Dynamics and Control of Energy Systems–A Recent Perspective: Preface to the Special Issue on Energy System Modeling and Optimization Conference (ESMOC 2013)

2014 ◽  
Vol 53 (51) ◽  
pp. 19653-19653
Author(s):  
S. Pushpavanam ◽  
P. Gupta ◽  
Babatunde A. Ogunnaike
Keyword(s):  
System Modeling ◽  
Energy Systems ◽  
Energy System ◽  
Special Issue ◽  
Modeling And Optimization ◽  
Dynamics And Control ◽  
Energy System Modeling ◽  
And Control

scholarly journals Special Issue on Standalone Renewable Energy System: Modeling and Controlling

2020 ◽  
Vol 10 (6) ◽  
pp. 2068
Author(s):  
Rodolfo Dufo-López ◽  
José L. Bernal-Agustín
Keyword(s):  
Renewable Energy ◽  
System Modeling ◽  
Energy Systems ◽  
Energy System ◽  
Special Issue ◽  
Renewable Energy Systems ◽  
Electrical Grid ◽  
Renewable Energy System ◽  
Energy System Modeling

Standalone (off-grid) renewable energy systems supply electricity in places where there is no access to a standard electrical grid [...]

scholarly journals Semi-Markov and hidden semi-Markov models of energy systems

2018 ◽  
Vol 58 ◽  
pp. 02023 ◽  
Author(s):  
Yuriy E. Obzherin
Keyword(s):  
Control Systems ◽  
Intelligent Control ◽  
Markov Models ◽  
System Modeling ◽  
Energy Systems ◽  
Energy System ◽  
Information Control ◽  
Efficiency Theory ◽  
Energy System Modeling ◽  
Semi Markov Processes

The problem of information control systems creation for energy systems and transition to intelligent control and engineering is one of the important problems of reliability and efficiency theory for energy systems. The solution of this problem is possible based on construction of mathematical models concerning different aspects of these systems structure and operation. The possibilities of application of semi-Markov processes with common phase space of states, hidden Markov and semi-Markov models for energy system modeling are considered in the paper.

scholarly journals Understanding Technology, Fuel, Market and Policy Drivers for New York State’s Power Sector Transformation

2020 ◽  
Vol 13 (1) ◽  
pp. 265
Author(s):  
Mine Isik ◽  
P. Ozge Kaplan
Keyword(s):  
New York ◽  
Electricity Generation ◽  
System Modeling ◽  
New York State ◽  
Clean Energy ◽  
Energy System ◽  
Offshore Wind ◽  
Power Sector ◽  
Reduce Emissions ◽  
Energy System Modeling

A thorough understanding of the drivers that affect the emission levels from electricity generation, support sound design and the implementation of further emission reduction goals are presented here. For instance, New York State has already committed a transition to 100% clean energy by 2040. This paper identifies the relationships among driving factors and the changes in emissions levels between 1990 and 2050 using the logarithmic mean divisia index analysis. The analysis relies on historical data and outputs from techno-economic-energy system modeling to elucidate future power sector pathways. Three scenarios, including a business-as-usual scenario and two policy scenarios, explore the changes in utility structure, efficiency, fuel type, generation, and emission factors, considering the non-fossil-based technology options and air regulations. We present retrospective and prospective analysis of carbon dioxide, sulfur dioxide, nitrogen oxide emissions for the New York State’s power sector. Based on our findings, although the intensity varies by period and emission type, in aggregate, fossil fuel mix change can be defined as the main contributor to reduce emissions. Electricity generation level variations and technical efficiency have relatively smaller impacts. We also observe that increased emissions due to nuclear phase-out will be avoided by the onshore and offshore wind with a lower fraction met by solar until 2050.

scholarly journals Time series of heat demand and heat pump efficiency for energy system modeling

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Oliver Ruhnau ◽  
Lion Hirth ◽  
Aaron Praktiknjo
Keyword(s):  
Time Series ◽  
System Modeling ◽  
Energy System ◽  
Heat Pumps ◽  
Reanalysis Data ◽  
Coefficient Of Performance ◽  
Pump Efficiency ◽  
Water Heating ◽  
Heat Demand ◽  
Energy System Modeling

Abstract With electric heat pumps substituting for fossil-fueled alternatives, the temporal variability of their power consumption becomes increasingly important to the electricity system. To easily include this variability in energy system analyses, this paper introduces the “When2Heat” dataset comprising synthetic national time series of both the heat demand and the coefficient of performance (COP) of heat pumps. It covers 16 European countries, includes the years 2008 to 2018, and features an hourly resolution. Demand profiles for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data as well as population geodata. COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating, radiators, and water heating – are calculated based on COP and heating curves using reanalysis temperature data. The dataset, as well as the scripts and input parameters, are publicly available under an open source license on the Open Power System Data platform.

scholarly journals Beyond the Energy System: Modeling Frameworks Depicting Distributional Impacts for Interdisciplinary Policy Analysis

2020 ◽  
Vol 9 (1) ◽  
pp. 2000668
Author(s):  
Roland Cunha Montenegro ◽  
Panagiotis Fragkos ◽  
Audrey Helen Dobbins ◽  
Dorothea Schmid ◽  
Steve Pye ◽  
...  
Keyword(s):  
Policy Analysis ◽  
System Modeling ◽  
Energy System ◽  
Energy System Modeling ◽  
Distributional Impacts

scholarly journals Decarbonizing China’s energy system – Modeling the transformation of the electricity, transportation, heat, and industrial sectors

2019 ◽  
Vol 255 ◽  
pp. 113820 ◽  
Author(s):  
Thorsten Burandt ◽  
Bobby Xiong ◽  
Konstantin Löffler ◽  
Pao-Yu Oei
Keyword(s):  
System Modeling ◽  
Energy System ◽  
Industrial Sectors ◽  
Energy System Modeling
Sign in / Sign up

Export Citation Format

Share Document