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Flow chart for optimal dispatching of smart hybrid energy system via uncertainty analysis, operating reserve, and hour-ahead and day-ahead forecasting strategies.
Source publication
A smart hybrid energy system (SHES) is presented using a combination of battery, PV systems, and gas/diesel engines. The economic/environmental dispatch optimization algorithm (EEDOA) is employed to minimize the total operating cost or total CO2 emission. In the face of the uncertainty of renewable power generation, the constraints for loss-of-load...
Contexts in source publication
Context 1
... the EEDOA with w = 1 is treated as the economic dispatch optimization problem, and the EEDOA with w = 0 becomes the environmental dispatch optimization problem. Moreover, the optimal dispatching of a smart hybrid energy system via uncertainty analysis, operating reserve, and hour-ahead and day-ahead forecasting strategies described by a flowchart are shown in Figure 5. ...
Context 2
... order to meet the real-time daily load demand, the economic/environmental power dispatch strategies for the grid-connected and islanded modes of SHES by solving EEDOA are shown in Figure 6a,c and Figure 7a,c, respectively. ies 2023, 16, Figure 5. Flow chart for optimal dispatching of smart hybrid energy system via uncertainty analysis, operating reserve, and hour-ahead and day-ahead forecasting strategies. ...
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Citations
... This independence can be achieved, on the one hand, through the management of endogenous fossil resources, such as coal, oil or natural gas, but also, from the perspective of decarbonizing energy production, by the use of renewable energy sources [2,3]. This balance between using (or even replacing) fossil energy forms with renewable alternatives allows countries like Portugal, which do not have their own coal, oil and natural gas resources, to reduce their trade balance with third countries by decreasing imports of energy products [4][5][6]. On the contrary, the utilization of plentifully accessible internal resources such as favorable solar exposure, ample winds, and even the existence of watercourses with energy generation potential (although this possibility is hindered by some unpredictability and intermittency caused by the changing weather conditions) enables Portugal to secure an escalating proportion inclined towards the use of renewable energy sources [7]. ...
... The landscape of the traditional distribution grid is rapidly changing with the increasing penetration of distributed energy resources (DERs) such as PVs and energy storage (ES) units. Although the addition of DER units presents several benefits, such as the reduction of fossil-fuel-based energy usage, and more potential benefits, such as improved grid resiliency, the current grid infrastructure is not equipped to deal with the stochastic nature and the bidirectional power flow in feeders associated with the high penetration of such units [1][2][3]. Therefore, more research is necessary regarding the high penetration of DER-based distribution feeders to fulfill their potential. ...
In this paper, genetic algorithm (GA)-based voltage optimization of a modified IEEE-34 node distribution feeder with high penetration of distributed energy resources (DERs) is proposed using two megawatt-scale reactive power sources. Traditional voltage support units present in distribution grids are not suitable for DER-rich feeders, while voltage support using small-scale DERs present in the feeder requires considerable communication effort to reach a global solution. In this work, two megawatt-scale units are placed to improve the voltage profile across the IEEE 34-node feeder, which has been modified to include several PV units and an energy storage unit. The megawatt-scale units are optimized using GA for fast and accurate operation. The performance of the proposed scheme is verified using simulation results with a multi-platform setup where the modified IEEE-34 node feeder is modeled in OpenDSS while the GA optimization scheme is programmed in MATLAB.
