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Hydropower plants play an integral role in energy supply and are one of the main renewable energy sources. The efficiency of hydropower reservoir systems is controlled by operating rules that need to be optimized to maximize energy production. Here, a novel optimization algorithm, influential flower pollination algorithm (IFPA), is developed in this paper. IFPA has three enhancements: an efficient exploration mechanism based on an adaptive coefficient, a new exploitation mechanism around the best solution, and a rank-based strategy to smoothly transition from exploration to exploitation. IFPA is tested in two benchmark multi-reservoir systems and a real-world five-reservoir hydropower system in Iran. The results show IFPA outperforms other advanced methods in terms of convergence speed and preciseness to achieve the global solution. The tested algorithms include adaptive guided differential evolution (AGDE), composite DE (CODE), hybridizing sum-local search optimizer (HSLSO), improved teaching learning-based optimization (ITLBO), self-adapting control parameters in DE (jDE), self-adaptive TLBO (SATLBO), and a multi-strategy hybrid of DE and particle swarm optimization (MS-DEPSO). IFPA also achieved better total power production in the real-world case study compared to other algorithms. Overall, IFPA can provide better solutions with less power deficit and shows as a promising method for optimizing hydropower reservoir problems. [ABSTRACT FROM AUTHOR]

Using hybrid renewable energy systems is a smart choice for reducing the carbon emitted by power plants. It also helps climate change mitigation and global warming, leading to universal health for humans and the environment. The efficiency of these systems depends on choosing the right combination of renewable sources, their sizes, and proper scheduling of the generating units. This paper suggests an optimisation method for sizing a geothermal/PV/wind/diesel system, both in off-grid and grid-connected configurations. In the grid-connected mode, the possibility of selling surplus energy generated by renewable resources to the network is considered. Investigations reveal that without accurate control of geothermal reservoirs, they may become depleted. In this study, a strategy is suggested for unit commitment; moreover, the harmony search algorithm is used to find the optimal size of the hybrid system in both configurations. The effectiveness of the proposed approach is represented by simulating an HRES for Ferdows/Iran. [ABSTRACT FROM AUTHOR]

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is 77.8 MW. Economic analysis is performed for the obtained results and it was observed that construction of this type of power plants will not be attractive for private sector investors with the market energy prices (i.e. 8 cents/kW h).The effect of the future development in power density of membrane and membrane unit price in economic feasibility of the osmotic power plant is studied. [ABSTRACT FROM AUTHOR]

Geothermal heat sources are promising renewable resources of energy. In this paper, a novel ammonia-water power cycle was designed considering the geothermal resources in Iran. This cycle was analyzed and the effects of ammonia fraction and boiler pressure on its performance were investigated. At the first, Sabalan geothermal field with temperature of 456K was studied. For this geothermal source, the effects of various ammonia fractions were perused in the boiler pressure of 25 bar. The results showed that the ammonia concentration of 0.855 led to the best performance. Also, investigating the boiler pressure at the constant concentration (0.855) indicated that the maximum efficiency happened at 35 bar. Based on genetic algorithm, the simultaneous effects of various concentrations and pressures on the performance of the ammonia-water cycle were surveyed and the optimum values were found for Sabalan source. So that, at the source temperature of 456K, the optimum concentration and pressure were obtained 0.85 and 36 bar, respectively. Finally, the optimum conditions for several geothermal source temperatures were presented within a table. Moreover, at the same sources, the presented optimized cycle was compared with other cycles in the literatures. The results indicated that the presented cycle at optimum conditions had higher efficiency. • Introducing an improved ammonia-water cycle in order to power generation by geothermal resource. • Energy and exergy analyses of the proposed cycle in details. • Optimizing ammonia concentration and boiler pressure in various temperatures of geothermal sources by genetic algorithm (GA). [ABSTRACT FROM AUTHOR]