scholarly journals A Combinatorial Optimization Approach for the Electrical Energy Management in a Multi-source System

Author(s):  
D. T. Kitamura ◽  
K. P. Rocha ◽  
L. W. Oliveira ◽  
J. G. Oliveira ◽  
B. H. Dias ◽  
...  

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 537
Author(s):  
Rittichai Liemthong ◽  
Chitchai Srithapon ◽  
Prasanta K. Ghosh ◽  
Rongrit Chatthaworn

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.


2012 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
HADI SUROSO ◽  
ONTOSENO PENANGSANG

Optimization in the operation of electric power system is an important task for both inland and onboard. The objective is to minimize operating cost index. Taking advantage of thescheme that onboard operator has the authority not only in the supply side but also in the demandside, an optimization approach toward onboard energy management systems based onintegrated model for supply and demand side is being developed. The model utilizes unit commitmentand economic dispatch in the supply side and load management based on multipleattribute decision-making in the demand side. As a part of the whole concept, this paper focuseson the modeling and simulation of demand side. A user friendly demand side model consistingof Unit Commitment and Economic Dispatch is developed by using LabVIEW, LaboratoryVirtual Instrument Engineering Workbench. Data taken from 3 units of Steam Power Plantare simulated. It is then eventually confirmed that 9% total cost saving can be achieved in theselected load demand range


2009 ◽  
Vol 20 (3) ◽  
pp. 14-21 ◽  
Author(s):  
Afua Mohamed ◽  
Mohamed Tariq Khan

A review of electrical energy management tech-niques on the supply side and demand side is pre-sented. The paper suggests that direct load control, interruptible load control, and time of use (TOU) are the main load management techniques used on the supply side (SS). The supply side authorities normally design these techniques and implement them on demand side consumers. Load manage-ment (LM) initiated on the demand side leads to valley filling and peak clipping. Power factor correc-tion (PFC) techniques have also been analysed and presented. It has been observed that many power utilities, especially in developing countries, have neither developed nor implemented DSM for their electrical energy management. This paper proposes that the existing PFC techniques should be re-eval-uated especially when loads are nonlinear. It also recommends automatic demand control methods to be used on the demand side in order to acquire optimal energy consumption. This would lead to improved reliability of the supply side and thereby reducing environmental degradation.


2016 ◽  
Vol 20 (4) ◽  
pp. 1091-1103 ◽  
Author(s):  
Marina Barbaric ◽  
Drazen Loncar

The increasing energy production from variable renewable energy sources such as wind and solar has resulted in several challenges related to the system reliability and efficiency. In order to ensure the supply-demand balance under the conditions of higher variability the micro-grid concept of active distribution networks arising as a promising one. However, to achieve all the potential benefits that micro-gird concept offer, it is important to determine optimal operating strategies for micro-grids. The present paper compares three energy management strategies, aimed at ensuring economical micro-grid operation, to find a compromise between the complexity of strategy and its efficiency. The first strategy combines optimization technique and an additional rule while the second strategy is based on the pure optimization approach. The third strategy uses model based predictive control scheme to take into account uncertainties in renewable generation and energy consumption. In order to compare the strategies with respect to cost effectiveness, a residential micro-grid comprising photovoltaic modules, thermal energy storage system, thermal loads, electrical loads as well as combined heat and power plant, is considered.


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