Abstract In many large-scale and time-consuming problems, the application of metaheuristics becomes essential, since these methods enable achieving very close solutions to the exact one in a much shorter time. In this work, we address the problem of portfolio optimization applied to electricity markets negotiation. As in a market environment, decision-making is carried out in very short times, the application of the metaheuristics is necessary. This work proposes a Hybrid model, combining a simplified exact resolution of the method, as a means to obtain the initial solution for a Particle Swarm Optimization (PSO) approach. Results show that the presented approach is able to obtain better results in the metaheuristic search process
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...
Power and energy systems are being subject to relevant changes, mostly due to the large increase of ...
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...
DOI:https://doi.org/10.1186/s42162-018-0066-7 In many large-scale and time-consuming problems, t...
This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of o...
Meta-heuristic search methods are used to find near optimal global solutions for difficult optimizat...
Electric power systems have undergone major changes in recent years. Electricity markets are one of ...
Smart Grid technologies enable the intelligent integration and management of distributed energy reso...
Massive changes in electricity markets have occurred during the last years, as a consequence of the ...
The increasing unpredictability of electricity market prices as reflection of the renewable generati...
The deregulation of the electricity sector has culminated in the introduction of competitive markets...
The portfolio optimization is a well-known problem in the areas of economy and finance. This problem...
Energy community markets have emerged to promote prosumers' active participation and empowerment in ...
The electricity markets environment has changed completely with the introduction of renewable energy...
In a liberalized electricity market, participants have several types of contracts to sell or buy ele...
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...
Power and energy systems are being subject to relevant changes, mostly due to the large increase of ...
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...
DOI:https://doi.org/10.1186/s42162-018-0066-7 In many large-scale and time-consuming problems, t...
This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of o...
Meta-heuristic search methods are used to find near optimal global solutions for difficult optimizat...
Electric power systems have undergone major changes in recent years. Electricity markets are one of ...
Smart Grid technologies enable the intelligent integration and management of distributed energy reso...
Massive changes in electricity markets have occurred during the last years, as a consequence of the ...
The increasing unpredictability of electricity market prices as reflection of the renewable generati...
The deregulation of the electricity sector has culminated in the introduction of competitive markets...
The portfolio optimization is a well-known problem in the areas of economy and finance. This problem...
Energy community markets have emerged to promote prosumers' active participation and empowerment in ...
The electricity markets environment has changed completely with the introduction of renewable energy...
In a liberalized electricity market, participants have several types of contracts to sell or buy ele...
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...
Power and energy systems are being subject to relevant changes, mostly due to the large increase of ...
This paper presents a methodology based on genetic Algorithms (GA) to solve the problem of optimal p...