Operation optimization of distributed generation using artificial intelligent techniques

Elkazaz, Mahmoud; Hoballah, Ayman; Azmy, Ahmed M.

doi:10.1016/j.asej.2016.01.008

Cited by 18 publications

(6 citation statements)

References 13 publications

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“…The objective problem formulated as total daily operating cost minimization problem. The target is to minimize the total cost of power generation ( ) from FC systems and generators to supply daily load considering power flow constraints [11], [16]. The cost function includes any costs related to FC systems operation and the cost of purchased power from the grid to supply the all daily loads.…”

Section: Research Methods 21 Objective Function Formulationmentioning

confidence: 99%

Optimal utilization of automated distributed generation in smart grid using genetic algorithm

Hoballah

Ahmad

Shoush³

2019

IJEECS

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<span>Distributed generation (DG) is an essential attributor in smart grid to fulfill the uncontrollable increase in the demand for energy. Artificial intelligent optimization techniques are widely used within automation systems for guarantee the optimal operation and utilization of DG allocation on the day-ahead power scheduling. In this paper, the genetic algorithm technique used for obtaining the optimal utilization of the automated operation of distributed generation for power losses and total cost minimization as well as user comfort maximization considering all operating constraints technique. Distributed generation represented by fuel cells to supply part of the daily demand in the power system. The target is to apply decision-making strategy of smart operation for economical and reliable operation of power system. Concentrated fuel cell units considered representing the available DG at the load centers. The methodology applied to the 11-bus test system. The simulation results have demonstrated that the GA capability for full automation of DGs in a smart manner within the power system for economic and safe operation</span>

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Section: Research Methods 21 Objective Function Formulationmentioning

confidence: 99%

Optimal utilization of automated distributed generation in smart grid using genetic algorithm

Hoballah

Ahmad

Shoush³

2019

IJEECS

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“…the cost of purchased electricity from the main grid), ( 2) Incomes (i.e. considering the revenue of the excess energy sold to the main grid produced by the MG PV and wind generation after satisfying the MG's demand and charging the BESS) [33], (3) Daily operation costs of the BESS. The daily operating cost of the BESS is calculated based on the daily operation scenario of the BESS and also the effect of the BESS degradation [34], [35].…”

Section: Cost Function Formulationmentioning

confidence: 99%

“…The following equations represent the constraints used in this work. The constraints reflect the limits of the generation units within the MG and also define the operating range of the MG [33]. This constraint reflects the max ramp up/down rate for the BESS power output between two consecutive time slots.…”

Section: Battery Energy Storage System Modelmentioning

confidence: 99%

Energy management system for hybrid PV-wind-battery microgrid using convex programming, model predictive and rolling horizon predictive control with experimental validation

Elkazaz

Sumner

Thomas

2020

International Journal of Electrical Power & Energy Systems

129

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The integration of energy storage technologies with renewable energy systems can significantly reduce the operating costs for microgrids (MG) in future electricity networks. This paper presents a novel energy management system (EMS) which can minimize the daily operating cost of a MG and maximize the self-consumption of the RES by determining the best setting for a central battery energy storage system (BESS) based on a defined cost function. This EMS has a two-layer structure. In the upper layer, a Convex Optimization Technique is used to solve the optimization problem and to determine the reference values for the power that should be drawn by the MG from the main grid using a 15 minute sample time. The reference values are then fed to a lower control layer, which uses a 1 minute sample time, to determine the settings for the BESS which then ensures that the MG accurately follows these references. This lower control layer uses a Rolling Horizon Predictive Controller and Model Predictive Controllers to achieve its target. Experimental studies using a laboratory-based MG are implemented to demonstrate the capability of the proposed EMS.

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“…Some examples include: a). Minimization of the total daily operating cost of a group of residential homes [48][49].…”

Section: Optimizationmentioning

confidence: 99%

Smart Review of the Application of Genetic Algorithm in Construction and Housing

Okagbue¹,

Peter²,

Akinola³

et al. 2020

IJATCSE

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Genetic algorithm (GA) is an example of evolutionary algorithms that are bio-inspired computational methods. GA has been applied to numerous fields. It has been applied in different aspects of construction and building but that is scarcely any review that documents it. The paper reviewed the application of GA in construction and building. It was revealed that energy management is the major area of application which are further subdivided into load scheduling, prediction, and optimization. Other nonenergy applications are pricing, environment, and construction design or real estate. The review presents research information to researchers. The information can assist in the optimization of construction processes which can reduce the construction time and costs, ensure optimal allocation and use of energy, prediction of energy demands and supply in houses and incorporation of sustainability in construction and management of real estate.

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Operation optimization of distributed generation using artificial intelligent techniques

Cited by 18 publications

References 13 publications

Optimal utilization of automated distributed generation in smart grid using genetic algorithm

Optimal utilization of automated distributed generation in smart grid using genetic algorithm

Energy management system for hybrid PV-wind-battery microgrid using convex programming, model predictive and rolling horizon predictive control with experimental validation

Smart Review of the Application of Genetic Algorithm in Construction and Housing

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