Franklin L. Quilumba

Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities

With the deployment of advanced metering infrastructure (AMI), an avalanche of new energy-use information became available. Better understanding of the actual power consumption patterns of customers is critical for improving load forecasting and efficient deployment of smart grid technologies to enhance operation, energy management, and planning of electric power systems. Unlike traditional aggregated system-level load forecasting, the AMI data introduces a fresh perspective to the way load forecasting is performed, ranging from very short-term load forecasting to long-term load forecasting at the system level, regional level, feeder level, or even down to the consumer level. This paper addresses the efforts involved in improving the system level intraday load forecasting by applying clustering to identify groups of customers with similar load consumption patterns from smart meters prior to performing load forecasting.

A Collaborative Design of Aggregated Residential Appliances and Renewable Energy for Demand Response Participation

Although the locational marginal price may change dramatically within a single day in competitive wholesale electricity markets, most end users are charged monthly electricity bills over flat rates. Without financial incentives, the customers are lacking of motivation to respond to the price signals, which may result in inefficient energy consumption. In Texas, Senate Bill 1125 encourages qualified residential and commercial customer classes to participate in demand response (DR) programs. This paper proposes an idea to aggregate a number of residential customers to participate in residential DR program by employing smart appliances and a home area network to shift the coincidental peak load to off-peak hours to reap financial benefits. The operation strategies for the most representative residential load types are discussed. To further reduce electricity purchase and cut electricity bills, a solar farm with energy storage system is proposed, and the control algorithm is designed accordingly. The operation strategies are simulated for a whole year, and the annual costs are calculated and compared in this paper. The results show that, by doing load control and utilizing renewable resources, the total operation cost can be reduced significantly.

Dispatch scheduling for a wind farm with hybrid energy storage based on wind and LMP forecasting

In a deregulated power market, the real-time wholesale market price of electricity varies dramatically within a single day due to the availability of the resources. Moreover, the price of electricity can be different from one location to the other at the same time period due to the location of the available resources and transmission constraints. This is the so-called locational marginal price (LMP). Since wind power is noncontrollable and partially unpredictable, it is difficult to schedule its output to exploit LMP variations. While energy storage system (ESS) may accommodate wind farm output, it requires significant initial financial commitment. Accurately forecasted wind power and LMP information can reduce the required capacity and make it financially feasible for the ESS to perform desired functions. In this paper, artificial neural network (ANN) technique is employed to forecast the day-ahead wind power and LMP, and a hybrid ESS consisting of two storage facilities is developed. The primary ESS is utilized for the optimizing wind-storage system production schedule with day-ahead forecasting data, while the secondary ESS is applied to address the forecasting errors during real-time operation. With this hybrid ESS design, financial benefits are achieved for the wind farm.

Demand response — An assessment of load participation in the ERCOT nodal market

The purpose of the restructured power market is to obtain maximum social benefits, including power generation and load customers. Although the power generation sector has been fully participating in the power market, relatively limited market options for demand sector to participate in the power market exist. Several Independent System Operators (ISOs) have deployed several terms of Demand Response (DR) programs in the auction power market. As an “intra-state” ISO, Electric Reliability Council of Texas (ERCOT) is responsible for the electric market in Texas. During the past several years, the demand response program in ERCOT had provided promising outcomes from both economic and reliability prospective. Both the improvement of the existing program and feasibility to create new program are always ERCOTs goal to increase the market efficiency and system reliability. Currently, demand-side resources, mainly on the industrial load class can participate into ancillary service market. To further promote demand-side response program, the market operation, regulatory intervention and special demand-side programs are needed. In addition, to meet the requirement of demand-side resource, the program may pay more attention to the commercial and residential customer in the future.

A collaborative design of aggregated residential appliances and renewable energy for demand response participation

Although the locational marginal price may change dramatically within a single day in competitive wholesale electricity markets, most end users are charged monthly electricity bills over flat rates. Without financial incentives, the customers are lacking of motivation to respond to the price signals, which may result in inefficient energy consumption. In Texas, Senate Bill 1125 encourages qualified residential and commercial customer classes to participate in demand response (DR) programs. This paper proposes an idea to aggregate a number of residential customers to participate in residential DR program by employing smart appliances and a home area network to shift the coincidental peak load to off-peak hours to reap financial benefits. The operation strategies for the most representative residential load types are discussed. To further reduce electricity purchase and cut electricity bills, a solar farm with energy storage system is proposed, and the control algorithm is designed accordingly. The operation strategies are simulated for a whole year, and the annual costs are calculated and compared in this paper. The results show that, by doing load control and utilizing renewable resources, the total operation cost can be reduced significantly.

AGC Parameter Determination for an Oil Facility Electric System

It is necessary to accurately estimate parameters to have a better prediction on the response of a generator under different operating conditions. Since automatic generation control (AGC) is closely related to the real power and frequency of the unit, the dynamic parameters that are required by a standard AGC function are determined for the electric system of an oil facility. Speed droop characteristics, governor deadbands, and generation ramp rates are evaluated using field tests on thermal units. Frequency bias for the area control error calculation is also presented. Test procedures for each parameter calculation are described in detail for thermal units of 1, 3, and 3.75 MW installed at Ecuadorian oil well facilities. Test results for these units demonstrate the practicability of the proposed test procedures.

Load models for flat panel TVs

A realistic representation of power system loads has proven to be essential to ensure reliable and economic operation of a power system. Although the exact load model is nearly impossible to obtain, it is still possible to find a suitable load representation that can improve dynamic simulations. With the ever increasing development of technology, electric appliances and equipment behavior have changed. In particular, home electronics, such as televisions, are a good example of these changes not only for their cutting edge technology but also for their penetration into the system. Electronic loads tend to behave mostly as constant power with respect to voltage variations, which leads to issues of instability in the system. Therefore, this paper describes the necessity of updating the load models by analyzing their effects on the stability of the power system. Then, it introduces the importance of television as a contributor of electricity consumption. Finally, ZIP load models for televisions are developed as means of obtaining a better representation of these loads.

Using a Microgrid test bed to evaluate the strategies for seamless renewable energy integration

The current limitations of infrastructure detain the power grid from meeting the requirement of the restructured power market and the integration of the renewable energy. The researches for the smart grid are necessary to develop the future power system. This paper presents the design, development, and hardware setting of the smart MicroGrid test bed at the University of Texas at Arlington. While the test bed can utilize the renewable energy sources like wind turbines, solar panels, and PEM fuel cell, it also has the capability of running in parallel with the utility grid. Since the smart micro grid acts as the basic unit of the smart grid, the test bed provides a playground for both research and education purposes. With real-time data acquisition and control devices, the operation of the smart MicroGrid test bed is also discussed in the paper.

Load Models for Flat-Panel TVs

A realistic representation of power system loads has proven to be essential for ensuring reliable and economic operation of a power system. Although the exact load model is nearly impossible to obtain, it is still possible to find a suitable load representation that can improve the accuracy of steady-state and dynamic simulations. Load model development has been a continuous effort among industry since the 1980s. However, with the ever increasing development of technology, electric appliances and equipment behavior have changed. In particular, home electronics, such as televisions, are a good example of these changes not only for their cutting edge technology but also for their penetration into the system. Electronic loads tend to behave mostly near constant power with respect to voltage and frequency variations, which may have significant impact on the system stability. Devoting efforts to include the load models of new appliances become a critical issue in the field of computer simulation. This paper devotes its efforts to develop ZIP load models for liquid-crystal-display and light-emitting-diode televisions to be added into the family of the load models to improve the accuracy of system simulation. A computer simulation of a power system illustrates the impact of load models on the stability of the power systems.

Distributed energy resources placement in distribution networks considering proximity to voltage collapse

The decline of voltage stability level is one of important factors which restrict the increase of load served by distribution companies. Major concern has been paid to voltage stability in transmission systems, but it can occur in distribution systems as well. Continuation Power Flow is a well-known method to analyze voltage stability phenomenon. It will be used to find the power margin index at each bus of the distribution system to identify the weakest buses from the voltage stability point of view. Those buses will constitute the optimal location for Distributed Energy Resources like Distributed Generation or Battery Storage Devices.