The Effects of Electricity Tariff Structure on DistributedGeneration Adoption in New York State

Firestone, Ryan; Marnay, Chris

doi:10.2172/860232

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…A recent addition to the literature (Firestone and Marnay, 2005) confirms the important impact of standby rates in six New York utility service areas.…”

Section: Introductionmentioning

confidence: 80%

Are US utility standby rates inhibiting diffusion of customer-owned generating systems?

Jackson

2007

Energy Policy

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“…A recent addition to the literature (Firestone and Marnay, 2005) confirms the important impact of standby rates in six New York utility service areas.…”

Section: Introductionmentioning

confidence: 80%

Are US utility standby rates inhibiting diffusion of customer-owned generating systems?

Jackson

2007

Energy Policy

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“…This is the case with many customers who produce some electricity on-site and purchase some from the grid. This issue is discussed in greater detail by Firestone, Marnay, and Maribu (2006) and Firestone and Marnay (2005b).…”

Section: Electricitymentioning

confidence: 98%

Optimal Real-time Dispatch for Integrated Energy Systems

Firestone

2007

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This report describes the development and application of a dispatch optimization algorithm for integrated energy systems (IES) comprised of on-site cogeneration of heat and electricity, energy storage devices, and demand response opportunities. This work is intended to aid commercial and industrial sites in making use of modern computing power and optimization algorithms to make informed, nearoptimal decisions under significant uncertainty and complex objective functions. The optimization algorithm uses a finite set of randomly generated future scenarios to approximate the true, stochastic future; constraints are included that prevent solutions to this approximate problem from deviating from solutions to the actual problem. The algorithm is then expressed as a mixed integer linear program, to which a powerful commercial solver is applied. A case study of United States Postal Service Processing and Distribution Centers (P&DC) in four cities and under three different electricity tariff structures is conducted to 1) determine the added value of optimal control to a cogeneration system over current, heuristic control strategies; 2) determine the value of limited My doctoral experience was made meaningful, enjoyable, and possible with the help and support of many, many people. It is with great pleasure that I have an opportunity to acknowledge some of them. I would like to start by thanking my parents, Marc and Carole Firestone, who raised me to take education seriously, be curious, and pursue what interests me. I would further like to thank my father for keeping tabs on my research and offering his empathy during my times of frustration. Many other relatives have also provided encouragement throughout. Thanks to my grandparents Sam and Bertha Farber and Leon and Nancy Firestone-I wish I could have finished a little sooner so that you could enjoy this more. Thanks also to my sister Lisa, my cousins, and my aunts and uncles who have encouraged me and challenged me to explain my work in simple terms. Many faculty members at U.C. Berkeley have given generously of their time and energy. I would like to thank the following professors for there assistance: • Alice Agogino, Mechanical Engineering-qualifying exam committee member. Alice and her research group were very kind in critiquing a trial run of my exam presentation. • Dave Auslander, Mechanical Engineering-dissertation committee chair. • Van Carey, Mechanical Engineering-qualifying exam committee member.

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“…Commodity prices have a number of characteristics that make them different from stock prices. Stock prices have been modeled successfully using random walk models, such as geometric Brownian motion, which is the underlying process assumed in the commonly used Black-Scholes model for pricing stock options (Dixit and Pindyck, 1994). Commodity prices, however, often exhibit a mean-reverting effect in the price, i.e.…”

Section: Energy Wholesale Price Processesmentioning

confidence: 99%

“…where κ Y is the mean-reversion parameter, -Y is the logarithm of the long-term average natural gas price, σ Y is electricity price volatility and DW Y = ε Yt √ -Dt is an increment of a Wiener process, and ε Yt ~ N(0,1). The variance of the logarithm of the electricity price is given as (Dixit and Pindyck, 1994)…”

Section: Energy Wholesale Price Processesmentioning

confidence: 99%

“…Now we have two correlated price processes for the electricity and the natural gas prices. A simple approach outlined in Dixit and Pindyck (1994) is followed to estimate the price process parameters. First, the seasonal parameters, k Sk , and, k Gk , are found as the average monthly deviation from the annual average price.…”

Section: Energy Wholesale Price Processesmentioning

confidence: 99%

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Combined Heat and Power in Commercial Buildings: Investment and Risk Analysis

Maribu¹,

Fleten²

2008

The Energy Journal

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Combined heat and power (CHP) systems can generate electricity locally while they recover heat to satisfy heating loads in buildings, which means they provide efficient energy. On-site generators may reduce both the expected energy costs and cost risk exposure for developers. With volatile energy prices, a deterministic modeling framework will not yield a fair value of CHP systems because flexibility in the operational response to price changes is not taken into account. In this paper, we present a Monte Carlo simulation model that is used to find the CHP value under uncertain future wholesale electricity and natural gas prices. When considering investing in a CHP system on should consider both return and risk. Clearly, both investment return and risk depend on local energy tariffs and energy loads. We highlight an example where CHP is marginally profitable and the investment decision is not straightforward. Interestingly, CHP systems were found particularly attractive with volatile electricity prices because their ability to respond to high prices provides efficient hedges to energy cost risk. Therefore, developers should not be discouraged but rather embrace onsite generation in markets with volatile prices. From the analysis, it can also be concluded that sizing of CHP systems can be related to the energy tariff structure and cost risk preferences as well as to energy loads.

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The Effects of Electricity Tariff Structure on DistributedGeneration Adoption in New York State

Abstract: PrefaceNew ideas must not only prove their merit but also make a place for themselves within traditional systems. Distributed generation has become a player within the centralized power paradigm.

Cited by 4 publications

References 4 publications

Are US utility standby rates inhibiting diffusion of customer-owned generating systems?

Are US utility standby rates inhibiting diffusion of customer-owned generating systems?

Optimal Real-time Dispatch for Integrated Energy Systems

Combined Heat and Power in Commercial Buildings: Investment and Risk Analysis

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