Information batteries

2021 ◽  
Vol 1 (1) ◽  
pp. 1-11
Author(s):  
Jennifer Switzer ◽  
Barath Raghavan
Keyword(s):  
Distributed Systems ◽  
Storage System ◽  
Macro Level ◽  
Power Prediction ◽  
Load Shifting ◽  
Systems Perspective ◽  
Renewable Power ◽  
Fundamental Challenge ◽  
The Future

Coping with the intermittency of renewable power is a fundamental challenge, with load shifting and grid-scale storage as key responses. We propose Information Batteries (IB), in which energy is stored in the form of information---specifically, the results of completed computational tasks. Information Batteries thus provide storage through speculative load shifting, anticipating computation that will be performed in the future. We take a distributed systems perspective, and evaluate the extent to which an IB storage system can be made practical through augmentation of compiler toolchains, key-value stores, and other important elements in modern hyper-scale compute. In particular, we implement one specific IB prototype by augmenting the Rust compiler to enable transparent function-level precomputation and caching. We evaluate the overheads this imposes, along with macro-level job prediction and power prediction. We also evaluate the space of operation for an IB system, to identify the best case efficiency of any IB system for a given power and compute regime.

scholarly journals Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration

2021 ◽  
Vol 13 (5) ◽  
pp. 2526
Author(s):  
Fahad Alismail ◽  
Mohamed A. Abdulgalil ◽  
Muhammad Khalid
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Integration ◽  
Planning Strategy ◽  
Demand Growth ◽  
Wind Power Integration ◽  
Renewable Power ◽  
Tie Lines

Since renewable power is intermittent and uncertain, modern grid systems need to be more elegant to provide a reliable, affordable, and sustainable power supply. This paper introduces a robust optimal planning strategy to find the location and the size of an energy storage system (ESS) and feeders. It aims to accommodate the wind power energy integration to serve the future demand growth under uncertainties. The methodology was tested in the IEEE RTS-96 system and the simulation results demonstrate the effectiveness of the proposed optimal sizing strategy. The findings validate the improvements in the power system reliability and flexibility.

Stakeholder Model of Change

2021 ◽  
pp. 249-274
Author(s):  
Laurie Lewis
Keyword(s):  
Organizational Change ◽  
Critical Theory ◽  
Organization Development ◽  
Macro Level ◽  
Change Strategies ◽  
Competing Interests ◽  
The Future ◽  
Challenges And Opportunities ◽  
Phenomenological Perspective ◽  
Stakeholder Model

This chapter explores the various ways in which opposing and/or contradictory entities unfold and play out with regard to change in organizations. This is undertaken from two different viewpoints. First, from a micro-phenomenological perspective it examines how insights derived from critical theory and other critical traditions have influenced the development of change strategies, interventions, and techniques. Second, at a more macro-level, it explores the extent to which particular schools of thought with regard to organizational change and organization development (OD) have embraced and/or resisted, the inevitable and unavoidable critical challenges and opportunities presented by opposing agents, competing interests, conflicting entities, and contrasting meanings in organizations. The chapter concludes by discussing the scope for, and possible directions of, critical change scholarship and practice in the future.

scholarly journals Alan Betts: Green Energy Times, 2018

2019 ◽  
Author(s):  
Alan Betts
Keyword(s):  
Climate Change ◽  
Energy Policy ◽  
Climate Science ◽  
Green Energy ◽  
Collective Decision ◽  
The Public ◽  
Systems Perspective ◽  
Climate Change Denial ◽  
The Earth ◽  
The Future

This is a collection of my 2018 articles in the Green Energy Times (http://www.greenenergytimes.org/ ).This series started in 2016. Many of these articles have been edited or updated from articles I wrote forthe Rutland Herald, sometimes with different titles and pictures.They blend science and opinion with a systems perspective, and encourage the reader to explorealternative and hopeful paths for their families and society. They are written so that a scientist willperceive them as accurate (although simplified); while the public can relate their tangible experience ofweather and climate to the much less tangible issues of climate change, energy policy and strategies forliving sustainably with the earth system.The politically motivated attacks on climate science by the current president have sharpened my politicalcommentary this year; since climate change denial may bring immense suffering to our children and lifeon Earth.I believe that earth scientists have a responsibility to communicate clearly and directly to the public1 –aswe all share responsibility for the future of the Earth. We must deepen our collective understanding, sowe can make a collective decision to build a resilient future.

scholarly journals Alternative Futures for the Digital Transformation: A Macro-Level Schumpeterian Perspective

2021 ◽  
Author(s):  
Zlatko Bodrožić ◽  
Paul S. Adler
Keyword(s):  
Public Policy ◽  
Digital Transformation ◽  
Macro Level ◽  
Alternative Futures ◽  
Considerable Uncertainty ◽  
The Future ◽  
Information And Communication ◽  
Critical Problems ◽  
Alternative Solutions ◽  
New Phase

This paper develops and deploys a theoretical framework for assessing the prospects of a cluster of technologies driving what is often called the digital transformation. There is considerable uncertainty regarding this transformation’s future trajectory, and to understand and bound that uncertainty, we build on Schumpeter’s macro-level theory of economy-wide, technological revolutions and on the work of several scholars who have extended that theory. In this perspective, such revolutions’ trajectories are shaped primarily by the interaction of changes within and between three spheres—technology, organization, and public policy. We enrich this account by identifying the critical problems and the collective choices among competing solutions to those problems that together shape the trajectory of each revolution. We argue that the digital transformation represents a new phase in the wider arc of the information and communication technology revolution—a phase promising much wider deployment—and that the trajectory of this deployment depends on collective choices to be made in the organization and public policy spheres. Combining in a 2 × 2 matrix the two main alternative solutions on offer in each of these two spheres, we identify four scenarios for the future trajectory of the digital transformation: digital authoritarianism, digital oligarchy, digital localism, and digital democracy. We discuss how these scenarios can help us trace and understand the future trajectory of the digital transformation.

scholarly journals Performance Analysis of a Stand-Alone PV/WT/Biomass/Bat System in Alrashda Village in Egypt

2021 ◽  
Vol 11 (21) ◽  
pp. 10191
Author(s):  
Hoda Abd El-Sattar ◽  
Salah Kamel ◽  
Hamdy Sultan ◽  
Marcos Tostado-Véliz ◽  
Ali M. Eltamaly ◽  
...  
Keyword(s):  
Hybrid System ◽  
Storage System ◽  
Optimal Solution ◽  
Grey Wolf Optimizer ◽  
Storage Unit ◽  
Renewable Power ◽  
First Case ◽  
Cost Of Energy ◽  
Battery Bank ◽  
Sooty Tern

This paper presents an analysis and optimization of an isolated hybrid renewable power system to operate in the Alrashda village in the Dakhla Oasis, which is situated in the New Valley Governorate in Egypt. The proposed hybrid system is designed to integrate a biomass system with a photovoltaic (PV), wind turbine (WT) and battery storage system (Bat). Four different cases are proposed and compared for analyzing and optimizing. The first case is a configuration of PV and WT with a biomass system and battery bank. The second case is the integration of PV with a biomass system and battery bank. The third case is WT integrated with biomass and a battery bank, and the fourth case is a conventional PV, WT, and battery bank as the main storage unit. The optimization is designed to reduce component oversizing and ensure the dependable control of power supplies with the objective function of reducing the levelized cost of energy and loss of power supply probability. Four optimization algorithms, namely Heap-based optimizer (HBO), Franklin’s and Coulomb’s algorithm (CFA), the Sooty Tern Optimization Algorithm (STOA), and Grey Wolf Optimizer (GWO) are utilized and compared with each other to ensure that all load demand is met at the lowest energy cost (COE) for the proposed hybrid system. The obtained results revealed that the HBO has achieved the best optimal solution for the suggested hybrid system for case one and two, with the minimum COE 0.121171 and 0.1311804 $/kWh, respectively, and with net present cost () of $3,559,143 and $3,853,160, respectively. Conversely, STOA has achieved the best optimal solution for case three and four, with a COE of 0.105673 and 0.332497 $/kWh, and an NPC of $3,103,938 and $9,766,441, respectively.

V2CTX Catalyzes Polysulfide Conversion to Enhance Redox Kinetics of Li−S Batteries

2022 ◽  
Author(s):  
Fengfeng Han ◽  
Qi Jin ◽  
Junpeng Xiao ◽  
Lili Wu ◽  
Xitian Zhang
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Redox Kinetics ◽  
Lithium Sulfur Batteries ◽  
The Future ◽  
Kinetics Of ◽  
Lithium Sulfur

Lithium–sulfur batteries (LBSs) have potential to become the future energy storage system, yet they are plagued by the sluggish redox kinetics. Therefore, enhancing the redox kinetics of polysulfide is a...

scholarly journals Effect of Prediction Error of Machine Learning Schemes on Photovoltaic Power Trading Based on Energy Storage Systems

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1249 ◽  
Author(s):  
Kuk Bae ◽  
Han Jang ◽  
Bang Jung ◽  
Dan Sung
Keyword(s):  
Machine Learning ◽  
Energy Storage ◽  
Output Power ◽  
Storage System ◽  
Weather Conditions ◽  
Energy Storage System ◽  
Energy Markets ◽  
Prediction Errors ◽  
Power Prediction ◽  
Power Trading

Photovoltaic (PV) output power inherently exhibits an intermittent property depending on the variation of weather conditions. Since PV power producers may be charged to large penalties in forthcoming energy markets due to the uncertainty of PV power generation, they need a more accurate PV power prediction scheme in energy market operation. In this paper, we characterize the effect of PV power prediction errors on energy storage system (ESS)-based PV power trading in energy markets. First, we analyze the prediction accuracy of two machine learning (ML) schemes for the PV output power and estimate their error distributions. We propose an efficient ESS management scheme for charging and discharging operation of ESS in order to reduce the deviations between the day-ahead (DA) and real-time (RT) dispatch in energy markets. In addition, we estimate the capacity of ESSs, which can absorb the prediction errors and then compare the PV power producer’s profit according to ML-based prediction schemes with/without ESS. In case of ML-based prediction schemes with ESS, the ANN and SVM schemes yield a decrease in the deviation penalty by up to 87% and 74%, respectively, compared with the profit of those schemes without ESS.

scholarly journals Integrated Photorechargeable Energy Storage System: Next‐Generation Power Source Driving the Future

2020 ◽  
Vol 10 (14) ◽  
pp. 1903930 ◽  
Author(s):  
Qiang Zeng ◽  
Yanqing Lai ◽  
Liangxing Jiang ◽  
Fangyang Liu ◽  
Xiaojing Hao ◽  
...  
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Power Source ◽  
Next Generation ◽  
The Future ◽  
Generation Power
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