scholarly journals Towards the Design of Resilient Waste-to-Energy Systems Using Bayesian Networks

2018 ◽  
Author(s):  
W. H. Jonathan Mak ◽  
Michel-Alexandre Cardin ◽  
Liu Ziqi ◽  
P. John Clarkson
Keyword(s):  
Bayesian Networks ◽  
Net Present Value ◽  
Energy System ◽  
Waste To Energy ◽  
Engineering System ◽  
Design Strategies ◽  
Expansion Strategy ◽  
Fixed Design ◽  
The Impact ◽  
Initial Capacity

The concept of resilience has emerged from various domains to address how systems, people and organizations can handle uncertainty. This paper presents a method to improve the resilience of an engineering system by maximizing the system economic lifecycle value, as measured by Net Present Value, under uncertainty. The method is applied to a Waste-to-Energy system based in Singapore and the impact of combining robust and flexible design strategies to improve resilience are discussed. Robust strategies involve optimizing the initial capacity of the system while Bayesian Networks are implemented to choose the flexible expansion strategy that should be deployed given the current observations of demand uncertainties. The Bayesian Network shows promise and should be considered further where decisions are more complex. Resilience is further assessed by varying the volatility of the stochastic demand in the simulation. Increasing volatility generally made the system perform worse since not all demand could be converted to revenue due to capacity constraints. Flexibility shows increased value compared to a fixed design. However, when the system is allowed to upgrade too often, the costs of implementation negates the revenue increase. The better design is to have a high initial capacity, such that there is less restriction on the demand with two or three expansions.

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 Thermodynamic and Economic Analyses of a New Waste-to-Energy System Incorporated with a Biomass-Fired Power Plant

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4345
Author(s):  
Peiyuan Pan ◽  
Meiyan Zhang ◽  
Gang Xu ◽  
Heng Chen ◽  
Xiaona Song ◽  
...  
Keyword(s):  
Power Plant ◽  
Net Present Value ◽  
Performance Enhancement ◽  
Integrated Design ◽  
Energy System ◽  
Waste To Energy ◽  
Low Pressure Turbine ◽  
Energy Plant ◽  
Energy And Exergy ◽  
Economic Analyses

A novel design has been developed to improve the waste-to-energy process through the integration with a biomass-fired power plant. In the proposed scheme, the superheated steam generated by the waste-to-energy boiler is fed into the low-pressure turbine of the biomass power section for power production. Besides, the feedwater from the biomass power section is utilized to warm the combustion air of the waste-to-energy boiler, and the feedwater of the waste-to-energy boiler is offered by the biomass power section. Based on a 35-MW biomass-fired power plant and a 500-t/d waste-to-energy plant, the integrated design was thermodynamically and economically assessed. The results indicate that the net power generated from waste can be enhanced by 0.66 MW due to the proposed solution, and the waste-to-electricity efficiency increases from 20.49% to 22.12%. Moreover, the net present value of the waste-to-energy section is raised by 5.02 million USD, and the dynamic payback period is cut down by 2.81 years. Energy and exergy analyses were conducted to reveal the inherent mechanism of performance enhancement. Besides, a sensitivity investigation was undertaken to examine the performance of the new design under various conditions. The insights gained from this study may be of assistance to the advancement of waste-to-energy technology.

scholarly journals Performance Analysis of a Waste-to-Energy System Integrated with the Steam–Water Cycle and Urea Hydrolysis Process of a Coal-Fired Power Unit

2022 ◽  
Vol 12 (2) ◽  
pp. 866
Author(s):  
Yuanyuan Zhang ◽  
Lai Wei ◽  
Xin Gao ◽  
Heng Chen ◽  
Qiubai Li ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Unit ◽  
System Integration ◽  
Net Present Value ◽  
Integrated Design ◽  
Energy System ◽  
Exergy Efficiency ◽  
Urea Hydrolysis ◽  
Waste To Energy ◽  
Energy Unit

An innovative hybrid energy system consisting of a waste-to-energy unit and a coal-fired power unit is designed to enhance the energy recovery of waste and decrease the investment costs of waste-to-energy unit. In this integrated design, partial cold reheat steam of the coal-fired unit is heated by the waste-to-energy boiler’s superheater. The heat required for partial preheated air of waste-to-energy unit and its feedwater are supplied by the feedwater of CFPU. In addition, an additional evaporator is deployed in the waste-to-energy boiler, of which the outlet stream is utilized to provide the heat source for the urea hydrolysis unit of coal-fired power plant. The stand-alone and proposed designs are analyzed and compared through thermodynamic and economic methods. Results indicate that the net total energy efficiency increases from 41.84% to 42.12%, and the net total exergy efficiency rises from 41.19% to 41.46% after system integration. Moreover, the energy efficiency and exergy efficiency of waste-to-energy system are enhanced by 10.48% and 9.92%, respectively. The dynamic payback period of new waste-to-energy system is cut down from 11.39 years to 5.48 years, and an additional net present value of $14.42 million is got than before.

The impact of subway operation on urban traffic: A GRA-BNs based study

2021 ◽  
pp. 1-16
Author(s):  
Lixin Yan ◽  
Tao Zeng ◽  
Yubing Xiong ◽  
Zhenyun Li ◽  
Qingmei Liu
Keyword(s):  
Bayesian Networks ◽  
Operating Characteristic ◽  
Urban Traffic ◽  
Relational Analysis ◽  
Traffic Security ◽  
Structural Network ◽  
Random Decision Forest ◽  
Roc Area ◽  
Grey Relational ◽  
The Impact

With the development of urbanization, urban traffic has exposed many problems. To study the subway’s influence on urban traffic, this paper collects data on traffic indicators in Nanchang from 2008 to 2018. The research is carried out from three aspects: traffic accessibility, green traffic, and traffic security. First, Grey Relational Analysis is used to select 18 traffic indicators correlated with the subway from 22 traffic indicators. Second, the data is discretized and learned based on Bayesian Networks to construct the structural network of the subway’s influence. Third, to verify the reliability of using GRA and the effectiveness of Bayesian Networks (GRA-BNs), Bayesian Networks with full indicators analysis and other four algorithms (Naive Bayes, Random Decision Forest, Logistic and regression) are employed for comparison. Moreover, the receiver operating characteristic (ROC) area, true positive (TP) rate, false positive (FP) rate, precision, recall, F-measure, and accuracy are utilized for comparing each situation. The result shows that GRA-BNs is the most effective model to study the impact of the subway’s operation on urban traffic. Then, the dependence relations between the subway and each index are analyzed by the conditional probability tables (CPTs). Finally, according to the analysis, some suggestions are put forward.

scholarly journals Electric Vehicle Integration into Road Transportation, Intelligent Transportation, and Electric Power Systems: An Abu Dhabi Case Study

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1039-1057
Author(s):  
Amro M. Farid ◽  
Asha Viswanath ◽  
Reem Al-Junaibi ◽  
Deema Allan ◽  
Thomas J. T. Van der Van der Wardt
Keyword(s):  
Electric Power ◽  
Intelligent Transportation ◽  
Energy System ◽  
Transportation System ◽  
Electric Power System ◽  
Abu Dhabi ◽  
Road Transportation ◽  
Unit Distance ◽  
The Impact

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

scholarly journals Technology Entrepreneurship and the Performance of Enterprises in the Conditions of Covid-19 Pandemic: The Fuzzy Set Analysis of Waste to Energy Enterprises in Poland

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3891
Author(s):  
Piotr Kordel ◽  
Radosław Wolniak
Keyword(s):  
Fuzzy Set ◽  
High Performance ◽  
Qualitative Comparative Analysis ◽  
Flexible Structures ◽  
Implementation Strategies ◽  
Waste To Energy ◽  
Energy Industry ◽  
Technology Entrepreneurship ◽  
Research Results ◽  
The Impact

This article’s aim is to explain the impact of technology entrepreneurship phenomenon on waste management enterprise performance in the conditions of COVID-19 pandemic. The concept of technology entrepreneurship according to the configuration approach and the category of high-performance organization are the theoretical bases of empirical investigation. For the implementation of empirical research, Fuzzy set Qualitative Comparative Analysis (FsQCA) was adopted. The research sample included a group of producers of Refused Derived Fuel (RDF) as a central part of the waste to energy industry located in Poland. The research results showed that the waste to energy sector is highly immune to pandemic threats. While during COVID-19, the basic economic parameters (i.e., sales, profitability and employment) of the entire industry in Poland clearly decreased, the same parameters in the case of the waste to energy industry remained at the same level. The research results allow the formulation of two high-performance models of technology entrepreneurship in the waste to energy industry under COVID-19 conditions. The first model is based on traditional technologies and hierarchical organizational structures, and the second is using innovative technologies and flexible structures. Both technology entrepreneurship models are determined by their emergence as complementary to implementation strategies and the opportunity-oriented allocation of resources within business model portfolios.

scholarly journals Decomposition Analysis of the Evolution of the Local Energy System as a Tool to Assess the Effect of Local Actions: Methodology and Example of Malmö, Sweden

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 461
Author(s):  
Isabel Azevedo ◽  
Vítor Leal
Keyword(s):  
Local Level ◽  
Ghg Emissions ◽  
Decomposition Analysis ◽  
Specific Effect ◽  
Energy System ◽  
Local Energy ◽  
Total Change ◽  
The Impact ◽  
Change Mitigation

This paper proposes the use of decomposition analysis to assess the effect of local energy-related actions towards climate change mitigation, and thus improve policy evaluation and planning at the local level. The assessment of the impact of local actions has been a challenge, even from a strictly technical perspective. This happens because the total change observed is the result of multiple factors influencing local energy-related greenhouse gas (GHG) emissions, many of them not even influenced by local authorities. A methodology was developed, based on a recently developed decomposition model, that disaggregates the total observed changes in the local energy system into multiple causes/effects (including local socio-economic evolution, technology evolution, higher-level governance frame and local actions). The proposed methodology, including the quantification of the specific effect associated with local actions, is demonstrated with the case study of the municipality of Malmö (Sweden) in the timeframe between 1990 and 2015.

scholarly journals Computer Model for Financial, Environmental and Risk Analysis of a Wind–Diesel Hybrid System with Compressed Air Energy Storage

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4054 ◽  
Author(s):  
Youssef Benchaabane ◽  
Rosa Elvira Silva ◽  
Hussein Ibrahim ◽  
Adrian Ilinca ◽  
Ambrish Chandra ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Renewable Energy ◽  
Energy Storage ◽  
Environmental Impact ◽  
Hybrid System ◽  
Computer Model ◽  
Net Present Value ◽  
Compressed Air ◽  
Compressed Air Energy Storage ◽  
The Impact

Remote and isolated communities in Canada experience gaps in access to stable energy sources and must rely on diesel generators for heat and electricity. However, the cost and environmental impact resulting from the use of fossil fuels, especially in local energy production, heating, industrial processes and transportation are compelling reasons to support the development and deployment of renewable energy hybrid systems. This paper presents a computer model for economic analysis and risk assessment of a wind–diesel hybrid system with compressed air energy storage. The proposed model is developed from the point of view of the project investor and it includes technical, financial, risk and environmental analysis. Robustness is evaluated through sensitivity analysis. The model has been validated by comparing the results of a wind–diesel case study against those obtained using HOMER (National Renewable Energy Laboratory, Golden, CO, United States) and RETScreen (Natural Resources Canada, Government of Canada, Canada) software. The impact on economic performance of adding energy storage system in a wind–diesel hybrid system has been discussed. The obtained results demonstrate the feasibility of such hybrid system as a suitable power generator in terms of high net present value and internal rate of return, low cost of energy, as well as low risk assessment. In addition, the environmental impact is positive since less fuel is used.

Sign in / Sign up

Export Citation Format

Share Document