Abstract
Integrating renewable energy sources (RESs) into electrical power systems has gotten highly noticeable among researchers and those interested in electrical energy production due to the increase in energy demands, fossil fuel exhaustion, and ecological effects. PV-based renewable energy generation is one of the essential RESs that has appeared and had played a vital role in electrical power systems recently due to their advantages. In this regard, this paper presents a multi-objective computation problem for optimal siting and the design of grid-tied PV systems to achieve optimum generating reliability, considering some states of different generation probabilities. The proposed paper studies the evaluation of the grid-tied PV systems reliability, the states of generation probabilities, the generation buses availabilities, the capacities of the generation's system in or out of service for each failure state, and the frequency and mean duration of generation failure states. The presented multi-objective computation problem is optimized using a modified adaptive accelerated particle swarm optimization (MAACPSO) algorithm. The effectiveness of the proposed method is demonstrated through IEEE_EPS_24_bus integrated with PV systems. Results revealed the ability of MAACPSO to solve the multi-objective optimization problem presented, consequently supporting the system reliability.
Highlights
Renewable energies have many economic and environmental advantages, which has led to an increase in researchers’ interests in studying these types of energies
This study focused on the probability analysis and reliability assessment of the components of grid-tied PV systems through IEEE 24 system with four different models; each has a different number of PV systems
Three combined algorithms were utilized in the proposed method, and these algorithms are the block diagram technique, Markov process technique, and the modified adaptive accelerated particle swarm optimization (MAACPSO) optimization algorithm
Summary
Renewable energies have many economic and environmental advantages, which has led to an increase in researchers’ interests in studying these types of energies. Ballireddy and Modi [11], presented a hybrid optimization technique to assess the reliability indices of power systems by installing wind farms and using ant lion optimization technique and Monte Caro simulation. Another study about minimizing the power losses in grid-connected RESs considering reliability improvement with an optimal sitting of some RESs was presented in [13], [14]. As the load demand grows over time, the generation units should be increased so that the LOLP/LOLE does not exceed the required criterion [29] These factors listed before for the reliability investigation and optimum design of grid-tied RESs, besides the non-linearities in the system components and uncertainties, make this multi-objective optimization problem is difficult to be handled by linear programming techniques [30]. This multi-objective optimization problem is performed by combining three techniques, block diagrams technique MCT, and MAACPSO
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