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| Ref. | Year | EC approach | Problem (optimization) | Characteristics |
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| [90] | 2015 | Hybrid algorithm: differential evolution combined with particle swarm optimization (DEPSO). | Maximum power point tracking (MPPT) techniques for PV applications. | Simulation and hardware implementation of DEPSO for MPPT. |
| [91] | 2015 | Hybrid algorithm: ant colony optimization combined with artificial bee colony (ACO-ABC). | Optimal location and sizing of distributed energy resources. | Multiobjective optimization. Objectives: minimization of power losses, total emissions, total electrical energy cost, and improvement of voltage stability. |
| [96] | 2015 | Brainstorm optimization algorithm (BSOA). | Optimal location and setting of flexible AC transmission system (FACTS) devices. | Discrete, multiobjective, multimodal, and constrained optimization. BSOA is compared with PSO, GA, DE, SA, hybrid of genetic algorithm and pattern search (GA-PS), backtracking search algorithm (BSA), gravitational search algorithm (GSA), and asexual reproduction optimization (ARO). |
| [92] | 2016 | Multistep approach: cuckoo search (CS) algorithm, fuzzy system (FS), weather research and forecasting (WRF), and ensemble forecast (CS-FS-WRF-E). | Forecasting of wind speed. | CS optimization is used to construct the final model adjusting and correcting the results obtained based on physical laws. The final model yields to best forecasting performance and outperforming all the other models used for comparison. |
| [97] | 2016 | Chaotic bat algorithm (CBA). | Economic dispatch problem (EDP). | Consideration of equality and inequality constraints (e.g., such as power balance, prohibited operating zones, and ramp rate limits). Also, transmission losses and multiple fuel options are taken into account. |
| [94] | 2016 | Second version of the nondominated sorting genetic algorithm (NSGA-II). | Optimization of solar driven Stirling heat engine with regenerative heat losses. | Multiobjective optimization. Objectives: power output, overall thermal efficiency, and thermo-economic function. A selection of the best solution in the Pareto front by Fuzzy Bellman-Zadeh, Shannon’s entropy, LINMAP, and TOPSIS is also implemented. |
| [98] | 2017 | Differential evolution (DE). | Optimization of combined cooling, heating, and power-based compressed air energy storage. | Multiobjective optimization. Objectives: maximization of system exergy efficiency and minimization of total product unit cost. |
| [93] | 2017 | Genetic algorithm (GA). | Optimal size of microgrid components. Unit commitment problem (UCP). | Leader-follower problem. The leader problem focuses on sizing. The follower problem, that is, the energy management issue, is solved with a mixed-integer linear program. |
| [99] | 2017 | Multiobjective quantum-behaved particle swarm optimization (MOQPSO). | Economic environmental hydrothermal scheduling problem. | Multiobjective, nonlinear, and constrained optimization. A constraint handling method is designed to adjust the constraint violation of hydro and thermal plants. |
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