The United States of storage [electric energy storage

2005 ◽  
Vol 3 (2) ◽  
pp. 31-39 ◽  
Author(s):  
I. Gyuk ◽  
P. Kulkarni ◽  
J.H. Sayer ◽  
J.D. Boyes ◽  
G.P. Corey ◽  
...  
Keyword(s):  
United States ◽  
Energy Storage ◽  
Electric Energy ◽  
The United States ◽  
Electric Energy Storage

Performance Analysis of Solar-Powered Organic Rankine Cycle With Energy Storage in Different Climate Zones in the United States

2021 ◽  
Vol 143 (9) ◽  
Author(s):  
Hadis Hemmati ◽  
Jian Zhang ◽  
Emily Spayde ◽  
Pedro J. Mago ◽  
Heejin Cho
Keyword(s):  
United States ◽  
Energy Consumption ◽  
Energy Storage ◽  
Electric Energy ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
The United States ◽  
Solar Irradiation ◽  
Climate Zones ◽  
Solar Powered

Abstract Solar-powered organic Rankine cycle (ORC) is considered a promising technology and has the potential to provide clean electric energy. Extensive studies on the design of ORC systems have been conducted and reported in the literature. However, few studies have presented the influence of climate zones on the performance of a solar-powered ORC, especially for an integrated ORC and energy storage system. This paper presents an analysis to determine the performance of solar-powered ORCs with electric energy storage (EES) systems to supply electricity to buildings in different climate zones in the United States. The building type evaluated in this paper is a large office, and the energy consumption of the facility in each climate location was determined using EnergyPlus. The ORC-EES operational strategy used in this investigation is described as follows: when solar irradiation is adequate to produce power, the ORC charges the EES. Then, when there is no solar energy available, the EES provides power to the building. The ORC-EES is evaluated based on the potential to reduce the operational cost, the primary energy consumption, and the carbon dioxide emission. Furthermore, the influence of the number of solar collectors and the EES size on the performance of the ORC-EES system is investigated.

scholarly journals Locomotive operation mode - the basis for developing the requirements for the energy storage device on railway transport

2018 ◽  
Vol 239 ◽  
pp. 01004
Author(s):  
Andrey Shatokhin ◽  
Alexandr Galkin
Keyword(s):  
Energy Storage ◽  
Direct Current ◽  
Electric Energy ◽  
Rolling Stock ◽  
Storage Device ◽  
Contact Network ◽  
Energy Storage Device ◽  
Electric Energy Storage ◽  
Operation Modes ◽  
Electric Rolling Stock

Increasing the efficiency of cargo transportation by rail is not only one of the main directions of the company JSC “Russian Railways” but also one of the main tasks of our country in order to achieve sustainable economic growth. Electric rolling stock is the largest consumer of electric energy in the company, that’s why its effective and failure-free operation is the way to solve the set tasks. The paper deals with studies related to the operation modes of a freight electric rolling stock of direct current for the purpose of determining the requirements for electric energy storage device, since it is the electric rolling stock that determines the daily schedule of electric load. The order of the analysis of experimental trips of freight electric locomotives of a direct current on the basis of cartridges of recorders of traffic parameters installed on the locomotive is determined. On the basis of the analysis of conducted trips, the main requirements for the energy storage device were obtained with a single running of electric DC rolling stock, namely the average duration of the operation modes of the electric locomotive, the maximum, minimum, and average values of voltage and current, the average value of the electric energy returned to the contact network, time of charge/discharge, and the useful energy intensity of the electric energy storage device. The studies were carried out with the support of the Russian Foundation for Basic Research for the project No 17-20-01148 ofi_m_RZD/17.

Economics of Electric Energy Storage Systems

2017 ◽  
pp. 181-194
Author(s):  
Przemyslaw Komarnicki ◽  
Pio Lombardi ◽  
Zbigniew Styczynski
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Electric Energy ◽  
Energy Storage Systems ◽  
Electric Energy Storage

Combining electric energy storage and deep-lake degassing by means of pumped hydropower

2021 ◽  
Vol 304 ◽  
pp. 117839
Author(s):  
Urbain Nzotcha ◽  
Jean Calvin Nsangou ◽  
Joseph Kenfack ◽  
Paul Salomon Ngohe-Ekam ◽  
Oumarou Hamandjoda ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Energy ◽  
Deep Lake ◽  
Electric Energy Storage

Baseload power potential from optimally-configured wind, solar and storage power plants across the United States

2020 ◽  
Author(s):  
Joshua D Rhodes ◽  
Aditya Choukulkar ◽  
Brianna Cote ◽  
Sarah A McKee ◽  
Christopher T M Clack
Keyword(s):  
United States ◽  
Energy Storage ◽  
Power Plants ◽  
Cost Optimization ◽  
The United States ◽  
Solar Pv ◽  
Wholesale Market ◽  
Optimal Technology ◽  
Current Price ◽  
The Cost

Abstract In the present paper, we assessed the potential for local wind, solar PV, and energy storage to provide baseload (constant, uninterrupted) power in every county of the contiguous United States. The amount of available capacity between 2020 and 2050 was determined via a least-cost optimization model that took into account changing costs of constituent technologies and local meteorological conditions. We found that, by 2050, the potential exists for about 6.8 TW of renewable baseload power at an average cost of approximately $50 / MWh, which is competitive with current wholesale market rates for electricity. The optimal technology configurations constructed always resulted in over two hours of emergency energy reserves, with the amount increasing as the price of energy storage falls. We also found that, given current price decline trajectories, the model has a tendency to select more solar capacity than wind over time. A second part of the study performed three million simulations followed by a regression analysis to generate an online map-based tool that allows users to change input costs assumptions and compute the cost of renewable baseload electricity in every contiguous US county.

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