Jason C. Fuller

Aggregate model for heterogeneous thermostatically controlled loads with demand response

Due to the potentially large number of Distributed Energy Resources (DERs) - demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies, where dynamics on time scales of seconds to minutes are important. On the other hand, a less complex model is more amenable to study stability of a large power system, and to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop an aggregated model for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response. The aggregated model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. The developed aggregated model is validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions.

Evaluation of Conservation Voltage Reduction (CVR) on a National Level

Conservation Voltage Reduction (CVR) is a reduction of energy consumption resulting from a reduction of feeder voltage. While there have been numerous CVR systems deployed in North America there has been little substantive analytic analysis of the effect; the majority of the published results are based on empirical field measurements. Since these results are based on empirical measurements it is difficult to extrapolate how this technology will behave on the various types of distribution feeders found throughout the nation. This report has utilized the Taxonomy of Prototypical feeder developed under the Modern Grid Initiative (MGI), now the Modern Grid Strategy (MGS), in order to estimate the benefits of CVR on multiple distribution feeder types. This information will then be used to determine an estimate of the national benefits of a wide scale deployment of CVR.

Multi-State Load Models for Distribution System Analysis

Recent work in the field of distribution system analysis has shown that the traditional method of peak load analysis is not adequate for the evaluation of emerging distribution system technologies. Voltage optimization, demand response, electric vehicle charging, and energy storage are examples of technologies with characteristics having daily, seasonal, and/or annual variations. In addition to the seasonal variations, emerging technologies such as demand response and plug-in electric vehicle charging have the potential to receive control signals that affects their energy consumption. To support time-series analysis over different time frames and to incorporate potential control signal inputs, detailed end-use load models that accurately represent loads under various conditions, and not just during the peak load period, are necessary. This paper will build on previous end-use load modeling work and outline the methods of general multi-state load models for distribution system analysis.

Analysis of Residential Demand Response and double-auction markets

Demand response and dynamic pricing programs are expected to play increasing roles in the modern smart grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction, can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies, coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

Effects of distributed energy resources on conservation voltage reduction (CVR)

Conservation voltage reduction (CVR) is one of the cheapest technologies that can be intelligently leveraged to provide considerable energy savings. The addition of renewables in the form of distributed resources can affect the entire power system, but more importantly, affects the traditional substation control schemes at the distribution level. This paper looks at the effect on energy consumption, peak load reduction, and voltage profile changes caused bu the addition of distributed generation in a distribution feeder using a volt-var control (VVC) technique for CVR with different end-of-line (EOL) measurements. An IEEE 13-node system is used to simulate the various cases. Energy savings and peak load reduction for different simulation scenarios are compared.

Analysis of distribution level residential demand response

Control of end use loads has existed in the form of direct load control for decades. Direct load control systems allow a utility to interrupt power to a medium to large size commercial or industrial customer a set number of times a year. With the current proliferation of computing resources and communications systems the ability to extend the direct load control systems now exists. Demand response systems now have the ability to not only engage commercial and industrial customers, but also the individual residential customers. Additionally, the ability exists to have automated control systems which operate on a continual basis instead of the traditional load control systems which could only be operated a set number of times a year. These emerging demand response systems have the capability to engage a larger portion of the end use load and do so in a more controlled manner. This paper will examine the impact that demand response systems have on the operation of an electric power distribution system.

Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response

One of the salient features of the smart grid is the wide spread use of distributed energy resources (DERs) like small wind turbines, photovoltaic (PV) panels, energy storage (batteries, flywheels, etc), Plug-in Hybrid Electric Vehicles (PHEVs) and controllable end-use loads. The affect of these distributed resources on the distribution feeder and on transmission system operations needs to be understood. Due to the potentially large number of DERs that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. This paper focuses on developing aggregated models for a population of Thermostatic Controlled Loads (TCLs) which are a class of controllable end-use loads. The developed reduced-order models are validated against simulations of thousands of detailed building models using an open source distribution simulation software (Grid LAB-D) under both steady state and dynamic conditions (thermostat setback program as a simple form of demand response).

Detailed end use load modeling for distribution system analysis

The field of distribution system analysis has made significant advances in the past ten years. It is now standard practice when performing a power flow simulation to use an algorithm that is capable of unbalanced per-phase analysis. Recent work has also focused on examining the need for time-series simulations instead of examining a single time period, i.e., peak loading. One area that still requires a significant amount of work is the proper modeling of end use loads. Currently it is common practice to use a simple load model consisting of a combination of constant power, constant impedance, and constant current elements. While this simple form of end use load modeling is sufficient for a single point in time, the exact model values are difficult to determine and it is inadequate for some time-series simulations. This paper will examine how to improve simple time invariant load models as well as develop multi-state time variant models.

AEP Ohio gridSMART Demonstration Project Real-Time Pricing Demonstration Analysis

This report contributes initial findings from an analysis of significant aspects of the gridSMART® Real-Time Pricing (RTP) – Double Auction demonstration project. Over the course of four years, Pacific Northwest National Laboratory (PNNL) worked with American Electric Power (AEP), Ohio and Battelle Memorial Institute to design, build, and operate an innovative system to engage residential consumers and their end-use resources in a participatory approach to electric system operations, an incentive-based approach that has the promise of providing greater efficiency under normal operating conditions and greater flexibility to react under situations of system stress. The material contained in this report supplements the findings documented by AEP Ohio in the main body of the gridSMART report. It delves into three main areas: impacts on system operations, impacts on households, and observations about the sensitivity of load to price changes.