An Accurate Optimal Sizing Method of a Hybrid PV/Wind Energy Conversion System with Battery Storage

2020 ◽  
Vol 48 ◽  
pp. 179-192 ◽  
Author(s):  
Ahmed Souissi
Keyword(s):  
Power Supply ◽  
Meteorological Data ◽  
Optimal Solution ◽  
Computation Time ◽  
Battery Storage ◽  
Optimal Sizing ◽  
Good Convergence ◽  
Wind Energy Conversion ◽  
Load Demand ◽  
Feasible Solutions

The present paper gives an accurate iterative methodology for optimal sizing of a hybrid photovoltaic/wind system with battery storage, using the concept of the loss of power supply probability and the total net present cost. In the first part, the optimum combinations that can meet the load demand while respecting the desired loss of power supply probability level are determinate, following two steps: First, all feasible solutions are determinate. Second, each feasible solution is optimized iteratively.In the second part, the optimal solution which has the lowest net present cost is selected based on an economical study. Lastly, the proposed and adopted methodology is verified and discussed with the meteorological data of the area of Hawaria (Tunisia) to prove its fast computation time and good convergence accuracy.

scholarly journals A Linear Relaxation-Based Heuristic for Iron Ore Stockyard Energy Planning

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5232
Author(s):  
Marcos Wagner Jesus Servare Junior ◽  
Helder Roberto de Oliveira Rocha ◽  
José Leandro Félix Salles ◽  
Sylvain Perron
Keyword(s):  
Energy Cost ◽  
Average Distance ◽  
Optimal Solution ◽  
Computation Time ◽  
Electrical Energy ◽  
Linear Relaxation ◽  
Mixed Integer ◽  
Management Decision ◽  
Management Decision Making ◽  
Feasible Solutions

Planning the use of electrical energy in a bulk stockyard is a strategic issue due to its impact on efficiency and responsiveness of these systems. Empirical planning becomes more complex when the energy cost changes over time. The mathematical models currently studied in the literature consider many actors involved, such as equipment, sources, blends, and flows. Each paper presents different combinations of actors, creating their own transportation flows, thus increasing the complexity of this problem. In this work, we propose a new mixed integer linear programming (MILP) model for stockyard planning solved by a linear relaxation-based heuristic (LRBH) to minimize the plan’s energy cost. The proposed algorithm will allow the planner to find a solution that saves energy costs with an efficient process. The numerical results show a comparison between the exact and heuristic solutions for some different instances sizes. The linear relaxation approach can provide feasible solutions with a 3.99% average distance of the objective function in relation to the optimal solution (GAP) in the tested instances and with an affordable computation time in instances where the MILP was not able to provide a solution. The model is feasible for small and medium-sized instances, and the heuristic proposes a solution to larger problems to aid in management decision making.

Time Series Model of Wind Power Forecasting Error by using Beta Distribution for Optimal Sizing of Battery Storage

2019 ◽  
Vol 139 (3) ◽  
pp. 212-224
Author(s):  
Xiaowei Dui ◽  
Masakazu Ito ◽  
Yu Fujimoto ◽  
Yasuhiro Hayashi ◽  
Guiping Zhu ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Power ◽  
Beta Distribution ◽  
Time Series Model ◽  
Battery Storage ◽  
Wind Power Forecasting ◽  
Optimal Sizing ◽  
Forecasting Error ◽  
Power Forecasting

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations

Energy ◽  
2021 ◽  
pp. 122545
Author(s):  
Čedomir Zeljković ◽  
Predrag Mršić ◽  
Bojan Erceg ◽  
Đorđe Lekić ◽  
Nemanja Kitić ◽  
...  
Keyword(s):  
Power Supply ◽  
Base Stations ◽  
Mobile Telephony ◽  
Optimal Sizing ◽  
Battery Power

Towards Intelligent Road Traffic Management over Weighted Large Graphs Hybrid Meta-heuristic-Based Approach

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Traffic Management ◽  
Large Scale ◽  
Road Traffic ◽  
Optimization Technique ◽  
Shortest Paths ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Computation Time ◽  
Exact Algorithm ◽  
On The Road

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Hybrid Photovoltaic-Diesel Energy System Optimization (Case Study of Electric Power Supply for Buildings under the Weather Conditions of Montenegro)

2014 ◽  
Vol 627 ◽  
pp. 357-364 ◽  
Author(s):  
Goran Radovic ◽  
Vera Murgul ◽  
Nikolai Vatin ◽  
Ekaterina Aronova
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Power Supply ◽  
Optimal Solution ◽  
Weather Conditions ◽  
System Optimization ◽  
Energy System ◽  
Energy Performance ◽  
Electric Power Supply ◽  
Continuous Power

The article deals with the concept of solar photovoltaic systems use in power supply systems. An analysis of local solar resources potential has been carried out, and optimal orientation points of radiant heat absorbing photovoltaic panels have been chosen to achieve maximum energy performance. Simulation of electric power systems having different configurations has been implemented using the software program Homer. It has been stated that a combination of solar and diesel energy systems is considered to be an optimal solution under the weather conditions of Montenegro. The systems working together make it possible to reduce maintenance costs significantly and adjust capacity generation schedule with due account for energy consumption features to a maximum extent. This allows generating electric power at less cost and results in a more reliable and continuous power supply without failures for a consumer chosen.

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