Integrated Energy System Dispatch Optimization

Firestone, Ryan; Städler, Michael; Marnay, Chris

doi:10.1109/indin.2006.275826

Cited by 15 publications

(7 citation statements)

References 3 publications

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“…The constraints of the hydrogen tank are indicated by Equations (15)- (17). The change in the amount of hydrogen in the hydrogen storage tank is related to the speed and time of the charge and discharge gas, as shown in Equation (15).…”

Section: Hpes Mathematical Modellingmentioning

confidence: 99%

“…The change in the amount of hydrogen in the hydrogen storage tank is related to the speed and time of the charge and discharge gas, as shown in Equation (15). The hydrogen storage tank also has maximum capacity constraints and charge and discharge gas maximum speed constraints as shown in Equations (16) and (17). In the model described herein, the hydrogen storage tank charging rate is the same as the electrolyzer producing hydrogen gas velocity and is therefore not listed in the hydrogen storage tank constraint.…”

Section: Hpes Mathematical Modellingmentioning

confidence: 99%

“…The lower level model is transferred by Karush-Kuhn-Tucher (KKT) conditions and added to the upper-level model, which make the whole model as a mixed integer linear programing (MILP) formulation and can be solved by most of the commercial optimization software packages. Other mathematical-driven approaches for optimizing the integrated energy system operation have been presented in [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network

Zhou

Zhang

et al. 2019

Sustainability

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Intra-day control and scheduling of energy systems require high-speed computation and strong robustness. Conventional mathematical driven approaches usually require high computation resources and have difficulty handling system uncertainties. This paper proposes two data-driven scheduling approaches for hydrogen penetrated energy system (HPES) operational scheduling. The two data-driven approaches learn the historical optimization results calculated out using the mixed integer linear programing (MILP) and conditional value at risk (CVaR), respectively. The intra-day rolling optimization mechanism is introduced to evaluate the proposed data-driven scheduling approaches, MILP data-driven approach and CVaR data-driven approach, along with the forecasted renewable generation and load demands. Results show that the two data-driven approaches have lower intra-day operational costs compared with the MILP based method by 1.17% and 0.93%. In addition, the combined cooling and heating plant (CCHP) has a lower frequency of changing the operational states and power output when using the MILP data-driven approach compared with the mathematical driven approaches.

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Section: Hpes Mathematical Modellingmentioning

confidence: 99%

Section: Hpes Mathematical Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network

Zhou

Zhang

et al. 2019

Sustainability

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“…Typically, on-site electricity production is most economic in parallel with utility electricity purchase. When the cost of produced electricity and heat on-site is less than the cost of purchased electricity and heating fuel separately, on-site generation is dispatched to run [3].…”

Section: Distributed Generation As An Option For Cost Optimizationmentioning

confidence: 99%

A method for cost minimization applicable to load centers containing distributed generation

Zeljković

Rajaković

Zubic

2009

2009 IEEE Bucharest PowerTech

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Distributed energy resources (DER), located close to end use loads, have the potential to meet consumer requirements more efficiently than the existing centralized grid. In this paper, a specific scenario is considered, where the consumer center uses distributed resources to meet a part of its energy requirements, while the rest of the needed electricity is purchased from the utility distribution company. In order to minimize total consumer costs, a robust optimization algorithm based on a search method has been developed. The main outputs of this algorithm are optimal dispatch between distributed resources generation and the electricity purchased from the utility as well as the particular contribution of every on-site generating unit in the dispatch schedule. The algorithm was tested using several characteristic simulations and two basic areas of its application have been discovered -optimal dispatching of existing distributed energy resources and economic evaluation concerning installation of new generating facilities.

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“…The format of curtailment in most of these studies is a few to 10 or 20 events per year, each event lasting three or four hours. While these structures and incentives are designed to directly or indirectly call upon DR when supplies are scarce, the standard demand charge that most commercial and industrial customers in the U.S. are subject to also incents some DR. One application of the research described in this dissertation has been a valuation of DR under standard demand charges (Firestone, Stadler, and Marnay 2006).…”

Section: Several Of the Tariffs And Incentive Programs Have Been Implmentioning

confidence: 99%

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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Integrated Energy System Dispatch Optimization

Cited by 15 publications

References 3 publications

A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network

A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network

A method for cost minimization applicable to load centers containing distributed generation

Optimal Real-time Dispatch for Integrated Energy Systems

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