Telecommunication Technologies for Smart Grids: Total Cost Optimization

2018 ◽  
pp. 451-478
Author(s):  
Marcelo Eduardo Vieira Segatto ◽  
Helder Roberto de Oliveira Rocha ◽  
Jair Adriano Lima Silva ◽  
Marcia Helena Moreira Paiva ◽  
Marco António do Rosário Santos Cruz
Keyword(s):  
Smart Grids ◽  
Cost Optimization ◽  
Total Cost

COST OPTIMIZATION OF MULTIPLE RESOURCES ALLOCATION FOR MULTI-PROJECTS

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Sarah Aboul Fotouh ◽  
A. Samer Ezeldin
Keyword(s):  
Genetic Algorithm ◽  
Construction Industry ◽  
Cost Optimization ◽  
Project Managers ◽  
Resources Allocation ◽  
Total Cost ◽  
Multiple Resources ◽  
The Cost ◽  
Critical Resources ◽  
Available Resources

As the construction industry grows year by year, optimization of resources is becoming essential to reduce their required number, their costs and as a consequence the total cost of the project. Project managers have to face problems regarding management of cost, time, and available resources for single projects. What is more challenging is to optimize the available resources for multiple projects, which would result in appreciable savings. Most of the companies in the construction industry commonly optimize the resources for single project. However, with the presence of several mega projects in many developing countries running at the same time, there is a need for a model to enhance the efficiency of available resources among multiple simultaneous projects. This paper discusses a numerical model of cost optimization and allocation of up to nine resources for up to three projects for a given company, taking into consideration the transportation of resources from one project to another and the cost of unused resources. The model was developed using a genetic algorithm, and it is used on the identified critical resources. It calculates the cost of each resource, minimizes the cost of extra resources, cost of unused resources, and generates the schedule of each project within a selected overall program.

scholarly journals Impact of PHEVs on Spinning Reserve and Frequency Regulation Market in Smart Grids

2019 ◽  
Vol 3 (4) ◽  
Author(s):  
Ali Ramzanzadeh Badeleh
Keyword(s):  
Electric Vehicles ◽  
Smart Grids ◽  
Hybrid Electric Vehicles ◽  
Cost Optimization ◽  
Power Grids ◽  
Frequency Regulation ◽  
Spinning Reserve ◽  
High Penetration ◽  
Optimization Study ◽  
Reliable Source

Plug-in hybrid electric vehicles (PHEVs) are being used in today’s smart grid with high penetration. In addition to their main transportation duty, they can be used as a reliable source of energy for the grid at the time of high demand and save money for their owners. Because PHEVs are able to quickly respond to systems need, they can be used for applications such as reserve and frequency regulations. This paper presents a cost optimization study on the effect of PHEVs presence in the reserve and frequency regulations in power grids.

scholarly journals Distributed multi-objective scheduling of power consumption for smart buildings

2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Marvin Nebel-Wenner ◽  
Christian Reinhold ◽  
Farina Wille ◽  
Astrid Nieße ◽  
Michael Sonnenschein
Keyword(s):  
Power Consumption ◽  
Smart Grids ◽  
Residential Buildings ◽  
Cost Optimization ◽  
Peak Load ◽  
Load Management ◽  
Management Technique ◽  
Smart Buildings ◽  
Multi Objective ◽  
The Cost

Abstract Load management of electrical devices in residential buildings can be applied with different goals in the power grid, such as the cost optimization regarding variable electricity prices, peak load reduction or the minimization of behavioral efforts for users due to load shifting. A cooperative multi-objective optimization of consumers and generators of power has the potential to solve the simultaneity problem of power consumption and optimize the power supply from the superposed grid regarding different goals. In this paper, we present a multi-criteria extension of a distributed cooperative load management technique in smart grids based on a multi-agent framework. As a data basis, we use feasible power consumption and production schedules of buildings, which have been derived from simulations of a building model and have already been optimized with regard to self-consumption. We show that the flexibilities of smart buildings can be used to pursue different targets and display the advantage of integrating various goals into one optimization process.

Computational Methods for Residential Energy Cost Optimization in Smart Grids

2016 ◽  
Vol 49 (1) ◽  
pp. 1-34 ◽  
Author(s):  
Muhammad Raisul Alam ◽  
Marc St-Hilaire ◽  
Thomas Kunz
Keyword(s):  
Computational Methods ◽  
Energy Cost ◽  
Smart Grids ◽  
Cost Optimization ◽  
Residential Energy

Total cost optimization of submersible irrigation pump maintenance using simulation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Niguss Haregot Hatsey ◽  
Seyoum Eshetu Birkie
Keyword(s):  
Smallholder Farmers ◽  
Cost Minimization ◽  
Cost Optimization ◽  
Spare Part ◽  
Economic Consequences ◽  
Maintenance Cost ◽  
Supply Uncertainty ◽  
Pump System ◽  
Content Type ◽  
Total Cost

PurposeThe unpredictable failure of submersible pump (SP) in groundwater irrigation systems has considerable negative economic consequences. The purpose of this paper is to develop a total cost minimization model that aims to optimize maintenance actions for SP. It reports on simulation-based stochastic scenario analysis for evaluating total cost of maintenance.Design/methodology/approachStochastic simulation modeling has been performed for failure of pump motor and corresponding maintenance. Five alternative scenarios were compared for total cost over 15 years starting with empirical data from a northern Ethiopian site. Downtime probabilities and spare part supply uncertainty have been considered in the mathematical model. The model is also validated using multiple ways.FindingsThe scenario comparisons indicate that despite the challenges of accessing SP doing one motor rewinding for each purchased pump system upon failure (preferably with shorter supply lead time and variability) seems to result in lowest overall costs for the time horizon considered.Practical implicationsThe model should help to make informed practical decision regarding planning and management of SP failure systems in a developing economy context. This should, therefore, lead to better revenue for smallholder farmers and improved food security in similar context.Originality/valueThere are limited number of publications that consider the life cycle costs with stochastic analysis when it comes to maintenance of SPs. To the best of the authors’ knowledge, no paper has previously directly addressed maintenance cost optimization for SP in irrigation. The study could be used to develop more sophisticated stochastic models with more efficient algorithms and consideration of additional sources of stochasticity for such system.

scholarly journals Cloud Provisioning for Work ow Application with Deadline using Discrete PSO

1970 ◽  
Vol 7 (1) ◽  
pp. 43-51
Author(s):  
Nuttapong Netjinda ◽  
Tiranee Achalakul ◽  
Booncharoen Sirinaovakul
Keyword(s):  
Task Scheduling ◽  
Cost Optimization ◽  
Optimal Solution ◽  
Cloud Provider ◽  
Total Cost ◽  
Np Hard Problem ◽  
Discrete Pso ◽  
Initial Results ◽  
New Framework ◽  
And Task

The need of cloud consumers to optimize all options offered by cloud provider has been rapidly arisen during the recent years. The consideration involves the appropriate number of VMs must be purchased along with the allocation of supporting resources. Moreover, commercial clouds may have many different purchasing options. Finding optimal provisioning solutions is thus an NP-hard problem. Currently, there are many research works discussing the cloud provisioning cost optimization. However, most of the works mainly concerned with task scheduling. In this paper, we proposed a new framework where number of purchased instance, instance type, purchasing options, and task scheduling are considered within an optimization process. The Particle Swarm Optimization (PSO) technique is used to find the optimal solution. The initial results show a promising performance in both the perspectives of the total cost and fitness convergence. The designed system provides the solutions of purchasing options with optimum budget for any specified workflow-based application based on the required performance.

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