Residential Distribution Feeder Research Articles

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

AbstractElectric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

A Human-Centered Power Conservation Framework based on Reverse Auction Theory and Machine Learning

Extreme outside temperatures resulting from heat waves, winter storms, and similar weather-related events trigger the Heating Ventilation and Air Conditioning (HVAC) systems, resulting in challenging, and potentially catastrophic, peak loads. As a consequence, such extreme outside temperatures put a strain on power grids and may thus lead to blackouts. In order to avoid the financial and personal repercussions of peak loads, demand response and power conservation represent promising solutions. Despite numerous efforts, it has been shown that the current state-of-the-art fails to consider: i) the complexity of human behavior when interacting with power conservation systems; and ii) realistic home-level power dynamics. As a consequence, this leads to approaches that are i) ineffective due to poor long-term user engagement; and ii) too abstract to be used in real-world settings. In this paper, we propose an auction-theory-based power conservation framework for HVAC designed to address such individual human component through a three-fold approach: personalized preferences of power conservation, models of realistic user behavior , and realistic home-level power dynamics . In our framework, the System Operator (SO) sends Load Serving Entities (LSEs) the required power saving to tackle peak loads at the residential distribution feeder. Each LSE then prompts its users to provide bids , i.e., personalized preferences of thermostat temperature adjustments, along with corresponding financial compensations. We employ models of realistic user behavior by means of online surveys to gather user bids and evaluate user interaction with such system. Realistic home-level power dynamics are implemented by our machine-learning-based Power Saving Predictions (PSP) algorithm, calculating the individual power savings in each user’s home resulting from such bids. A machine-learning-based Power Saving Predictions (PSP) algorithm is executed by the users’ Smart Energy Management System (SEMS). PSP translates temperature adjustments into the corresponding power savings. Then, the SEMS sends bids back to the LSE, which selects the auction winners through an optimization problem called POwer Conservation Optimization (POCO). We prove that POCO is NP-hard, and thus provide two approaches to solve this problem. One approach is an optimal pseudo-polynomial algorithm called DYnamic programming Power Saving (DYPS), while the second is a heuristic polynomial-time algorithm called Greedy Ranking Allocation (GRAN). EnergyPlus, the high-fidelity and gold-standard energy simulator funded by the U.S. Department of Energy, was used to validate our experiments, as well as to collect data to train PSP. We further evaluate the results of the auctions across several scenarios, showing that, as expected, DYPS finds the optimal solution, while GRAN outperforms recent state-of-the-art approaches.

Forecasting voltage harmonic distortion in residential distribution networks using smart meter data

This paper introduces a methodology to forecast voltage total harmonic distortion (THD) at low voltage busbars of residential distribution feeders based on the data provided by a limited number of smart meters. The methodology provides relevant power quality indices to system operators using only the existing monitoring infrastructure required for demand response operation. Different algorithms for voltage THD forecasting are implemented, including artificial neural networks, and their performance is tested and compared. The necessary coverage of smart meters for the acceptable accuracy of the estimated THD is also established. The estimation algorithms are validated considering probabilistic demand load model developed based on typical harmonic injections of household devices obtained from measurements and using a typical European low voltage test-feeder with 471 residential consumers.

A Smart On-Line Centralized Coordinated Charging Strategy in Residential Distribution Networks

Environmental and economic aspects encourage the transition of conventional fuel-based vehicles to electric vehicles (EVs). However, the uncoordinated charging activities of EVs may increase the stress on the distribution networks. Coordination between EVs charging activities is the perfect way to avoid the negative consequences of unscheduled charging activities without reinforcing the existing network infrastructure. Many previous works proposed coordinated charging strategies but without considering some influencing factors like EV departure time and energy tariff. Some others used impractical assumptions like a very large parking period or forced the users to choose the preferred charging period before the vehicles' arrival. In this work, a centralized coordinated charging strategy is proposed to reduce EVs charging costs from users’ point of view side by side with the safe operation of the distribution network considering vehicle departure time and charging prices. The proposed strategy mainly determines the proper starting instant and the suitable charger power rate of the charging process. The proper starting instant of the EV charging process is calculated by ranking the charging priority of the arrived vehicles. In contrast, the charging power rate is estimated based on the available duration from starting instant to the instant of vehicle departure. The strategy is applied to a modified IEEE 31 bus residential distribution system with 22 residential distribution feeders. The results proved the proposed strategy’s effectiveness in reducing the charging costs, alleviating overloading on the main substation, improving voltage deviations, and reducing the power loss.

Power Factor Correction in Feeders With Distributed Photovoltaics Using Residential Appliances as Virtual Batteries

Thermostatically controlled residential appliances have built-in thermodynamic storage that, even within a narrow temperature band that does not degrade the comfort level of occupants, can be used to provide a variety of value streams to power system operators and customers. In this paper, residential air conditioners and electric water heaters are used to improve feeder power factor in a distribution system where photovoltaic systems cause the feeder power factor to dip daily, increasing losses. Improving distribution feeder power factor improves the efficiency of the transmission and bulk generation systems. A daily optimal dispatch regime is used to maximize the daily minimum feeder power factor. Following this regime, electric water heaters cool off in preparation for a low-feeder-power-factor event, turn on to improve the power factor during the event and return to a neutral condition after the event. Air conditioners, which have a power factor lower than the feeder overall, are optimally dispatched in the inverse pattern. Using a model of a real commercial and residential distribution feeder in the western United States, the optimal dispatch of virtual batteries is shown to be capable of improving the daily minimum power of that feeder by as much as 0.026. The power factor correction and optimal dispatch techniques are based on a robust virtual battery framework, making them portable to other applications, such as volt-var optimization and transactive energy systems.

Novel Residential Energy Demand Management Framework Based on Clustering Approach in Energy and Performance-based Regulation Service Markets

Flexible electric loads are key elements in the path to a sustainable electric grid with high penetration of green resources. With the increasing level of intermittent wind and solar generation replacing the conventional power plants, there is a growing trend to involve electricity consumers in the balancing activity between the generation and consumption. In this paper, a bi-level demand response scheduling framework is proposed for residential load aggregators in which the planning scope spans a diverse set of loads and activities including inflexible loads, electric vehicles, air conditioning and water heating TCLs, energy storage system, and energy and regulation service scheduling on a residential distribution feeder with relevant constraints. Novel aggregation mechanism is proposed to capture the flexibility of heterogeneous loads based on clustering concept. In particular, the aggregation model of rapidly-growing inverter-based TCLs is derived using the proposed clustering techniques. Also, participation in regulation service market is based on the performance-based compensation scheme adopted by ISOs. The presented approach is applicable to day-ahead and real-time markets with a reliably fast calculation process. The results are indicative of the accuracy and sufficiency of the derived models.

THD Reduction of Distribution System Based on ASRFC and HVC Method for SVC under EV Charger Condition for Power Factor Improvement

Electric vehicles (EVs) have been gaining popularity in recent years due to growing concerns about fuel depletion and increasing petrol prices. Random uncoordinated charging of multiple EVs at residential distribution feeders with moderate penetration levels is expected in the near future. This paper describes a high performance voltage controller for the EVs charging system, and proposes a scheme of asymmetric synchronous reference frame controller (ASRFC) in order to compensate for the voltage distortions and unbalance distribution system due to EVs charger. This paper explores the power factor of distribution and residential network under random EVs charger on the bus load. ASRFC and harmonic voltage compensator (HVC) are employed for static VAR compensator (SVC) in this paper. The proposed scheme can improve the power factor and total harmonic distortion (THD) of the smart grid due to the EVs charger in grid. The effectiveness of the scheme was investigated and verified through computer simulations of a 22.9-kV grid.

Predictive control of residential HVAC and its impact on the grid. Part II: simulation studies of residential HVAC as a supply following resource

This paper introduces a methodology, using model predictive control, for shaping the electric demand of residential distribution feeder. The methods are designed to result in a paradigm shift from generation that follows load to load that follows supply. First, a reference demand curve, obtained from “smoothing” a base case demand profile, is proposed. Then, in order to better match the availability of renewable energy resources, the reference demand curve is modified to consider residential rooftop photovoltaic systems and utility scale wind generation. A simulation framework introduced in a companion paper is employed. Simulation results suggest that the active load shaping methodology is very effective at providing demand flexibility at time scales shorter than two or three hours. At longer time scales, flexibility is limited by the thermal storage effectiveness of the residential building envelope, and to a large extent, the amount of load being shifted relative to total active cooling demand.

Evaluating the Magnitude and Duration of Cold Load Pick-up on Residential Distribution FeedersUsing Multi-State Load Models

The increased level of demand that is associated with the restoration of service after an outage, Cold Load Pick-Up (CLPU), can be significantly higher than pre-outage levels, even exceeding the normal distribution feeder peak demand. These high levels of demand can delay restoration efforts and in extreme cases damage equipment. The negative impacts of CLPU can be mitigated with strategies that restore the feeder in sections, minimizing the load current. The challenge for utilities is to manage the current level on critical equipment while minimizing the time to restore service to all customers. Accurately modeling CLPU events is the first step in developing improved restoration strategies that minimize restoration times. This paper presents a new method for evaluating the magnitude of the CLPU peak, and its duration, using multi-state load models. The use of multi-state load models allows for a more accurate representation of the end-use loads that are present on residential distribution feeders.

Coupling of neighbouring low voltage residential distribution feeders for voltage profile improvement using power electronics converters

Low voltage feeders (LVFs) experience several voltage quality (VQ) issues such as voltage drop at network peak periods, voltage rise at middays when high number of rooftop photovoltaic cells (PVs) are existing in the feeder, rapid voltage fluctuations as the results of the clouds effects on the power generation of PVs, and voltage unbalance due to the inherent random characteristics of the single-phase loads and PVs. This study addresses these problems by proposing the concept of coupling the neighbouring LVFs. Based on this concept, two or more LVFs of the same distribution transformer or different distribution transformers are interconnected to support each other and minimise the VQ problems. First, the performance of LVFs in the existing form is discussed and three approaches of coupling the LVFs are presented. Among the presented techniques, coupling of LVFs through a distribution static compensator (DSTATCOM) at the end of the feeder is proposed and focused as an effective technique with minimal side effects such as power losses and cost. Proper dynamic control methods are also proposed for the DSTATCOM and the performance of such a system is investigated under steady-state and dynamic conditions via numerical analysis and simulation studies in MATLAB and PSCAD/EMTDC.

Coordinated Control of Grid-Connected Photovoltaic Reactive Power and Battery Energy Storage Systems to Improve the Voltage Profile of a Residential Distribution Feeder

Increasing penetration of photovoltaic (PV), as well as increasing peak load demand, has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and battery energy storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop-based BES system is evaluated for rural and urban scenarios (having different \mbi R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low-resistance feeder), whereas coordinated PV and BES support is required for the rural scenario (high-resistance feeder). Constant, as well as variable, droop-based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes are presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data are used to verify the efficacy of the proposed method.

Effectiveness of Reactive Power Capability of Photo Voltaic Inverters to Maintain Voltage Profile in a Residential Distribution Feeder

AbstractAbstract—Large penetration of rooftop PVs has resulted in unacceptable voltage profile in many residential distribution feeders. Limiting real power injection from PVs to alleviate over voltage problem is not feasible due to loss of green power and hence corresponding revenue loss. Reactive capability of the PV inverter can be a solution to address over voltage and voltage dip problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness for voltage improvement based on R/X ratio of the feeder. The length and loading level of the feeder for a particular R/X ratio to have acceptable voltage profile is also investigated. This can be useful for suburban design and residential distribution planning. Furthermore, coordination among different PVs using residential smart meters via a substation based controller is also proposed.

Effectiveness of Reactive Power Capability of Photo Voltaic Inverters to Maintain Voltage Profile in a Residential Distribution Feeder

Effectiveness of Reactive Power Capability of Photo Voltaic Inverters to Maintain Voltage Profile in a Residential Distribution Feeder

Analysis of injected apparent power and flicker in a distribution network after wind power plant connection

The maximum apparent power that can be injected in a bus and the flicker emission can represent a significant limit in the total capacity of a wind farm when wind turbines are connected to a radial distribution system. Quantification of these values is important in determining the largest number of wind turbines that can be connected in a network. The calculation of maximum apparent power and flicker of residential and commercial radial distribution feeder with remotely connected wind turbines has been investigated using elaborated specific software denominated winds port program and data from two energy systems. The developed software can calculate the approximate injected maximum apparent power, for a wind farm, in one bus of the network and in two buses of the network, simultaneously, without the need of a load flow program. The various simulations results reveal that wind farm capacities, in each bus, can be limited firstly for flicker and later for bus injected power for a voltage variation value, and the calculation of approximate apparent powers allows a precise and fast adjustment of voltage variation. If a load flow program is used for the determination of the wind farm maximum apparent power in each bus of the distribution system, a lot of simulations with a lot of attempts must be necessary. Therefore the methodology used by the authors is advantageous.

Residential load modeling for predicting distribution transformer load behavior, feeder load and cold load pickup

This paper presents a physically based model for computing the electric load on residential distribution feeders and on distribution transformers. The load is assumed to consist of electric space heating, electric water heating and other miscellaneous devices. Validation against field tests and field monitoring records shows the accuracy of the approach both for steady-state operation and for power restoration conditions. The magnitude and duration of cold load pickup is predicted more accurately with the approach presented than with previous models.

Impact of remotely connected wind turbines on steady state operation of radial distribution networks

Remotely connected wind farms can have a significant impact on voltages, load demand and power losses in radial distribution networks. Quantification of these effects is important in determining the true value of wind energy and requires detailed simulations of integrated network behaviour over an extended period of time. The steady state behaviour of commercial and residential radial distribution feeders with remotely connected wind turbines has been investigated using a recursive, loadflow-based simulation algorithm and time series data from a known system. The results of annual simulations reveal that large wind farm capacities can be freely operated in remote locations without violation of voltage limits and with a net reduction in feeder energy consumption. With automatic control of real and reactive power flows from the wind farm, connected capacity can be significantly expanded before operation becomes infeasible.

General probabilistic voltage drop calculation method for LV distribution networks based on a beta p.d.f. load model

In previous work, it was shown that a probabilistic approach to the calculation of voltage regulation in low voltage residential distribution feeders is superior to deterministic methods. The probabilistic technique, known as the Herman Beta method, is now being used on a national scale in South Africa for the design of residential distribution circuits. This paper describes enhancements to the Herman Beta method that improves accuracy and particularly addresses the issue of successive risk.

The application of load models of electric appliances to distribution system analysis

This paper proposes a methodology to apply the load models of key electric appliances in residential area for distribution system analysis. According to the load models, the transformer hourly loading is estimated during simulation iteration by the bus voltage and ambient temperature. A three phase load flow program is then executed to find the feeder daily profile of power consumption and system loss with the transformer hourly loading derived. Besides, the daily power consumption by each type of key appliance can also be solved. To demonstrate the effectiveness of the proposed method, a distribution feeder of Taipower system is selected for computer simulation to find the potential of energy conservation by controlling the feeder service voltage at the substation. Moreover, the load model of air conditioners, which are temperature sensitive appliances, is also considered in the program to find the impact of ambient temperature change to the power consumption of residential distribution feeders. It is concluded that the load models of key electric appliances can provide a useful tool for distribution engineers to enhance the accuracy of system analysis to estimate the operation efficiency of distribution system in a more effective manner. >