scholarly journals A Global Dynamic Harmony Search for Optimization of a Hybrid Photovoltaic–Battery Scheme: Impact of Type of Solar Panels

2021 ◽  
Vol 14 (1) ◽  
pp. 109
Author(s):  
Jingchao Liu ◽  
Lixue Mei ◽  
Akbar Maleki ◽  
Roghayeh Ghasempour ◽  
Fathollah Pourfayaz
Keyword(s):  
Harmony Search ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimization Approach ◽  
Solar Panels ◽  
Hybrid Scheme ◽  
Total Cost ◽  
Optimal Sizing ◽  
Global Dynamic ◽  
Performance Optimizations

The type of solar panels has a great impact on the optimal sizing of a hybrid photovoltaic–battery scheme. The optimization of these schemes based on a powerful optimization approach results in more cost-effective schemes. In this paper, a new global dynamic harmony search method, as an optimization method, is presented for the optimal sizing of a hybrid photovoltaic–battery scheme. The new optimization method is aimed at minimizing the total cost and loss of load supply probability of the scheme at the same time. In this regard, the effect of the type of solar panels on the optimal sizing of the hybrid scheme is investigated. Furthermore, performance optimizations are performed with an original global dynamic harmony search, an original harmony search, and simulated annealing to determine the effectiveness of the suggested optimization method. The effects of the initial costs and efficiency of monocrystalline and polycrystalline solar panels on the optimization of hybrid systems are analyzed. The superiority of the suggested method in terms of time and cost indicators of the hybrid scheme is presented comparing the other algorithm.

Sustainability through Optimization: The Future of Watershed Management

2012 ◽  
Vol 260-261 ◽  
pp. 876-881
Author(s):  
Thambirajah Saravanapavan ◽  
Guo Shun Zhang ◽  
Mark Voorhees
Keyword(s):  
Watershed Management ◽  
Stormwater Management ◽  
Management Practices ◽  
Traditional Approach ◽  
Optimization Technique ◽  
Low Impact Development ◽  
Cost Effective ◽  
Optimization Method ◽  
Phosphorus Loading ◽  
Optimization Approach

A quantitative comparison of total costs between the traditional approach and the optimization approach for stormwater management is presented in this study. As the uniform sizing method is always associated with the traditional stormwater management practices, the optimization approach is well suited for the more recent stormwater management paradigm of low impact development (LID) practices. In the case study conducted for the town of Franklin in the Upper Charles River Watershed, Massachusetts, USA, the optimization method is able to identify stormwater management alternatives that cost 60% less than the traditional approach for meeting the Phosphorus loading reduction targets. The study highlights the comprehensive benefits from coupling optimization with the LID practices in stormwater management: 1. The LID practices’ focus on restoring the predevelopment runoff conditions ensures sustainable stormwater management, and 2. The optimization technique guarantees that the most cost-effective LID practices are selected throughout the decision-making process. The approaches outlined in this study can be very informative to many Asian countries that are under fast development and are in urgent need of scientific and sound approaches for achieving sustainable watershed management.

Harmony Search Algorithm and its Application to Product Module Identification

2011 ◽  
Vol 225-226 ◽  
pp. 1100-1104 ◽  
Author(s):  
Quan Shan ◽  
Yan Chen
Keyword(s):  
Design Theory ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Optimization Approach ◽  
Module Identification ◽  
Optimization Function ◽  
Axiomatic Design Theory

Point to product module identification, a new optimization method is proposed in this paper. This approach uses the harmony search (HS) algorithm with the synthesis design structure matrix (DSM). The synthesis DSM thinks a series of property correlations facing the product lifecycle, such as function, geometer, physics, assistant and so on. An optimization function for module identification, based on the axiomatic design theory, is established. This optimization approach, which used HS algorithm, is tested several times and compared with other classical algorithms, such as simulated annealing algorithm (SAA) and genetic algorithm (GA). The result demonstrates the feasibility of the proposed approaches.

The Application of the Combination of Monte Carlo Optimization Method based QSAR Modeling and Molecular Docking in Drug Design and Development

2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović
Keyword(s):  
Monte Carlo ◽  
Molecular Docking ◽  
Computer Calculation ◽  
Molecular Graph ◽  
Optimization Method ◽  
Docking Studies ◽  
Optimization Approach ◽  
Qsar Modeling ◽  
Monte Carlo Optimization ◽  
Molecular Docking Studies

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals Toward Decentralised Sanitary Sewage Collection Systems: A Multiobjective Approach for Cost-Effective and Resilient Designs

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1886
Author(s):  
Arezoo Zahediasl ◽  
Amin E. Bakhshipour ◽  
Ulrich Dittmer ◽  
Ali Haghighi
Keyword(s):  
Treatment Plant ◽  
Drainage System ◽  
Cost Effective ◽  
Optimization Approach ◽  
Hydraulic Design ◽  
Multiobjective Approach ◽  
Layout Generation ◽  
Plant Allocation ◽  
Problem Solving Process

In recent years, the concept of a centralized drainage system that connect an entire city to one single treatment plant is increasingly being questioned in terms of the costs, reliability, and environmental impacts. This study introduces an optimization approach based on decentralization in order to develop a cost-effective and sustainable sewage collection system. For this purpose, a new algorithm based on the growing spanning tree algorithm is developed for decentralized layout generation and treatment plant allocation. The trade-off between construction and operation costs, resilience, and the degree of centralization is a multiobjective problem that consists of two subproblems: the layout of the networks and the hydraulic design. The innovative characteristics of the proposed framework are that layout and hydraulic designs are solved simultaneously, three objectives are optimized together, and the entire problem solving process is self-adaptive. The model is then applied to a real case study. The results show that finding an optimum degree of centralization could reduce not only the network’s costs by 17.3%, but could also increase its structural resilience significantly compared to fully centralized networks.

scholarly journals Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului
Keyword(s):  
Decision Making ◽  
Ad Hoc ◽  
Market Competition ◽  
Optimal Solution ◽  
Cost Savings ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimal Decision ◽  
Environmental Damage ◽  
Fuel Cost

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.

scholarly journals How chief risk officers (CROs) can have meaningful and productive dealings with insurance agencies: a leading example

2021 ◽  
Vol 1 (5) ◽  
Author(s):  
Alberto Bettanti ◽  
Antonella Lanati
Keyword(s):  
Monte Carlo Simulation ◽  
Methodological Approach ◽  
Cost Effective ◽  
Third Parties ◽  
Computational Tool ◽  
Building Relationships ◽  
Total Cost ◽  
Retention Level ◽  
Operational Risks ◽  
Risk Appetite

AbstractIn broad terms, risk management (RM) covers four conventional actions in addressing operational risks (OpRisks), i.e., actions to mitigate, eliminate, accept, and transfer operational risks. In relation to transferring OpRisks to external third parties, this study aids chief risk officers (CROs) in addressing issues related to the reduction of economic exposure to OpRisk. In this respect, the economic handling of OpRisks and their coverage through specific insurance programs are among the major challenges that CROs face within their roles. The aim of this paper is to provide CROs with an analytical pathway to addressing these challenges by applying the total cost of risk (TCoR) method tailored to their purposes. Through a leading example, this paper demonstrates that the TCoR approach meaningfully and productively supports CROs’ decisions when striving to deal with OpRisk. In fact, the TCoR approach implementation, together with the application of Monte Carlo simulation as a computational tool, drives TCoR value optimization when OpRisk is transferred to insurance agencies. In addition, by applying a TCoR framework, CROs can find the correct and cost-effective balance between the company’s retention level—consistent with the company’s risk appetite—and the premiums paid to insurance agencies. In conclusion, this paper provides CROs with a methodological approach for efficiently building relationships with insurance agencies by consistently addressing TCoR-based dealings.

scholarly journals Seeking optimal groundwater pumping strategies at Pinggu District in Beijing, China

2012 ◽  
Vol 15 (2) ◽  
pp. 607-619 ◽  
Author(s):  
A. L. Yang ◽  
G. H. Huang ◽  
X. S. Qin ◽  
L. Li ◽  
W. Li
Keyword(s):  
Groundwater Management ◽  
Fuzzy Optimization ◽  
Cost Effective ◽  
Optimization Method ◽  
Chance Constrained Programming ◽  
Groundwater Pumping ◽  
Simulation And Optimization ◽  
Study Results ◽  
Pumping Rates ◽  
Beijing China

A simulation-based fuzzy optimization method (SFOM) was proposed for regional groundwater pumping management in considering uncertainties. SFOM enhanced the traditional groundwater management models by incorporating a response matrix model (RMM) into a fuzzy chance-constrained programming (FCCP) framework. RMM was used to approximate the input–output relationship between pumping actions and subsurface hydrologic responses. Due to its explicit expression, RMM could be easily embedded into an optimization model to help seek cost-effective pumping solutions. A groundwater management case in Pinggu District of Beijing, China, was used to demonstrate the method's applicability. The study results showed that the obtained system cost and pumping rates would vary significantly under different confidence levels of constraints satisfaction. The decision-makers could identify the best groundwater pumping strategy through analyzing the tradeoff between the risk of violating the related water resources conservation target and the economic benefit. Compared with traditional approaches, SFOM was particularly advantageous in linking simulation and optimization models together, and tackling uncertainties using fuzzy chance constraints.

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