An enhanced jellyfish search optimizer for stochastic energy management of multi-microgrids with wind turbines, biomass and PV generation systems considering uncertainty
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This study presents an enhanced Jellyfish Search Optimizer (EJSO) for multi-microgrid energy management. EJSO significantly reduces costs and improves system performance, offering a powerful solution for renewable energy integration.
Area Of Science
- Electrical Engineering
- Optimization Algorithms
- Renewable Energy Systems
Background
- Energy management (EM) in multi-microgrids (MMGs) is vital for flexibility and reliability.
- High renewable energy penetration complicates MMG energy management due to resource variability and load fluctuations.
Purpose Of The Study
- To solve the complex energy management problem in MMGs with integrated photovoltaic (PV) systems, wind turbines (WTs), and biomass.
- To minimize total cost and enhance system performance concurrently using an optimized approach.
Main Methods
- Proposed an enhanced Jellyfish Search Optimizer (EJSO) for MMG energy management.
- EJSO incorporates Weibull Flight Motion (WFM) and Fitness Distance Balance (FDB) to overcome stagnation issues.
- Validated EJSO performance on standard and CEC 2019 benchmark functions and compared it with other optimization techniques.
Main Results
- EJSO demonstrated superior performance in solving the MMG energy management problem compared to Sand Cat Swarm Optimization (SCSO), Dandelion Optimizer (DO), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Jellyfish Search Optimizer (JSO).
- The proposed EJSO solution reduced costs by 44.75%.
- System voltage profile and stability were enhanced by 40.8% and 10.56%, respectively.
Conclusions
- EJSO is a powerful and effective method for multi-microgrid energy management, especially with high renewable energy penetration.
- The algorithm offers significant economic benefits and substantial improvements in system voltage profile and stability.
- EJSO provides a robust solution for optimizing complex energy systems.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Based on Bernoulli's equation, the energy line (EL) and hydraulic grade line (HGL) provide graphical representations of energy distribution in a fluid flow system. For steady, incompressible, inviscid flows, Bernoulli's equation is expressed as:
Here, H is the total head, p/γ is the pressure head, V2/2g is the velocity head, and z is the elevation head.
The energy line (EL) represents the total head available in the flow. It is located above the datum and includes all three energy...
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
Open channel flow, where a fluid flows with a free surface exposed to the atmosphere, is primarily governed by gravitational and surface effects, distinguishing it from closed conduit or pipe flow. In open channels such as rivers, canals, and artificial channels, energy analysis provides valuable insights into flow behavior and the relationship between depth, velocity, and slope.Specific Energy and Flow DepthIn open channel flow, the specific energy, E, combines the gravitational potential...
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
For a lossless line, simplifications streamline the calculation of real...
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Since N is dimensionless and the unit of f(v) is seconds per meter, the equation can be conveniently modified into a...