Feeder Load Research Articles

Research on Multi-mode Operation Control Strategy of Feeder Flexible Interconnection in Distribution Network Based on Flexible Multi-State Switch

Aiming at the problems of multi-mode operation and switching, unbalanced feeder load and heavy load of main transformer in flexible interconnection system of distribution network based on Flexible Multi-State Switch(FMSS), a multi-mode operation control strategy of feeder interconnection in distribution network based on Virtual Synchronous Generator (VSG) is proposed,which includes load balancing control strategy and heavy load main transformer automatic control strategy. Firstly, according to the feeder and main transformer load status, the operation mode of system is divided.Then, through the analysis power transmission and switching logic of different operating mode, active power control instructions of FMSS under multi-mode operation are obtained. So that multi-mode stable operation and free switching of the system, the feeder load balancing and main transformer heavy load automatic regulation are realized. In addition, there is no need for control strategy switching. Simulation verifies the rationality and effectiveness of the proposed control strategy.

Analysis of interconnected configuration for penetration of distributed generation

This paper visualizes the feasibility of the proposed interconnected distributed power system configuration, which aims at incorporating the electricity generation from renewables and to cater to low voltage areas of radial distribution network. The shortcoming of existing traditional radial systems is inconsistent load distribution and technical viability in incorporating renewable sources without disturbing the power system. Sustainable development is achieved with improvement in the prevailing distribution system. Maximum potential benefits in terms of demand-supply balance and integrating renewables can be achieved by selecting properly placed and optimally sized distributed generation sources in a distribution network. The generation facility is selected as per the geographical profile of the location and placed on the weakest node. The weakest node is the low voltage profile region where the maximum output of the integration of power sources is beneficial. In this paper, the ZIP model-based methodology is applied to feeder loads on the data set of the distribution grid of the National University of Science & Technology (NUST), Islamabad, Pakistan. The comparative analysis is performed on a radial network of NUST distribution grid and compared with a simulated interconnected distribution system of the same distribution network on MATLAB software as a case study to observe the performance of interconnected power systems. This analysis results in better voltage profiles for interconnected networks, compared to radial networks. That said, incorporating a Distributed Generation (DG) source in the interconnected network builds a substantial impact on the distribution system voltage profile. The efficacy of the proposed interconnected system confirms the performance improvement of the distribution power system. The VSI values for interconnected systems give better results which is further justified by the machine learning algorithm, Logistic regression. The simulation results indicate that the Interconnected system encourages penetrations of solar, wind, gas turbine, and other renewable sources near the low voltage end in the distribution system. © 2021 Bilal Asghar Farooqi et al.

Experimental Validation of a Reduced-Scale Rail Power Conditioner Based on Modular Multilevel Converter for AC Railway Power Grids

Rail power conditioner (RPC) has the ability to improve the power quality in AC railway power grids. This power conditioner can increase the loading capacity of traction substations, balance the active power between the feeder load sections, and compensate for reactive power and current harmonics. At present, there is increasing use of multilevel converter topologies, which provide scalability and robust performance under different conditions. In this framework, modular multilevel converter (MMC) is emerging as a prominent solution for medium-voltage applications. Serving that purpose, this paper focuses on the implementation, testing, and validation of a reduced-scale laboratory prototype of a proposed RPC based on an MMC. The developed laboratory prototype, designed to be compact, reliable, and adaptable to multipurpose applications, is presented, highlighting the main control and power circuit boards of the MMC. In addition, MMC parameter design of the filter inductor and submodule capacitor is also explained. Experimental analysis and validation of a reduced-scale prototype RPC based on MMC topology, are provided to verify the power quality improvement in electrified railway power grids. Thus, two experimental case studies are presented: (1) when both of the load sections are unequally loaded; (2) when only one load section is loaded. Experimental results confirm the RPC based on MMC is effective in reducing the harmonic contents, solving the problem of three-phase current imbalance and compensating reactive power.

Analyzing Electric Vehicle Load Impact on Power Systems: Modeling Analysis and a Case Study for Maldives

Electric vehicles (EVs) can have massive benefits in energy sector especially for a small island country like the Maldives that imports oil with high transportation costs while power could have been generated from abundantly available local renewable resources. However, EV charging may also impose significant investment requirement for the power system that needs to be analyzed carefully including the capacity of the existing distribution network system, investments needed in solar PV together with battery storage and additional diesel capacity to meet the incremental demand from EVs. We explore an EV adoption scenario for Maldives for 2030 with 30% of all vehicles including two-wheelers that dominate the transport on the island under two different charging regimes: uncoordinated and optimized coordinated mode. The latter is achieved through a system wide optimization using a modified version of the World Bank Electricity Planning Model (EPM) that optimizes charging load subject to a range of constraints on allowable timing for different categories of vehicles. If charging from the fleet is uncoordinated, a relatively small increase in energy requirement of 3.1% due to EV may lead to a 26.1% increase in generation capacity requirement and hence 15.7% additional investment. While the optimized charging regime helps to drastically cut down on generation capacity requirements to just 1.8% increase and also considerably eases feeder loading, it may also lead to higher emissions as more EV load during off-peak hours lead to an increase in diesel-based generation. We have therefore explored an additional scenario wherein the annual emissions from the power sector are constrained to the baseline (“No EV”) scenario. The analysis shows the importance of focused modeling analysis to understand the ramifications of EV load impact on the power system including significant increase in generation capacity and potential increase in power sector emissions in a fossil-fuel dominated system.

Two full capacity generators—Why is the calculated emergency power system probability of failure on demand so high?

AbstractThe probability of failure on demand (PFD) for an emergency generator system is important when electrical power is needed to protect humans from harm or to prevent equipment damage. To evaluate the PFD for an emergency power system (EPS), we must consider: All the components for the fuel, the controls, the transfer switches, and the circuit breakers in the emergency load feeders. The capability of the weekly, monthly, semiannual, annual, and four‐year inspections and proof tests to detect all the failure modes that can prevent correct operation of the generator system. Many common cause events may prevent both generators from starting or running: The fuel storage system. The generator control system including over‐voltage and overload protection. The downstream electrical system including the transfer switches and circuit breakers. Human action during maintenance and testing, such as leaving the transfer switches in test mode instead of automatic. While the EPS may be designed and operated according to NFPA 110, it is critical to evaluate and eliminate single points of failure. The paper will suggest opportunities to provide redundancy, to manage human error, and to improve inspections and proof testing to detect more failure modes.

Impact of Photovoltaic System Integration on Low Voltage Network

In this paper, we perform an analysis of the Photovoltaic penetrations on Low Voltage Power Distribution Networks. A case study of the East Legon Power Distribution Services M05/52 LV Network. The impacts of high photovoltaic penetration on voltage level and power factors are explored. We fixed power quality analyzers at the distribution substation and at the customers’ nodes; to capture the feeder loads and the voltage profiles. Simulations are done at varying photovoltaic penetrations levels to determine the strike of increasing photovoltaic incursion on the low voltage power network. We present results to show that, the optimum penetration level is achieved at the point where minimum loss reduction is recorded, reverse flow not present and power factor limit is not violated.

Voltage violation in four‐wire distribution networks integrated with rooftop PV systems

Integration of rooftop photovoltaic (PV) systems in a three-phase four-wire distribution network cause voltage-violations namely voltage-rise and voltage unbalance. This study investigates the factors that affect both the voltage-rise and voltage unbalance in low voltage distribution network integrated with the rooftop PV systems. The concerning factors are classified into active factors such as; loads active powers, PV active powers, and bus reactive powers, and passive factors such as; numbers of feeder buses and neutral-grounded resistances. The study also determines the factors conditions at which the highest values of both voltage-rise and voltage unbalance occurred. Moreover, the most and least significant effects of individual factors on both voltage-rise and voltage unbalance are studied. The studied system is simulated and implemented in MATLAB software environment and the feeder loads are modelled based on Back–Forward Sweep method. The simulation results identify that the conditions of the worst voltage-rise and voltage unbalance cases depend on the collective influence of the studied factors.

An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System

Recent developments, such as smart metering, distributed energy resources, microgrids, and energy storage, have led to an exponential increase in system complexity and have emphasized the need to include customer behavior and social and cultural backgrounds in planning activities. This paper analyzes how emergent behavior in electricity consumption can affect the planning of distribution grids with a smart grid vision. For this, an agent-based model that uses insights from the field of behavioral economics to differentiate four consumer categories (high income, low income, middle class, and early adopters) was used. The model was coupled with a real distribution feeder and customer load curve data, and the results showed that heterogeneity of customer’s preferences, values, and behavior led to very distinct load growth patterns. The results emphasize the relevance of modeling customer’s behavioral aspects in planning increasingly complex power systems.

Control of Pervasive Domestic-Scale Inverters for Minimizing Total Feeder Power

This paper proposes a method for studying the potential benefits of reactive power control by domestic-scale inverters, considering network losses, inverter losses, and load-voltage sensitivity. The model is developed as a mixed-integer quadratically constrained quadratic program (MI-QCQP), using a linearization of the unbalanced distribution load flow equations. Networks both with and without on-load tap changers are studied, with the test cases covering both European and North American-style circuits. The use of domestic inverter control is shown to increase benefits compared to conventional tap control by 20%, reducing the total feeder power draw by as much as 0.5% of the feeder load. In contrast, the minimization of either load or losses in isolation is shown to increase the amount of power that a feeder draws in five of the seven circuits. To reduce the communications overhead of the approach, a control scheme is proposed that specifies the reactive power of all inverters on each phase identically; this approach is shown to realise up to 98% of the potential benefits of inverter reactive power control.

A Data-Driven Pivot-Point-Based Time-Series Feeder Load Disaggregation Method

The load profile at a feeder-head is usually known to utility engineers while the nodal load profiles are not. However, the nodal load profiles are increasingly important for conducting time-series analysis in distribution systems. Therefore, in this paper, we present a pivot-point based, two-stage feeder load disaggregation algorithm using smart meter data. The two stages are load profile selection (LPS) and load profile allocation (LPA). In the LPS stage, a random load profile selection process is first executed to meet the load diversity requirement. Then, a few pairs of pivot points are selected as the matching targets. After that, a matching algorithm will run repetitively to select one load profile at a time for matching the reference load profile at the pivot points. In the LPA stage, the LPS selected load profiles are allocated to each load node on the feeder considering distribution transformer loading limits, load composition, and square-footage. The proposed method is validated using actual data collected in a North Carolina service area. Simulation results show that the proposed method can generate a unique load shape for each load node while match the shape of their aggregated profile with the actual feeder head load profile.

Battery charging and discharging scheduling with demand response for an electric bus public transportation system

This paper presents a case study of the Penghu bus transportation system wherein all the diesel buses were considered for replacement with battery-swapping e-buses. A genetic algorithm was employed to optimize the battery charging and discharging capacity at different time points during the timeframe, thereby minimizing the total single-day cost of the bus system. Demand response was used to adjust the main transformer load by using the residual capacity of the batteries. However, the resale of electricity increased the total cost because more batteries were required, battery life was shortened due to more charging cycles being performed, and energy was lost. Two cases were used to elucidate this problem. In case 1, the battery charging and discharging schedule was optimized for different maximum residual battery capacities. In case 2, we additionally considered wind and solar power generation, feeder load, and demand response. The results revealed that the total single-day cost in case 2 was 13%–17% higher than that of case 1. Finally, revenue from the resale of electricity was found to be higher than the added cost of conducting demand response when the resale price of electricity was twice that of the electricity rate offered by the power company.

Reliability improvement of distribution system considering EV parking lots

Metropolitan cities have hundreds of parking lots (PLs), where each PL may have a capacity to hold hundreds of cars. Large-scale use of electric vehicles coupled with technological advancements in battery storage systems provide several technical and economic benefits of integrating PLs into the grid. This study presents the impacts of electric vehicle PLs on the distribution system reliability. The reliability indices of the distribution feeder are determined using recently proposed novel storage capacity model of a PL that accounts for the load and component outage data of the distribution feeder. The paper uses average interruption duration, average interruption frequency, and energy not served as feeder reliability indices. For load point reliability indices interruption frequency, interruption duration and energy not served are used. Numerical results, thus attained, show that for the backup operation mode of the PL; the feeder reliability indices and load point reliability indices improve up to 26% and 44% respectively.

Virtual Impedance Control Scheme to Compensate for Voltage Harmonics With Accurate Harmonic Power Sharing in Islanded Microgrids

In case of voltage harmonic compensation at the point of common coupling (PCC) in islanded microgrids, it is important to share the harmonic load power correctly among the distributed generators (DGs) to use the DGs' capacity effectively. In previous DG control schemes, it is impossible to satisfy the requirements of PCC voltage quality and accurate harmonic power sharing simultaneously with only a virtual impedance controller (VIC). In this article, we propose an enhanced DG VIC to provide accurate harmonic power sharing along with voltage harmonic compensation in islanded microgrids. The proposed VIC is developed based on simple integral controllers with two controllable parts and no information about the feeder impedances or load currents. The control performance is theoretically analyzed using a small-signal state-space model to evaluate the system dynamics and stability. The feasibility and effectiveness of the method are validated by simulated and experimental results.

Enhancing the voltage stability of distribution network during PV ramping conditions with variable speed drive loads

The Photovoltaic (PV) sources have become the most popular renewable energy resources as it is modular and are deployed quickly. However, the distributed PVs are highly volatile and can have high ramping characteristics where the ramping can go up to 90% of its capacity in about 20 s due to events such as the passing of fast-moving clouds. This kind of PV ramps with high magnitudes can lead to voltage instability in distribution networks that are usually dominated by Induction motor (IM) loads. This paper explains the mechanism of such an instability analytically using Q-V analysis with distribution feeder and IM load characteristics. Highlighting the gradual replacement of IM loads by Variable Speed Drive (VSD) loads due to energy efficiency policies, the paper demonstrates the enhanced voltage stability under VSD loads by both time simulation and analytical approach. Furthermore, the analysis is extended to a realistic distribution network namely, United Kingdom General Distribution System (UKGDS) and extensive case studies are conducted to analyze the voltage stability during PV ramping events at various load compositions of IMs and VSDs. Moreover, the minimum VSD penetration level required to avert the voltage instability at various PV penetration levels have also been determined.

Distributed control scheme for accurate reactive power sharing with enhanced voltage quality for islanded microgrids

This study presents a distributed control scheme for islanded microgrids to eliminate power sharing errors as well as frequency and voltage deviations based on distributed cooperative control. A consensus algorithm is developed through adaptive regulation of the virtual impedances for accurate power sharing regardless of load variations. The proposed power sharing controller is quite easy to implement with only one simple integral gain. It is achieved without using information about the feeder impedances, load powers or detailed microgrid structure. To remove the deviations in the frequency and voltage magnitude, conventional droop equations are enhanced by adding compensating signals, which are simply determined from the neighbors’ droop information without a PI controller. Therefore, the control complexity is significantly reduced. The control performance is theoretically analyzed using a small-signal state-space model to evaluate the system dynamics and stability. A digital simulation is done using PSIM, and experiments are carried out with a scaled-down microgrid prototype to verify the proposed scheme.

Load Distribution Constraints Based Power Supply Capacity Calculation for a Distribution Network

Starting from the application purpose of real distribution network planning, for the high-voltage distribution network connected by medium-voltage tie lines, the power supply capacity is predicted according to current feeder loads and their changing trends, so that the results are more realistic. Based on the above calculation process, the weakness of a distribution network can be identified intuitively and conveniently, which can be used as the basis for generating the measures or schemes to improve power supply capacities. Numerical examples show that the presented model and method are intuitive, simple, and stable and effective compared with the existing methods, and are convenient for application in practice.

Impact of an electrified parkade on the built environment: An unsupervised learning approach

Proposed legislation in British Columbia would require 30 percent of new car sales to be zero-emission vehicles by 2030, and 100 percent by 2040. The growing amount of energy demand and usage data from smart meters or internet of things (IoT) devices enables new research areas. We reporton machine learning approaches to reevaluate the impacts of battery electric vehicles (BEV) on the built environment. We developed a daily power profile analysis based on unsupervised learning, to understand the underlying structure of building and BEV charging station demand data. In addition, we have implemented a load aggregation method based on the features revealed by a clustering process. This aggregation method simulates the electricity demand of an arbitrary number of charging stations, all of which are connected to the main feeder of a building. Several scenarios are simulated using charging stations and building demand data from the University of British Columbia campus in Vancouver. Results for 150 charging stations revealed that the feeder load could increase from a peak load scenario of 300 kW to more than 1000 kW during a high-consumption weekday.

A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction

Distribution feeder long-term load forecast (LTLF) is a critical task many electric utility companies perform on an annual basis. The goal of this task is to forecast the annual load of distribution feeders. The previous top-down and bottom-up LTLF methods are unable to incorporate different levels of information. This paper proposes a hybrid modeling method using sequence prediction for this classic and important task. The proposed method can seamlessly integrate top-down, bottom-up and sequential information hidden in multi-year data. Two advanced sequence prediction models Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks are investigated in this paper. They successfully solve the vanishing and exploding gradient problems a standard recurrent neural network has. This paper firstly explains the theories of LSTM and GRU networks and then discusses the steps of feature selection, feature engineering and model implementation in detail. In the end, a real-world application example for a large urban grid in West Canada is provided. LSTM and GRU networks under different sequential configurations and traditional models including bottom-up, ARIMA and feed-forward neural network are all implemented and compared in detail. The proposed method demonstrates superior performance and great practicality.

Retracted: Rearrangement of Electrical Distribution Networks With Optimal Coordination of Grid-Connected Hybrid Electric Vehicles and Wind Power Generation Sources

In this paper, a new model for distribution network rearrangement (DNR) with regard to plug-in electric vehicles (PEVs) is presented. The proposed model is a random model (random programming) in which scenarios corresponding to vehicle uncertainty are simulated by the Monte Carlo method. The distribution system was also mathematically modeled by an approximate linear model. This way of modeling helps us to derive a new design based on linear integer programming. The electricity market is considered to be the day-ahead electricity market. Uncertainties regarding the price of electricity as well as the load of the distribution network are also considered. The simulation results on a 24-bus distribution system showed that the proposed model has the required efficiency. Uncertainties related to PEVs are modeled by random programming using Monte Carlo Simulation (MCS). The DNR problem is formulated as a MILP problem. This problem is then solved by the Banders decomposition (BD) algorithm. Numerical results also showed that if the PEV is charged intelligently in the DNR issue, then the cost of purchasing electricity from above will be lower than in the case where the PEV is not controlled in a controlled way. We also see a different switching strategy in these two cases, which indicates that considering the electric vehicle in the DNR problem is inevitable. In addition, a method for rearranging distribution networks to transfer load from one feeder to another was presented. It has been observed that this reduces the load of high-capacity feeders well and causes the construction of new feeders to be delayed. It was also observed that rearrangement of the distribution network leads to a reduction in network losses. Also, with the help of rearrangement, the amount of interrupted load can be significantly reduced.

A distributed control strategy of microgrid based on multi-agent consensus algorithm

In an islanded microgrid with distributed generators (DGs), on account of the influence of feeder impedance, load and other factors, it is difficult to dispatch output power reasonably by means of droop control, therefore the secondary control is employed to solve this problem. However, the convention methods may fail to achieve the expected effect. In this context, an improved distributed control strategy based on multi-agent consensus algorithm is proposed in this paper. A virtual leader is set to track the balance of power. Through the mutual communication between DGs, it can realize the flexible distribution of load power and has good convergence. By introducing the integral controller on the basis of conventional droop control, the droop curve can move adaptively to maintain frequency and voltage stable. Finally, the effectiveness of the proposed scheme and the performance of anti-communication failure are verified in MATLAB/Simulink simulation platform.