EV penetration level was defined as 26.88% compared to the base case of constant power (P). The simulation results showed the impact levels from EV load models to the grid based on the traditional method, with impact levels from high to low being for polynomial load (EVI), constant current load (EVIII), and VDL (EVII) models, respectively. In particular, the highest impact for EVI was in scenario 4 (D), where the total active power loss, total reactive power loss, and LVD were 3.45%, 3.47%, and 3.36%, respectively. Therefore, the EV load model was one important factor to select for solving the power flow of the grid. Moreover, the position and size of the EV load could be considered in the optimal condition for reducing the impact to the grid. However, energy management will become a key challenge for supporting the high penetration of EVs in the near future.

Investigations of Large-Scale Voltage-Dependent Loads for Damping Inter-Area Oscillations: Mechanism and Robust Decentralized Control

To uncover the mechanism by which voltage-dependent loads (VDLs) influence electromechanical dynamics, this paper mathematically deduces the damping torque induced by VDLs based on a single machine infinite bus system. Moreover, by continuously regulating the terminal voltage of a typical large-scale VDL, i.e., the aluminum electrolysis load, this paper proposes a novel load damping control architecture to dynamically modulate the power consumption of controlled loads so as to eliminate interarea oscillations in power systems. Specifically, the decentralized load damping controllers (LDCs) used in this architecture are designed by a proposed multistage mixed ${{{H}}_{2}} / {{{H}}_\infty }$ control approach to guarantee robustness against uncertainties (e.g., tie-line outages and wind generation fluctuations) as well as to ensure reasonable control efforts of controlled VDLs. Simulation results on the modified New England and New York interconnected system validate the method for analysis of VDLs’ effects on interarea oscillations and show the proposed load damping control strategy can satisfactorily damp interarea oscillations over multiple operating points.

Gauss-Quadrature-Based Probabilistic Load Flow Method With Voltage-Dependent Loads Including WTGS, PV, and EV Charging Uncertainties

This paper proposes a Gauss-quadrature-based probabilistic load flow (PLF) keeping in view the uncertainties and correlations in load, renewable generations (wind and PV), and electric vehicle charging. An approach to include uncertainties of voltage-dependent loads has also been proposed. The simulation study has been performed on a modified IEEE-118 bus system. Further, the performance of the proposed method has been compared with that of the benchmark method, i.e., Monte Carlo simulation and a few well-established methods, such as point estimate method, combined cumulant and Gram–Charlier method, and combined cumulant and Gaussian mixture approximation method. The extensive simulation studies and comparison of various results obviates the aptitude of the proposed method for PLF.

Recommended Parameter Values and Ranges of Most Frequently Used Static Load Models

This paper presents parameter values and ranges of static load models used in a power system analysis for the representation of both individual electrical devices and aggregate system loads. The paper discusses and correlates load models and their parameters following statistical processing of the responses of around 100 transmission system operators and utilities around the world, who participated in a survey initiated by CIGRE Working Group C4.605, with the corresponding information on load models and their parameter values from the existing literature. According to the survey, the most frequently used static load models are voltage dependent, and voltage and frequency dependent exponential load models. The identified typical parameter values and ranges of these static load models, both for low voltage devices and for aggregate loads at higher voltage levels, are results of the analysis of a large number of data. Based on these results, the paper provides recommendations for their further use in power system studies and also introduces a novel method for obtaining the mean values and ranges of parameters of the aggregate system load models.

A Dual Inductor High Step-Up DC/DC Converter Based on the Cockcroft–Walton Multiplier

A new nonisolated, high step-up dc–dc converter is proposed based on the current-fed Cockcroft–Walton Voltage Multiplier (CW-VM) that can be used as the boosting power stage of converter for low-voltage low power renewable energy sources such as photovoltaic and fuel cells. The proposed converter employs two low-voltage common-emitter switches. Utilizing the current-fed CW-VM eliminates some problems associated with the conventional voltage-fed type such as voltage ripple and load-dependent voltage droop. Other advantages of the proposed converter are continuous input current, high voltage gain, and high efficiency. Steady state operation principles, specifications, and design considerations of the proposed converter are illustrated. Furthermore, efficiency analysis of the converter is performed and discussed. Experimental tests for a 200 W prototype are carried out which confirm the theoretical analysis.

Multi-Objective based Optimal Energy and Reactive Power Dispatch in Deregulated Electricity Markets

This paper presents a day-ahead (DA) multi-objective based joint energy and reactive power dispatch in the deregulated electricity markets. The traditional social welfare in the centralized electricity markets comprises of customers benefit function and the cost function of active power generation. In this paper, the traditional social welfare is modified to incorporate the cost of both active and reactive power generation. Here, the voltage dependent load modeling is used. This paper brings out the unsuitability of traditional single objective functions, e.g., social welfare maximization (SWM), loss minimization (LM) due to the reduction of amount of load served. Therefore, a multi-objective based optimization is required. This paper proposes four objectives, i.e., SWM, load served maximization (LSM), LM and voltage stability enhancement index (VSEI); and these objectives can be combined as per the operating condition. The simulation studies are performed on IEEE 30 bus test system by considering the both traditional constant load modeling and the proposed voltage dependent load modeling.

Estimation of Aggregate Reserve With Point-of-Load Voltage Control

Voltage dependent loads can collectively provide a certain amount of power reserve (by virtue of the ability to change their power consumption within the stipulated voltage tolerance) which could be exploited for grid frequency regulation through voltage control at the substation/feeder or at the point of load. The amount of such power reserve would vary with time of the day depending on the incidence of different types of voltage dependent loads and also the voltage profile across the feeders. It is important for the grid operators to know the aggregate power reserve from the voltage dependent loads during different times of the day in order to schedule other forms of reserves accordingly. This paper presents a methodology to estimate such power reserve from the measured power and voltage at the bulk supply points without knowing the actual distribution network topology and/or load profile of individual customers. The proposed method is applied to estimate the time variation of the aggregate reserve offered by the voltage dependent loads within the domestic sector in Great Britain. Studies on a standard IEEE distribution network are presented to validate the estimated reserve margins under typical voltage profiles across the distribution feeders.

Tracking Transformer Tap Position in Real-Time Distribution Network Power Flow Applications

The current injection power flow method is commonly used by the power distribution industry in real-time distribution management systems. The inclusion of reactive power control adjustments that simulate local voltage controllers is known to create multiple power flow solutions. The state-of-the-art for simulating local voltage controllers computes the most likely operational solution by considering the different precedences of the controlled devices, based on their speeds of response. This paper presents a novel sensitivity-based approach for simulating local controllers, which directly accounts for both controller interactions and the way in which the system state is reached. Numerical results are reported on networks with up to 3146 nodes and voltage dependent load models; the results show that the proposed approach yields probable power flow solutions that are virtually identical to those given by an implementation of the state-of-the-art time-coordinated method and with a speed-up factor around three on the large network cases.

A two-stage reactive power optimization in transmission network incorporating reserves from voltage-dependent loads

With the integration of intermittent resources, more reserves are required for uncertainties. Traditionally, reactive power optimization in transmission network focuses on loss minimization problems, regarding loads as voltage-independent injections. In fact, the bus voltage magnitude affects the load active/reactive injection, providing a possibility for system operators to regulate the power of loads through voltage regulation. Inspired by this inherent feature of loads, this paper considers the regulation of voltage-dependent loads (VDLs) for fast reserves through reactive power optimization and voltage control under the coordination of transmission and distribution networks. A two-stage multi-objective optimal power flow model is developed to incorporate reserves from VDLs. The first stage is to optimize the minimization of losses and the maximization of the reserves that the VDLs can provide, which is modeled as an AC optimal power flow problem. In the second stage, it is verified whether the reserves from the first stage can be delivered by voltage regulation to settle down the possible imbalance power in the power system. Case studies show that the proposed method can estimate the amount of reserves from VDLs and optimize the bus voltages accordingly.

Impact of time varying load models on PV DG planning

A constant load and generation model is generally considered in planning studies that pertain to Distributed Generation (DG) integrated distribution systems. However, such considerations may result in misleading and inconsistent values for the voltage profile, loss reduction, payback period, deferral values, and other related calculations due to the variation of both renewable energy-based generation and load demand. This paper investigates the impact of time varying voltage dependent load models on the DG planning studies. The study is based on the comparative assessment of different impact indices, penetration level, active and reactive power intake, active and reactive power loss, and Mega Volt Ampere support offered by the installation of photovoltaic based DG for different time varying load models. The outcomes of the current research work reveal that the time varying load modeling approach has significant impact on the distribution systems.

A measurement-based VSI for voltage dependent loads using angle difference between tangent lines of load and PV curves

In this short communication, a generic measurement-based voltage stability indicator (VSI) is presented with voltage dependent load models incorporated. It uses the angle difference between the tangent lines of the load characteristic curve and the PV curve. Based on the Thevenin equivalent estimated from the measurements, the proposed VSI can be easily applied to both the ZIP and the exponential load models. Time domain simulation results on both load models demonstrate that the proposed VSI accurately indicates voltage instability and outperforms a conventional VSI which is based on a constant power load model.

Enhancing power system state estimation by incorporating equality constraints of voltage dependent loads and zero injections

This paper presents a new state estimation (SE) method including equality constraints to model voltage dependent loads and zero injections. Formulation of conventional SE, assuming simple constant power model for the system's loads, is modified to incorporate voltage dependent load models. Assuming reliable load models and zero injections, it is analytically proved that modeling the equality constraints leads to better SE accuracy. To numerically validate the analytical findings, the proposed SE method is implemented on the IEEE 118-bus test system and the large-scale real-world Iran’s power system, and its obtained results are compared with the results of conventional SE. Also, it is shown that considering voltage dependent load model in SE formulation leads to better performance of bad data detection. Moreover, it is illustrated that the accuracy of the proposed SE has low sensitivity to load model identification error.

Analytical assessment of voltage support via reactive power from new electric vehicles supply equipment in radial distribution grids with voltage-dependent loads

Grid operators have to cope with secure electric vehicles integration in the power system, which may lead to violations of the allowed voltage band. This work intends to provide an analytical assessment and guidelines for distribution system operators when evaluating new electric vehicle supply equipment installations with fast charging capability in existing low voltage distribution feeders. The aim is to prevent the voltage to exceed the permitted values when charging at high power, by exploiting the effect of reactive power. The contribution of each power component in distribution grids is analyzed, including the loads’ voltage-dependency, which influences the effectiveness of reactive power control. The proposed guidelines indicate the amount of capacitive reactive power that an individual electric vehicle supply equipment is expected to provide, in order to effectively manage the voltage rise. The proposed method is validated on the Cigrè benchmark low voltage distribution network as well as on a real Danish low voltage grid.

Effect of Load Model Using Ranking Identification Technique for Multi Type DG Incorporating Embedded Meta EP-Firefly Algorithm

This paper presents the effect of load model prior to the distributed generation (DG) planning in distribution system. In achieving optimal allocation and placement of DG, a ranking identification technique was proposed in order to study the DG planning using pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm. The aim of this study is to analyze the effect of different type of DG in order to reduce the total losses considering load factor. To realize the effectiveness of the proposed technique, the IEEE 33 bus test systems was utilized as the test specimen. In this study, the proposed techniques were used to determine the DG sizing and the suitable location for DG planning. The results produced are utilized for the optimization process of DG for the benefit of power system operators and planners in the utility. The power system planner can choose the suitable size and location from the result obtained in this study with the appropriate company’s budget. The modeling of voltage dependent loads has been presented and the results show the voltage dependent load models have a significant effect on total losses of a distribution system for different DG type.

Battery Storage for the Utility-Scale Distributed Photovoltaic Generations

Batteries are essential for efficiently utilizing the energy from the photovoltaic (PV) modules. However, integration of batteries with PV plants at large scale needs more attention in terms of size, location, and times for the charging and discharging of the batteries. This paper addresses these aspects. It presents a mixed integer optimization using genetic algorithm for determining the optimum size and placement of battery-sourced distributed PV generation (B-SDPVG) in distribution networks. The total energy loss index is formulated as the main objective function and simultaneously, the bus voltage deviations and penetrations of the B-SDPVG are calculated. The yields from the PV plants are estimated using 15 years of weather data modeled with the aid of beta probability density function. Furthermore, a novel charge–discharge control model is developed for determining the choice of the charging and discharging of batteries at each hour. By considering different time varying voltage-dependent load models, the proposed algorithm is applied on the IEEE 33 bus and the IEEE 69 bus test distribution networks. The numerical results of two distribution networks with time-varying loads show the advantages of the proposed methodology. It was revealed that integration of battery storage and intelligent scheduling for charging and discharging of batteries produced much better results and improved the quality of distribution networks. The supply of power from the B-SDPVG during the peak load hours and at night was made possible for each load model. The proposed charge–discharge control model for scheduling the charging and discharging of the batteries was found dynamic. Results of this paper can be of potential importance in planning for the integration of battery storage in distribution networks.

Probablistic generation model for optimal allocation of PV DG in distribution system with time-varying load models

Distributed generation (DG) planning studies are generally conducted while assuming constant generation and load models. However, in this paper, optimal allocation of photovoltaic (PV) based DG is carried out while considering probabilistic generation and time varying voltage dependent load models. First, a novel probabilistic generation model is proposed for solar irradiance uncertainty modeling to compute the hourly output power produced via PV units. Subsequently, the obtained power values are used to determine the optimum PV allocation in the distribution system through particle swarm optimization to minimize the multi-objective function. The proposed algorithm has been validated on 33-bus and 69-bus distribution test systems. The results demonstrate that the proposed model is suitable for solar irradiance modeling and can be employed in power system planning studies.

Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks

Active network management (ANM) aims to increase the capacity of variable distributed generation (DG), which can be connected to existing distribution networks. In this study, it is proposed to simultaneously consider the efficient use of energy resources when high shares of DG are procured through the ANM approach. To that end, a multi-period and multiobjective optimisation algorithm, based on the linearised optimal power flow, is formulated. The algorithm seeks to maximise the installed capacity of DG while minimising the energy losses and consumption of voltage-dependent loads. The objectives are optimised considering the coordinated operation of voltage regulators and on-load tap changers, and the management of DG generation curtailment and reactive power compensation from DG. Additionally, the effects of load and generation uncertainties are addressed through a two-stage stochastic programming formulation of the multiobjective problem. The result is a set of non-inferior solutions, which allows exploring the degree of conflict among the objectives. The proposed approach was tested on two IEEE test feeders and the solutions show a significant improvement in the system's energy efficiency with a low impact on the amount of connected DG.

Development of new force sensor using super-multilayer alternating laminated film comprising piezoelectric poly(l-lactic acid) and poly(d-lactic acid) films in the shape of a rectangle with round corners

A new super-multilayer alternating laminated film in the shape of a rectangle with round corners has been developed. The super-multilayer film, which comprised piezoelectric poly(l-lactic acid) (PLLA) and poly(d-lactic acid) (PDLA) films, was wound with the number of turns on the order of from 100 to 1000 to form piezoelectric rolls. These piezoelectric rolls could generate an induced voltage of more than 95% of the initial voltage for over 10 s when a constant load was applied. The desired duration and magnitude of the piezoelectric response voltage were realized by adjusting the number of turns of the piezoelectric rolls. Similarly to many other conventional piezoelectrics, the piezoelectric rolls enable instantaneous load-dependent voltage generation and attenuation. The piezoelectric rolls are also lighter than conventional piezoelectric ceramics and can be used as a novel pressure sensor.

Techno-Economic Collaboration of PEV Fleets in Energy Management of Microgrids

This paper develops a generalized energy management approach for smart microgrids (MGs) with the collaboration of plug-in electric vehicle (PEV) charging facilities in both active and reactive powers exchange. In addition to the monetary saving and economical benefits, this feature reveals a promising opportunity for power quality improvement in modern MGs. To do this, an efficient multi-objective framework is proposed for the optimal operation scheduling of MGs. The optimization model incorporates the full potential benefits of PEV fleets in balancing both active and reactive powers supply and demand. The multi-objective formulation lies within a mixed-integer linear programming fashion, which is tackled by $\varepsilon $ -constraint method. A quadruple linear operating area is envisioned for PEV fleet inverters caped with the maximum apparent power limit. A suitable voltage-dependent load model, with negligible error, is deployed to tailor the proposed approach for real-world applications. The new methodology is successfully applied to a 33-bus test MG with illustrative case studies. The obtained results are reported in terms of voltage profile improvement, released capacity of generating units, moderated operation of under-load tap changers, and MG operation cost reduction.

Probabilistic voltage stability assessment of distribution networks with wind generation using combined cumulants and maximum entropy method

From the voltage stability viewpoint, a proper probabilistic analysis of the active distribution networks is essential for distribution system operator to identify and rank the weak buses of system. This paper introduces a probabilistic voltage stability index (VSI) to study the local stability of radial distribution networks including wind generation uncertainty. This index can identify the most sensitive bus to the voltage collapse. The proposed model combines the cumulants with the maximum entropy technique based on a backward/forward sweep technique. The suggested method evaluates not only the voltage magnitude, but also the voltage stability condition of each node in a probabilistic manner. Furthermore, the uncertainties of distributed generation and load demand are taken into account by this index. The proposed methodology is applied to IEEE 33-bus and 69-bus distribution test systems, and the results are interpreted. Four scenarios are studied to assess the impacts of substation voltage changes and different probability density functions of load on the distribution functions of voltage and VSI. Moreover, the effects of voltage dependent load model on the probabilistic VSI are studied. The results of different case studies have demonstrated that the proposed approach is fast and accurate.