scholarly journals Energy and Uncertainty: Models and Algorithms for Complex Energy Systems

AI Magazine ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 8-21 ◽  
Author(s):  
Warren Powell
Keyword(s):  
Learning Community ◽  
Value Function ◽  
Optimization Problems ◽  
Energy Systems ◽  
Modeling Framework ◽  
Different Types ◽  
Case Application ◽  
Storage Problem ◽  
Function Approximations ◽  
Uncertainty Models

The problem of controlling energy systems (generation, transmission, storage, investment) introduces a number of optimization problems which need to be solved in the presence of different types of uncertainty. We highlight several of these applications, using a simple energy storage problem as a case application. Using this setting, we describe a modeling framework based around five fundamental dimensions which is more natural than the standard canonical form widely used in the reinforcement learning community. The framework focuses on finding the best policy, where we identify four fundamental classes of policies consisting of policy function approximations (PFAs), cost function approximations (CFAs), policies based on value function approximations (VFAs), and lookahead policies. This organization unifies a number of competing strategies under a common umbrella.

scholarly journals Optimal Planning of Electricity-Natural Gas Coupling System Considering Power to Gas Facilities

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3400
Author(s):  
Jie Xing ◽  
Peng Wu
Keyword(s):  
Natural Gas ◽  
Energy Systems ◽  
Optimal Planning ◽  
Planning Model ◽  
Operation Costs ◽  
Coupling System ◽  
Gas System ◽  
Different Types ◽  
Power To Gas ◽  
Natural Gas System

Bidirectional coupling systems for electricity and natural gas composed of gas units and power-to-gas (P2G) facilities improve the interactions between different energy systems. In this paper, a combined optimization planning method for an electricity-natural gas coupling system with P2G was studied. Firstly, the characteristics of the component model of the electricity-natural gas coupling system were analyzed. The optimization planning model for the electricity-natural gas coupling system was established with the goal of minimizing the sum of the annual investment costs and the annual operation costs. Based on the established model, the construction statuses for different types of units, power lines, and pipelines and the output distribution values for gas units and P2G stations were optimized. Then, the immune algorithm was proposed to solve the optimization planning model. Finally, an electricity-natural gas coupling system composed of a seven-node natural gas system and a nine-node power system was taken as an example to verify the rationality and effectiveness of the model under different scenarios.

scholarly journals Carbons Formed in Methane Thermal and Thermocatalytic Decomposition Processes: Properties and Applications

2021 ◽  
Vol 7 (3) ◽  
pp. 50
Author(s):  
Emmi Välimäki ◽  
Lasse Yli-Varo ◽  
Henrik Romar ◽  
Ulla Lassi
Keyword(s):  
Thermal Decomposition ◽  
Hydrogen Production ◽  
Energy Systems ◽  
Hydrogen Gas ◽  
Solid Carbon ◽  
Hydrogen Economy ◽  
Decomposition Processes ◽  
Different Types ◽  
Decomposition Of Methane ◽  
Thermocatalytic Decomposition

The hydrogen economy will play a key role in future energy systems. Several thermal and catalytic methods for hydrogen production have been presented. In this review, methane thermocatalytic and thermal decomposition into hydrogen gas and solid carbon are considered. These processes, known as the thermal decomposition of methane (TDM) and thermocatalytic decomposition (TCD) of methane, respectively, appear to have the greatest potential for hydrogen production. In particular, the focus is on the different types and properties of carbons formed during the decomposition processes. The applications for carbons are also investigated.

Optimization of Cold-Formed Channel Sections Using Imperialist Competitive Algorithm

2012 ◽  
Vol 166-169 ◽  
pp. 493-496
Author(s):  
Roya Kohandel ◽  
Behzad Abdi ◽  
Poi Ngian Shek ◽  
M.Md. Tahir ◽  
Ahmad Beng Hong Kueh
Keyword(s):  
Sequential Quadratic Programming ◽  
Optimization Problems ◽  
Imperialist Competitive Algorithm ◽  
Computational Method ◽  
Compression Force ◽  
Sqp Method ◽  
Competitive Algorithm ◽  
Different Types ◽  
Formed Channel ◽  
Good Agreement

The Imperialist Competitive Algorithm (ICA) is a novel computational method based on the concept of socio-political motivated strategy, which is usually used to solve different types of optimization problems. This paper presents the optimization of cold-formed channel section subjected to axial compression force utilizing the ICA method. The results are then compared to the Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) algorithm for validation purpose. The results obtained from the ICA method is in good agreement with the GA and SQP method in terms of weight but slightly different in the geometry shape.

scholarly journals Metaheuristic Optimization of Power and Energy Systems: Underlying Principles and Main Issues of the ‘Rush to Heuristics’

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5097
Author(s):  
Gianfranco Chicco ◽  
Andrea Mazza
Keyword(s):  
Global Optimization ◽  
Specific Problem ◽  
Optimization Problems ◽  
Energy Systems ◽  
Progressive Increase ◽  
Metaheuristic Algorithms ◽  
Metaheuristic Algorithm ◽  
Power And Energy Systems ◽  
Power And Energy ◽  
Better Than

In the power and energy systems area, a progressive increase of literature contributions that contain applications of metaheuristic algorithms is occurring. In many cases, these applications are merely aimed at proposing the testing of an existing metaheuristic algorithm on a specific problem, claiming that the proposed method is better than other methods that are based on weak comparisons. This ‘rush to heuristics’ does not happen in the evolutionary computation domain, where the rules for setting up rigorous comparisons are stricter but are typical of the domains of application of the metaheuristics. This paper considers the applications to power and energy systems and aims at providing a comprehensive view of the main issues that concern the use of metaheuristics for global optimization problems. A set of underlying principles that characterize the metaheuristic algorithms is presented. The customization of metaheuristic algorithms to fit the constraints of specific problems is discussed. Some weaknesses and pitfalls that are found in literature contributions are identified, and specific guidelines are provided regarding how to prepare sound contributions on the application of metaheuristic algorithms to specific problems.

Subdividing the sprawl: Endogenous segmentation of housing submarkets in expansion areas of Santiago, Chile

2020 ◽  
pp. 239980832094772
Author(s):  
Tomás Cox ◽  
Ricardo Hurtubia
Keyword(s):  
Real Estate ◽  
Latent Class ◽  
Latent Class Models ◽  
Modeling Framework ◽  
Quantitative Studies ◽  
Different Types ◽  
Real Estate Projects ◽  
Socioeconomic Segregation ◽  
Housing Submarkets ◽  
Location Strategies

Urban sprawl is a phenomenon observed in most cities around the globe and especially in Latin America, where it is associated to socioeconomic segregation. In the case of Chile, sprawl has been generally based on large real estate projects. Developers target their projects to different types of consumers, which translates into submarkets with a broad range of housing-unit’s characteristics, but also different location strategies. This heterogeneity has been analyzed and measured in the literature, but quantitative studies have used exogenous or sequential methods to identify submarkets, leading to potential bias in the segmentation. In this paper, we propose an econometric model to measure location drivers for different types of real estate projects that fills this gap. The modeling framework is based on discrete-choice and latent-class models, allowing us to simultaneously identify market segmentations, and their particular location choice preferences, without the need of arbitrary or ex-ante definitions of submarkets. The model is applied to the city of Santiago, Chile. The results reveal two clearly different approaches taken by developers to produce housing, with one submarket of “exclusive” and more sprawling projects, and another submarket of “massive” and more density driven projects. Location strategies are very different between submarkets, reproducing the socio-spatial segregation already observed in the consolidated city.

A Linear Optimization Approach for Increasing Sustainability in Vegetable Crop Production

2011 ◽  
pp. 234-265 ◽  
Author(s):  
Lana dos Santos ◽  
Marcos Arenales ◽  
Alysson Costa ◽  
Ricardo Santos
Keyword(s):  
Crop Rotation ◽  
Crop Production ◽  
Optimization Problems ◽  
Linear Optimization ◽  
Future Research ◽  
Optimization Approach ◽  
Vegetable Crops ◽  
Vegetable Crop ◽  
Modeling Framework ◽  
Ecological Criteria

This chapter is concerned with a set of optimization problems associated to crop rotation scheduling in the context of vegetable crop production according to some ecological criteria: no crop of the same botanic family is planted in sequence, green manure and fallow periods must be present in any schedule. A core mathematical model called the crop rotation scheduling model is proposed to represent these ecological criteria together with specific technical constraints associated to the growing of vegetable crops. Three optimization problems based on crop rotation schedules are written in detail in this chapter. For each problem, the authors present a general modeling framework and a solution methodology based on a technique known as column generation, which iteratively builds crop rotation plans for a number of plots. Some extensions are also presented, with the aim of incorporating additional characteristics found in production field conditions. This chapter ends with a brief discussion on a set of computational experiments and some suggestions for future research.

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