scholarly journals Reducing the Cost of Electricity by Optimizing Real-Time Consumer Planning Using a New Genetic Algorithm-Based Strategy

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1144 ◽  
Author(s):  
Laurentiu-Mihai Ionescu ◽  
Nicu Bizon ◽  
Alin-Gheorghita Mazare ◽  
Nadia Belu
Keyword(s):  
Genetic Algorithm ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Time Interval ◽  
Renewable Sources ◽  
Total Cost ◽  
Cost Of Electricity ◽  
Cost Of Energy ◽  
Input Parameters ◽  
The Cost

To ensure the use of energy produced from renewable energy sources, this paper presents a method for consumer planning in the consumer–producer–distributor structure. The proposed planning method is based on the genetic algorithm approach, which solves a cost minimization problem by considering several input parameters. These input parameters are: the consumption for each unit, the time interval in which the unit operates, the maximum value of the electricity produced from renewable sources, and the distribution of energy production per unit of time. A consumer can use the equipment without any planning, in which case he will consume energy supplied by a distributor or energy produced from renewable sources, if it is available at the time he operates the equipment. A consumer who plans his operating interval can use more energy from renewable sources, because the planning is done in the time interval in which the energy produced from renewable sources is available. The effect is that the total cost of energy to the consumer without any planning will be higher than the cost of energy to the consumer with planning, because the energy produced from renewable sources is cheaper than that provided from conventional sources. To be validated, the proposed approach was run on a simulator, and then tested in two real-world case studies targeting domestic and industrial consumers. In both situations, the solution proposed led to a reduction in the total cost of electricity of up to 25%.

scholarly journals Optimized Placement of Connecting the Distributed Generationswork Stand Alone to Improve the Distribution Systems Reliability

2013 ◽  
Vol 64 (2) ◽  
pp. 76-83
Author(s):  
Hamed Hashemi-Dezaki ◽  
Ali Agheli ◽  
Behrooz Vahidi ◽  
Hossein Askarian-Abyaneh
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
System Reliability ◽  
Distribution Systems ◽  
Analytical Approach ◽  
Distributed Generations ◽  
Joint Point ◽  
Cost Of Energy ◽  
Optimum Solution ◽  
The Cost

The use of distributed generations (DGs) in distribution systems has been common in recent years. Some DGs work stand alone and it is possible to improve the system reliability by connecting these DGs to system. The joint point of DGs is an important parameter in the system designing. In this paper, a novel methodology is proposed to find the optimum solution in order to make a proper decision about DGs connection. In the proposed method, a novel objective function is introduced which includes the cost of connector lines between DGs and network and the cost of energy not supplied (CENS) savings. Furthermore, an analytical approach is used to calculate the CENS decrement. To solve the introduced nonlinear optimization programming, the genetic algorithm (GA) is used. The proposed method is applied to a realistic 183-bus system of Tehran Regional Electrical Company (TREC). The results illustrate the effectiveness of the method to improve the system reliability by connecting the DGs work stand alone in proper placements.

Hybrid Distributed Power Generation for an Isolated Rural Settlement in Masirah Island, Oman

2011 ◽  
Author(s):  
Saleh Al Saadi ◽  
Moncef Krarti
Keyword(s):  
Power Systems ◽  
Residential Buildings ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Small Community ◽  
Solar Pv ◽  
Cost Of Energy ◽  
Storage Batteries ◽  
Electrical Generation ◽  
The Cost

This paper summarizes the findings from a feasibility study of using renewable energy sources in combination with conventional power systems to meet the electrical requirements for an isolated island of Masirah in Oman. The study has been conducted to determine the best hybrid system to generate electrical energy needed for a small community of 500 residential buildings. A series of a simulation analyses have been carried out to evaluate and optimize different distribution technologies including photovolatics, wind and diesel for electrical generation in combination with storage batteries. It was found that the cost of energy could be reduced by as much as 48% compared to the cost for the baseline generation system currently used in the Masirah Island (i.e. diesel-driven generators). In particular, it was found that wind turbines in combination with storage batteries have a great impact in reducing the cost of generating electrical energy for the residential community. Moreover, solar PV panels were found unattractive under the current diesel price rates but could potentially become viable if the diesel prices increase. The paper outlines an optimal design for generating electricity for the community at lowest cost while minimizing carbon emissions.

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 Genetic algorithm for network cost minimization using threshold based discounting

2003 ◽  
Vol 7 (4) ◽  
pp. 207-228 ◽  
Author(s):  
Hrvoje Podnar ◽  
Jadranka Skorin-Kapov
Keyword(s):  
Genetic Algorithm ◽  
Communication Networks ◽  
Branch And Bound ◽  
Cost Minimization ◽  
Total Flow ◽  
Cpu Time ◽  
Network Cost ◽  
Cost Minimization Problem ◽  
The Cost ◽  
Different Sources

We present a genetic algorithm for heuristically solving a cost minimization problem applied to communication networks with threshold based discounting. The network model assumes that every two nodes can communicate and offers incentives to combine flow from different sources. Namely, there is a prescribed threshold on every link, and if the total flow on a link is greater than the threshold, the cost of this flow is discounted by a factor α. A heuristic algorithm based on genetic strategy is developed and applied to a benchmark set of problems. The results are compared with former branch and bound results using the CPLEX® solver. For larger data instances we were able to obtain improved solutions using less CPU time, confirming the effectiveness of our heuristic approach.

scholarly journals Techno-Economic Optimisation for a Wave Energy Converter via Genetic Algorithm

2020 ◽  
Vol 8 (7) ◽  
pp. 482 ◽  
Author(s):  
Sergej Antonello Sirigu ◽  
Ludovico Foglietta ◽  
Giuseppe Giorgi ◽  
Mauro Bonfanti ◽  
Giulia Cervelli ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Wave Energy ◽  
Capital Expenditure ◽  
Ocean Waves ◽  
Wave Energy Converter ◽  
Width Ratio ◽  
Energy Converter ◽  
Essential Condition ◽  
Cost Of Energy ◽  
The Cost

Although sea and ocean waves have been widely acknowledged to have the potential of providing sustainable and renewable energy, the emergence of a self-sufficient and mature industry is still lacking. An essential condition for reaching economic viability is to minimise the cost of electricity, as opposed to simply maximising the converted energy at the early design stages. One of the tools empowering developers to follow such a virtuous design pathway is the techno-economic optimisation. The purpose of this paper is to perform a holistic optimisation of the PeWEC (pendulum wave energy converter), which is a pitching platform converting energy from the oscillation of a pendulum contained in a sealed hull. Optimised parameters comprise shape; dimensions; mass properties and ballast; power take-off control torque and constraints; number and characteristics of the pendulum; and other subcomponents. Cost functions are included and the objective function is the ratio between the delivered power and the capital expenditure. Due to its ability to effectively deal with a large multi-dimensional design space, a genetic algorithm is implemented, with a specific modification to handle unfeasible design candidate and improve convergence. Results show that the device minimising the cost of energy and the one maximising the capture width ratio are substantially different, so the economically-oriented metric should be preferred.

scholarly journals Optimization Model and Algorithm of Empty Pallets Dispatching under the Time-Space Network of Express Shipment

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Kang Zhou ◽  
Shiwei He ◽  
Rui Song ◽  
Xiaole Guo ◽  
Kaiming Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Clonal Selection ◽  
Transportation Cost ◽  
Transport Cost ◽  
Utilization Rate ◽  
Time Requirement ◽  
Total Cost ◽  
Time Space ◽  
The Cost

Relying on the express freight network, the dispatching of empty pallets based on the pallet pool mode is studied to reuse pallets with the minimum transport cost, enhance the pallet utilization rate, reduce the waste of resources, and save the cost of logistics. Considering the influence of transport efficiency for different modes in transportation process, differences of transportation cost, carbon emissions, and transportation timeliness of demand points required, an optimization model is constructed. The objective of the model is to minimize the total cost including transportation cost, inventory cost, lease cost, and loss cost. According to the structural characteristics of the model, genetic algorithm and improved cloud clonal selection operation is used to solve the model. Finally, the validity and rationality of the optimization model are verified by a case study. The result shows that the total dispatching cost of considering time requirement is 1.8 times the cost without considering the time requirement, respectively, both less than the total cost of pallets leasing. Moreover, when there are 3 supply points and 2 demand points and the number of iterations is 100, after the algorithms are run for 30 times, the worst values are 9305 and 8317 for genetic algorithm and the improved cloud clonal selection operation, respectively. Therefore, the efficiency of the improved cloud clonal selection operation is higher than genetic algorithm.

Optimization of Hybrid Renewable Energy System (HRES) Using Modified Evolutionary Strategy for Cost Minimization

2015 ◽  
Vol 785 ◽  
pp. 546-550
Author(s):  
Ahmad Syazwan Aznan ◽  
Ismail Musirin ◽  
Siti Aliyah Mohd Saleh ◽  
Nur Azzammudin Rahmat
Keyword(s):  
Renewable Energy ◽  
Distribution System ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Evolutionary Strategy ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
The Cost ◽  
Hybrid Renewable Energy

Recently, renewable energy has been in place to cater the depreciation of main energy. The presence of renewable energy sources can be made in hybrid to satisfy the demand in the distribution system. Nevertheless, the growth in number for renewable energy could lead to cost increment. This paper presents the optimization process of Hybrid Renewable Energy System (HRES) using Modified Evolutionary Strategy (ES) technique for cost minimization. The study involves the development of optimization engine for modified ES in order to solve the cost minimization of HRES. The improved version of ES is expected to address the computation burden experienced by the traditional ES technique. Results obtained from the implementation of the modified ES managed to reveal that its implementation is worth in terms of minimizing the cost

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Marcelo Ramos Martins ◽  
Diego F. Sarzosa Burgos
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Ship Design ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Multi Objective ◽  
The Cost

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies.

scholarly journals Identification of Efficient Energy Source among Solar, Biomass and Battery for Electric Vehicle Charging using Novel Optimal Firefly Algorithm

2021 ◽  
Author(s):  
Nishant Kumar ◽  
Kumari Namrata
Keyword(s):  
Solar Energy ◽  
Firefly Algorithm ◽  
Renewable Energy Sources ◽  
Solar Panel ◽  
Annual Basis ◽  
Cost Of Energy ◽  
The Cost ◽  
Charging Stations ◽  
Ev Charging ◽  
Effective Source

Abstract Background: The EV (Electric Vehicles) is rapidly growing as a substitute to oil dependant vehicles to minimize the pollutant and greenhouse gas (GHS) emissions. Various charging schemes and grid integration techniques are introduced to minimize the impacts of EV charging. Hence, this study introduced a system that uses renewable energy sources (RES) like solar energy, biomass and battery for EV charging.Objective: This study intended to calculate the cost of the system design as well as variations in its cost during the usage on an annual basis. In addition, it used various energy conversion technologies such as solar panel, battery and biomass to find the effective source of energy for EV charging through the proposed novel Optimal Firefly Algorithm (OFA). Methodology: An initial setup is made that consists of number of buildings, overall load demand, ratings of EV charging, storage capacity, grid intake and solar panel. Then, the proposed novel OFA is used to find the count of EVs that gets charged from the charging stations and its choice of charging from the charging stations. The computation is performed on an annual basis for the cost, energy and count of EVs that arrive to the charging stations to get it charged. Results: The proposed methodology is used to compare the efficiency of the solar, biomass and battery efficiency in charging an EV through computation of Net present cost, Cost of Energy, EV savings and power generation. The results revealed that that the proposed system is effective than the traditional methods and effectively identified that the solar energy is the effective source for EV charging.

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