Steve Willard
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Publication
Featured researches published by Steve Willard.
photovoltaic specialists conference | 2012
Abraham Ellis; David A. Schoenwald; Jon Hawkins; Steve Willard; Brian Arellano
This paper describes a simple algorithm designed to reduce the variability of photovoltaic (PV) power output by using an energy storage device. A full-scale implementation was deployed in an actual PV-Energy demonstration project, in partnership with a utility and a battery manufacturer. The paper describes simulation tests as well as field results. In addition to demonstrating implementation of smoothing controls, this work also served to verify the models, identify best parameter sets for utility operations, and study the operation of an advanced energy storage system under partial state of charge and rapid, irregular charge/discharge cycling.
ieee pes innovative smart grid technologies conference | 2012
Olga Lavrova; Feng Cheng; Shahin Abdollahy; Hans Barsun; Andrea Mammoli; D. Dreisigmayer; Steve Willard; Brian Arellano; C. van Zeyl
A Smart Grid demonstration project is currently underway at Public Service Company of New Mexico (PNM). The project combines both residential and commercial loads on a dedicated feeder, with high PV penetration ratio, equipped with a 0.5MW substation-sited photovoltaic (PV) system and large-scale utility storage. The unique aspect of the battery storage system being used, is that both slow (load-shifting) and fast (intermittency-mitigation) power discharge modes are possible. Smart meters and customer Demand Response (DR) management, along with some customer-owned storage will all be implemented. This program targets a minimum of 15% peak-load reduction at a specific feeder through a combination of these the devices and measures. In this paper, we present goals, future plans and current results of modeling for the existing and future infrastructure of this Smart Grid project.
ieee pes innovative smart grid technologies conference | 2012
Shahin Abdollahy; Olga Lavrova; Andrea Mammoli; Steve Willard; Brian Arellano
Distribution level modeling or monitoring has not been of primary concerns of the utility companies so far, because traditionally the electric power is delivered unidirectional from distribution substations to the customers. Meanwhile, integrating Distributed Energy Resources (DER) into the distribution feeders and contribution of the customers in demand response and other aspects of the future smart grid is starting to push system planners, utility companies and researchers to build unabridged and detailed model of the distribution feeders even down to home appliances level. GridLAB-D™ and Open-DSS are both open source software tools, designed for modeling distribution level power systems. Design and development of multiple algorithms for peak shaving, arbitrage, load shifting and smoothing scenarios is of major concerns. We show that very promising results in terms of modeling future smart grid and various possibilities are expected.
Archive | 2012
Abraham Ellis; Brian Arellano; Steve Willard; Jon Hawkins; David A. Schoenwald
This paper describes a simple algorithm designed to reduce the variability of photovoltaic (PV) power output by using an energy storage device. A full-scale implementation was deployed in an actual PV Energy demonstration project, in partnership with a utility and a battery manufacturer. The paper describes simulation tests as well as field results. In addition to demonstrating implementation of smoothing controls, this work also served to verify the models, identify best parameter sets for utility operations, and study the operation of an advanced energy storage system under partial state of charge and rapid, irregular charge/discharge cycling.
ieee/pes transmission and distribution conference and exposition | 2014
J. Hawkins; Steve Willard; Brian Arellano; Andrea Mammoli; John Simmins
A dispatchable, renewable resource of combined storage and utility sized PV has been commissioned as part of Public Service of New Mexicos Smart Grid Demonstration Project. The project consists of two banks of batteries, one for voltage smoothing and the other for peak shifting and relies on unique algorithms and communication infrastructure. This paper describes the experiment, the algorithms used, and the communications infrastructure.
ieee energytech | 2012
Feng Cheng; Steve Willard; J. Hawkins; Brian Arellano; Olga Lavrova; Andrea Mammoli
ieee conference on technologies for sustainability | 2013
Andrea Mammoli; Anthony Robert Menicucci; Thomas P. Caudell; Abraham Ellis; Steve Willard; John Simmins
Archive | 2014
Andrea Mammoli; Olga Lavrova; Brian Arellano; Feng Cheng; Wesley Greenwood; J. Hawkins; Steve Willard
ieee energytech | 2013
Feng Cheng; W. Greenwood; Brian Arellano; J. Hawkins; Olga Lavrova; Andrea Mammoli; Steve Willard
Archive | 2016
Andrea Mammoli; Bhuwanbabu Bastola; Steve Willard; Dean Weng; Arindam Maitra; Salman Mashayekh; Pablo Fontela Martinez