scholarly journals A Review on Time Series Aggregation Methods for Energy System Models

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 641 ◽  
Author(s):  
Maximilian Hoffmann ◽  
Leander Kotzur ◽  
Detlef Stolten ◽  
Martin Robinius
Keyword(s):  
Time Series ◽  
Input Data ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy System ◽  
Machine Learning Techniques ◽  
Future Research ◽  
System Models ◽  
Number Of Publications ◽  
The Impact

Due to the high degree of intermittency of renewable energy sources (RES) and the growing interdependences amongst formerly separated energy pathways, the modeling of adequate energy systems is crucial to evaluate existing energy systems and to forecast viable future ones. However, this corresponds to the rising complexity of energy system models (ESMs) and often results in computationally intractable programs. To overcome this problem, time series aggregation (TSA) is frequently used to reduce ESM complexity. As these methods aim at the reduction of input data and preserving the main information about the time series, but are not based on mathematically equivalent transformations, the performance of each method depends on the justifiability of its assumptions. This review systematically categorizes the TSA methods applied in 130 different publications to highlight the underlying assumptions and to evaluate the impact of these on the respective case studies. Moreover, the review analyzes current trends in TSA and formulates subjects for future research. This analysis reveals that the future of TSA is clearly feature-based including clustering and other machine learning techniques which are capable of dealing with the growing amount of input data for ESMs. Further, a growing number of publications focus on bounding the TSA induced error of the ESM optimization result. Thus, this study can be used as both an introduction to the topic and for revealing remaining research gaps.

scholarly journals Big Data in Smart Energy Systems: A Critical Review

2020 ◽  
Vol 11 (41) ◽  
pp. 11-26
Author(s):  
Keziban Seçkin Codal ◽  
İzzet Arı ◽  
H. Kemal İlter
Keyword(s):  
Big Data ◽  
Critical Review ◽  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy System ◽  
Interdisciplinary Studies ◽  
Smart Energy Systems ◽  
The Impact

Climate change is an undeniable fact. Considering that two-thirds of greenhouse gas emissions originate from the energy sector, it is expected that the world's energy system will be transformed with renewable energy sources. Energy efficiency will be continuously increased. Reducing energy-related carbon dioxide emissions is the heart of the energy transition. Big data in energy systems play a crucial role in evaluating the adaptive capacity and investing more smartly to manage energy demand and supply. Indeed, the impact of the smart energy grid and meters on smart energy systems provide and assist decision-makers in transforming energy production, consumption, and communities. This study reviews the literature for aligning big data and smart energy systems and criticized according to regional perspective, period, disciplines, big data characteristics, and used data analytics. The critical review has been categorized into present themes. The results address issues, including scientific studies using data analysis techniques that take into account the characteristics of big data in the smart energy literature and the future of smart energy approaches. The manuscripts on big data in smart energy systems are a promising issue, albeit it is essential to expand subjects through comprehensive interdisciplinary studies

scholarly journals Techno-Economic Evaluation of Interconnected Nuclear-Renewable Micro Hybrid Energy Systems with Combined Heat and Power

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1642 ◽  
Author(s):  
Hossam A. Gabbar ◽  
Muhammad R. Abdussami ◽  
Md. Ibrahim Adham
Keyword(s):  
Fossil Fuel ◽  
Renewable Energy Sources ◽  
Ghg Emissions ◽  
Energy Systems ◽  
Energy System ◽  
Combined Heat And Power ◽  
Small Scale ◽  
Hybrid Energy ◽  
Hybrid Energy Systems ◽  
The Impact

Renewable energy sources (RESs) play an indispensable role in sustainable advancement by reducing greenhouse gas (GHG) emissions. Nevertheless, due to the shortcomings of RESs, an energy mix with RESs is required to support the baseload and to avoid the effects of RES variability. Fossil fuel-based thermal generators (FFTGs), like diesel generators, have been used with RESs to support the baseload. However, using FFTGs with RESs is not a good option to reduce GHG emissions. Hence, the small-scale nuclear power plant (NPPs), such as the micro-modular reactor (MMR), have become a modern alternative to FFTGs. In this paper, the authors have investigated five different hybrid energy systems (HES) with combined heat and power (CHP), named ‘conventional small-scale fossil fuel-based thermal energy system,’ ‘small-scale stand-alone RESs-based energy system,’ ‘conventional small-scale fossil fuel-based thermal and RESs-based HES,’ ‘small-scale stand-alone nuclear energy system,’ and ‘nuclear-renewable micro hybrid energy system (N-R MHES),’ respectively, in terms of net present cost (NPC), cost of energy (COE), and GHG emissions. A sensitivity analysis was also conducted to identify the impact of the different variables on the systems. The results reveal that the N-R MHES could be the most suitable scheme for decarbonization and sustainable energy solutions.

Assessment of soft and hard linking approaches of integrated water-energy simulation

2020 ◽  
Author(s):  
Mikiyas Etichia ◽  
Eduardo Alejandro Martinez ◽  
Julien Harou ◽  
Mathaios Panteli
Keyword(s):  
Renewable Energy Sources ◽  
Computational Cost ◽  
Energy Systems ◽  
Energy System ◽  
Domestic Water ◽  
Sustainable Solutions ◽  
System Models ◽  
Advantages And Disadvantages ◽  
Operation Rules ◽  
Trade Offs

<p>The strong synergies between water and energy use are becoming increasingly evident nowadays. It is becoming more and more apparent that significant benefits can be gained if both resources are managed in an integrated manner, which can be critical to improve efficiencies, reduce trade-offs, and find better and more sustainable solutions to future energy and water resources scarcity problems. Two types of approaches have drawn attention to integrate water and power system models, namely soft-link and hard-link approaches. Soft-linking approaches involve iterations, wherein the two system models are simulated independently, and their outputs (e.g., water available for hydropower generation) are passed to the other model until convergence is reached. In hard-link approaches, both the water and power systems are simulated with a single optimization model. More research to understand better the implications of different water-energy linking approaches, their computational cost, flexibility, and scalability are critically needed.</p><p>In this work water and energy system network models are linked with varying levels of integration (i.e., gradually moving from soft to hard link approaches) to demonstrate the advantages and disadvantages of the different types of links. The water and energy model includes multi-purpose storage reservoirs, irrigation, and domestic water users, renewable energy sources, and conventional power generators. Results show that soft linking approaches are more suitable for water-energy systems with fixed reservoir operation rules. Hard linking approaches are proven to be more suitable for cases with well established water and energy markets and can be computationally cheaper than soft linking approaches. Better joint simulation will help investigate better ways to manage and invest in water-energy systems.</p>

Reducing energy time series for energy system models via self-organizing maps

2019 ◽  
Vol 61 (2-3) ◽  
pp. 125-133
Author(s):  
Hasan Ümitcan Yilmaz ◽  
Edouard Fouché ◽  
Thomas Dengiz ◽  
Lucas Krauß ◽  
Dogan Keles ◽  
...  
Keyword(s):  
Time Series ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Model Complexity ◽  
Electricity Production ◽  
Self Organizing Maps ◽  
System Models ◽  
Execution Times ◽  
New Research ◽  
Self Organizing

Abstract The recent development of renewable energy sources (RES) challenges energy systems and opens many new research questions. Energy System Models (ESM) are important tools to study these problems. However, including RES into ESM strongly increases the model complexity, because one needs to model the fluctuant, weather-dependent electricity production from RES with a high level of granularity. This leads to long execution times. To deal with this issue, our objective is to reduce the input time series of ESM without losing their energy-related key characteristics, such as weather-dependent fluctuations in production or peak demands. This task is challenging, because of the variety and high-dimensionality of the data. We describe a carefully engineered data-processing pipeline to reduce energy time series. We use Self-Organizing Maps, a specific kind of neural network, to select “representative days”. We show that our approach outperforms the existing ones with respect to the quality of ESM results, and leads to a significant reduction of ESM execution times.

scholarly journals Integrating Behavioural Aspects in Energy System Modelling—A Review

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4579
Author(s):  
David Huckebrink ◽  
Valentin Bertsch
Keyword(s):  
Technology Acceptance ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy System ◽  
System Modelling ◽  
Economic Dimension ◽  
System Models ◽  
The Many ◽  
Sustainable Energy System ◽  
Behavioural Aspects

Many countries worldwide have adopted policies to support the expansion of renewable energy sources aimed at reducing greenhouse gas emissions, combating climate change, and, more generally, establishing a globally sustainable energy system. As a result, energy systems around the world are undergoing a process of fundamental change and transformation that goes far beyond the technological dimension. While energy system models have been developed and used for several decades to support decision makers in governments and companies, these models usually focus on the techno-economic dimension, whereas they fall short in addressing and considering behavioural and societal aspects of decisions related to technology acceptance, adoption, and use. In fact, it is often the societal dimension that comes with the greatest challenges and barriers when it comes to making such a socio-technical transformation happen in reality. This paper therefore provides an overview of state-of-the-art energy system models on the one hand and research studying behavioural aspects in the energy sector on the other hand. We find that these are two well-developed fields of research but that they have not yet been integrated sufficiently well to provide answers to the many questions arising in the context of complex socio-technical transformation processes of energy systems. While some promising approaches integrating these two fields can be identified, the total number is very limited. Based on our findings, research gaps and potentials for improvement of both energy system models and behavioural studies are derived. We conclude that a stronger collaboration across disciplines is required.

scholarly journals Balancing the Slovak Energy Market After the Adoption of “Fit for 55 Package”

2021 ◽  
Vol 129 ◽  
pp. 05015
Author(s):  
Stanislav Zabojnik ◽  
Marius Hricovsky
Keyword(s):  
Fossil Fuels ◽  
Slovak Republic ◽  
Renewable Energy Sources ◽  
Balance Sheet ◽  
Value Added ◽  
Energy Systems ◽  
Energy System ◽  
Energy Market ◽  
Transportation Fuels ◽  
The Impact

Research background: Slovak energy sector is based on older strategic documents setting national interests within energy policy and energy security (before 2014). “Fit for 55 package” proposed by European Commission in July 2021 is one of the most politically ambitious projects after WW2 and brings crucial changes for EU27 energy systems, especially for CEE countries. Purpose of the article: To analyze the potential impact of the “Fit for 55 package” objectives and consequences on the energy system of the Slovak Republic in terms of fossil fuels substitutes. Methods: Authors use Energy Balance Sheet (EBS) to outline the unprecedented impact of the EU policy on the Slovak energy system and alternative scenarios for its development. Simulating the impact of CO2 emissions cuts via Gretl software, the authors outline crucial changes in the energy system and subsequent energy shortages within the Slovak energy market, which have to be replaced (in electricity generation, natural gas, and transportation fuels). Findings & Value added: According to the authors´ findings, possible substitutes (hydrogen or renewable energy sources) will not fully cover the future demand, and authors suggest possible solutions. Secondly, the impact on transportation capacities and energy transportation corridors are outlined. Finally, the authors stress that political efforts oversize economic and energy reality, especially in Slovakia, and policymakers should better consider the specifics of the CEE energy systems and allocate financial grants for the upgrade of transport corridors

scholarly journals On the Role of Electric Vehicles towards Low-Carbon Energy Systems: Italy and Germany in Comparison

2019 ◽  
Author(s):  
Sara Bellocchi ◽  
Kai Klöckner ◽  
Michele Manno ◽  
Michel Noussan ◽  
Michela Vellini
Keyword(s):  
Co2 Emissions ◽  
Electric Vehicles ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy System ◽  
Low Carbon ◽  
Smart Charging ◽  
Low Carbon Energy ◽  
The Impact

Electric vehicles, being able to reduce pollutant and greenhouse gas emissions and shift the economy away from oil products, can play a major role in the transition towards low-carbon energy systems. However, the related increase in electricity demand inevitably affects the strategic planning of the overall energy system as well as the definition of the optimal power generation mix. With this respect, the impact of electric vehicles may vary significantly depending on the composition of both total primary energy supply and electricity generation. In this study, Italy and Germany are compared to highlight how a similarity in their renewable shares not necessarily leads to a CO2 emissions reduction. Different energy scenarios are simulated with the help of EnergyPLAN software assuming a progressive increase in renewable energy sources capacity and electric vehicles penetration. Results show that, for the German case, the additional electricity required leads to a reduction in CO2 emissions only if renewable capacity increases significantly, whereas the Italian energy system benefits from transport electrification even at low renewable capacity. Smart charging strategies are also found to foster renewable integration; however, power curtailments are still significant at high renewable capacity in the absence of large-scale energy storage systems.

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals The Impact of Temporal Complexity Reduction on a 100% Renewable European Energy System with Hydrogen Infrastructure

2019 ◽  
Author(s):  
Dilara Gulcin Caglayan ◽  
Heidi Ursula Heinrichs ◽  
Detlef Stolten ◽  
Martin Robinius
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Alternative Energy ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Promising Alternative ◽  
Renewable Energy System ◽  
Hydrogen Infrastructure ◽  
Storage Technologies ◽  
The Impact

The transition towards a renewable energy system is essential in order to reduce greenhouse gas emissions. The increase in the share of variable renewable energy sources (VRES), which mainly comprise wind and solar energy, necessitates storage technologies by which the intermittency of VRES can be compensated for. Although hydrogen has been envisioned to play a significant role as a promising alternative energy carrier in a future European VRES-based energy concept, the optimal design of this system remains uncertain. In this analysis, a hydrogen infrastructure is posited that would meet the electricity and hydrogen demand for a 100% renewable energy-based European energy system in the context of 2050. The overall system design is optimized by minimizing the total annual cost. Onshore and offshore wind energy, open-field photovoltaics (PV), rooftop PV and hydro energy, as well as biomass, are the technologies employed for electricity generation. The electricity generated is then either transmitted through the electrical grid or converted into hydrogen by means of electrolyzers and then distributed through hydrogen pipelines. Battery, hydrogen vessels and salt caverns are considered as potential storage technologies. In the case of a lull, stored hydrogen can be re-electrified to generate electricity to meet demand during that time period. For each location, eligible technologies are introduced, as well as their maximum capacity and hourly demand profiles, in order to build the optimization model. In addition, a generation time series for VRES has been exogenously derived for the model. The generation profiles of wind energy have been investigated in detail by considering future turbine designs with high spatial resolution. In terms of salt cavern storage, the technical potential for hydrogen storage is defined in the system as the maximum allowable capacity per region. Whether or not a technology is installed in a region, the hourly operation of these technologies, as well as the cost of each technology, are obtained within the optimization results. It is revealed that a 100 percent renewable energy system is feasible and would meet both electricity demand and hydrogen demand in Europe.

scholarly journals Role of the national energy system modelling in the process of the policy development

2012 ◽  
Vol 16 (3) ◽  
pp. 703-715 ◽  
Author(s):  
Matevz Pusnik ◽  
Boris Sucic ◽  
Andreja Urbancic ◽  
Stane Merse
Keyword(s):  
System Analysis ◽  
Renewable Energy Sources ◽  
Research Work ◽  
Calculated Data ◽  
Energy Systems ◽  
Energy System ◽  
Alternative Possibilities ◽  
System Modelling ◽  
Small Energy ◽  
New Approach

Strategic planning and decision making, nonetheless making energy policies and strategies, is very extensive process and has to follow multiple and often contradictory objectives. During the preparation of the new Slovenian Energy Programme proposal, complete update of the technology and sector oriented bottom up model of Reference Energy and Environmental System of Slovenia (REES-SLO) has been done. During the redevelopment of the REES-SLO model trade-off between the simulation and optimisation approach has been done, favouring presentation of relations between controls and their effects rather than the elusive optimality of results which can be misleading for small energy systems. Scenario-based planning was integrated into the MESAP (Modular Energy System Analysis and Planning) environment, allowing integration of past, present and planned (calculated) data in a comprehensive overall system. Within the paper, the main technical, economic and environmental characteristics of the Slovenian energy system model REES-SLO are described. This paper presents a new approach in modelling relatively small energy systems which goes beyond investment in particular technologies or categories of technology and allows smooth transition to low carbon economy. Presented research work confirms that transition from environment unfriendly fossil fuelled economy to sustainable and climate friendly development requires a new approach, which must be based on excellent knowledge of alternative possibilities of development and especially awareness about new opportunities in exploitation of energy efficiency and renewable energy sources.

Sign in / Sign up

Export Citation Format

Share Document