scholarly journals Energy Management Strategy in Dynamic Distribution Network Reconfiguration considering Renewable Energy Resources and Storage

2020 ◽  
Author(s):  
Ali Azizivahed ◽  
Ali Arefi ◽  
Sahand Ghavidel ◽  
Miadreza Shafie-khah ◽  
Li Li ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Management Strategy ◽  
Distribution Network ◽  
Energy Resources ◽  
Network Reconfiguration ◽  
Renewable Energy Resources ◽  
Energy Management Strategy ◽  
Dynamic Distribution ◽  
And Storage

Value of Distribution Network Reconfiguration in Presence of Renewable Energy Resources

2016 ◽  
Vol 31 (3) ◽  
pp. 1879-1888 ◽  
Author(s):  
Mohammad Reza Dorostkar-Ghamsari ◽  
Mahmud Fotuhi-Firuzabad ◽  
Matti Lehtonen ◽  
Amir Safdarian
Keyword(s):  
Renewable Energy ◽  
Distribution Network ◽  
Energy Resources ◽  
Network Reconfiguration ◽  
Renewable Energy Resources ◽  
Distribution Network Reconfiguration

scholarly journals Multi-Objective Energy Management of a Micro-Grid Considering Stochastic Nature of Load and Renewable Energy Resources

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 403
Author(s):  
Deyaa Ahmed ◽  
Mohamed Ebeed ◽  
Abdelfatah Ali ◽  
Ali S. Alghamdi ◽  
Salah Kamel
Keyword(s):  
Renewable Energy ◽  
Objective Function ◽  
Energy Management ◽  
Energy Resources ◽  
Management Problem ◽  
Renewable Energy Resources ◽  
Multi Objective ◽  
Stochastic Nature ◽  
Whale Optimization ◽  
Micro Grid

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.

scholarly journals Home Energy Management Strategy-Based Meta-Heuristic Optimization for Electrical Energy Cost Minimization Considering TOU Tariffs

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 537
Author(s):  
Rittichai Liemthong ◽  
Chitchai Srithapon ◽  
Prasanta K. Ghosh ◽  
Rongrit Chatthaworn
Keyword(s):  
Energy Management ◽  
Energy Cost ◽  
Management Strategy ◽  
Cost Minimization ◽  
Distribution Network ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Heuristic Optimization ◽  
Energy Management Strategy ◽  
Home Energy Management

It is well documented that both solar photovoltaic (PV) systems and electric vehicles (EVs) positively impact the global environment. However, the integration of high PV resources into distribution networks creates new challenges because of the uncertainty of PV power generation. Additionally, high power consumption during many EV charging operations at a certain time of the day can be stressful for the distribution network. Stresses on the distribution network influence higher electricity tariffs, which negatively impact consumers. Therefore, a home energy management system is one of the solutions to control electricity consumption to reduce electrical energy costs. In this paper, a meta-heuristic-based optimization of a home energy management strategy is presented with the goal of electrical energy cost minimization for the consumer under the time-of-use (TOU) tariffs. The proposed strategy manages the operations of the plug-in electric vehicle (PEV) and the energy storage system (ESS) charging and discharging in a home. The meta-heuristic optimization, namely a genetic algorithm (GA), was applied to the home energy management strategy for minimizing the daily electrical energy cost for the consumer through optimal scheduling of ESS and PEV operations. To confirm the effectiveness of the proposed methodology, the load profile of a household in Udonthani, Thailand, and the TOU tariffs of the provincial electricity authority (PEA) of Thailand were applied in the simulation. The simulation results show that the proposed strategy with GA optimization provides the minimum daily or net electrical energy cost for the consumer. The daily electrical energy cost for the consumer is equal to 0.3847 USD when the methodology without GA optimization is used, whereas the electrical energy cost is equal to 0.3577 USD when the proposed methodology with GA optimization is used. Therefore, the proposed optimal home energy management strategy with GA optimization can decrease the daily electrical energy cost for the consumer up to 7.0185% compared to the electrical energy cost obtained from the methodology without GA optimization.

Energy Optimization and Power Stack Shed Reduction of Oil Depots by using Renewable Energy Resources

2021 ◽  
Vol 4 (2) ◽  
pp. 125-130
Author(s):  
Muhammad Azhar Mahmood ◽  
Muhammad Kamran Liaqat Bhatti ◽  
S. Raza ◽  
M. Riaz
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Energy Management ◽  
Unit Cost ◽  
Research Work ◽  
Energy Resource ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Oil Sector ◽  
Continuous Power

Most of the industries including the oil sector are looking forward towards the renewable energy resources with proper energy management system (EMS) as it is the need of time. For this purpose, solar and wind energy are the renewable energy resources, which are obtained from natural resources and produce clean and environment -friendly electrical energy and can be used for oil depots. The proper utilization of solar and wind energy from natural resource may result in economical and cost-effective EMS. In the proposed research work, an effective energy management demonstration is delivered to ensure the ceaseless flexibility of power. Furthermore, reduction of production per unit cost to the oil sector industry by utilizing multiple objectives streamlining. In the proposed oil depot, connected loads are divided into Shiftable and Non-Shiftable loads and then apply Branch and Bound Algorithm (BnB) with binary integer linear programming (BILP). By using the BnB technique, selected shiftable loads are shifted to the low cost energy resource automatically and resultantly, we get the low price unit cost and continuous power supply. Simulation results for the above-mentioned research work are performed on MATLAB. The proposed technique helps to reduce the power stack shedding issue as well.

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