This paper presents the optimal planning of renewable hybrid systems including wind turbines and bio-waste energy units according to hydrogen and thermal storages considering feeding of electrical and thermal energies. Bio-waste unit is based on the operation of the combined power and heat system, which produces electrical and thermal energy at the same time. Hydrogen storage is hybrid of an electrolyze, hydrogen tank, and fuel cell. The proposed scheme minimizes the total annual investment and maintenance costs. It is subject to the operation model of the mentioned elements. In the operation model of sources and storage, renewable sources supply loads of energy, then storage uses to cover the gap between the load and renewable power profiles. This paper uses the hybrid solver of the Gray wolf optimizer and the sine-cosine algorithm to obtain a reliable optimal solution with a low standard deviation in the final response. Finally, based on numerical results according to Espoo in Finland data, the proposed scheme's capability is confirmed in the Economic extraction of a 100% renewable island hybrid system suitable for simultaneous supply of electrical and thermal energy.

The energy demand is growing daily due to the growing population, rising electricity consumption, and widespread usage of advanced equipment. The environmental damage caused by fossil fuels and their economic and political implications in countries worldwide has prompted a quest for alternative energy sources. One of the key advantages of renewable energy sources is their ability to combine with other energy sources to create hybrid renewable energy systems. Hybrid renewable systems are devices that utilize more than one energy generation source to fulfill the required electrical and thermal loads. In this study, a hybrid renewable energy system has been designed for the Faculty of Engineering of Golestan University located in Gorgan City, utilizing Homer software. This system, which includes solar panels, wind turbines, diesel generators and grid power integration, fulfills the energy needs of the facility. Additionally, heating needs are supplied using a boiler and heat controller. The results indicate that the optimized system has a total current cost of $214,266, with a cost of energy production per kilowatt-hour amounting to 0.0159 $ and the renewable resource contribution is 71.7%. Moreover, the sensitivity analysis reveals that when the inflation rate surges to 20%, the current cost of the whole project ascends to 16 %.

This paper presents the planning of a hybrid system with wind turbines and biomass energy sources, and batteries and electric vehicles parking lot. The proposed scheme minimizes the total costs of construction and maintenance for sources and storage and the degradation cost of storage. It is subject to the operating model of sources, storage, and power electronic converters. To provide clean energy, the priority of supplying the energy demand is given to renewable sources, and then the storages cover the distance between the load profile and the generation power of the sources. Furthermore, the proposed scheme has uncertainties regarding the load, renewable power, and energy consumption of mobile storage devices. In this paper, scenario-based stochastic planning is adopted to model the mentioned parameters. The combined algorithm of Ant lion optimization and Krill Herd optimization extracts a reliable optimal solution with low dispersion in the final response. Finally, the obtained numerical results demonstrate the capability of the proposed scheme in deriving economic planning for the proposed hybrid system, in which the presence of renewable resources leads to the extraction of an environmentally-friendly hybrid system, and the energy management of mobile storage devices reduces the planning cost of the hybrid system by 1.9% compared with a case with their absence.

The increasing population and rising demand for water and energy supply, along with the exacerbation of environmental pollution effects on natural and human resources, demonstrate the vital need for a cohesive movement toward the water, energy, and environment Nexus (WEEN). Since the electricity generation industry has a significant share in water and fuel consumption and CO2 emissions in Iran, in this study, the application of a combined renewable system in the Zarand Steam Power Plant was evaluated based on the Nexus approach. Solar system designing and carbon balance evaluation during plant lifetime was conducted via PVSyst software in 2021. Also, an environmental model of ReCipe was applied to evaluate the effect of carbon reduction on the ecosystem. The results have shown that replacement of at least 1% of the nominal capacity of the fossil power plant with renewable sources, will significantly prevent 1249/46 t CO2 emission annually in this power plant which is equivalent to 362/160 m3 fossil resources storage and 373/73 TOE.year-1 energy savings. Also, the results showed that in addition to protecting valuable natural resources, the combined cycle will lead to a significant reduction in water demand equivalent to 3660 m3 having the capacity of supplying underground water resources. Considering the benefits of saving water and energy resources and reducing carbon emissions, from the NEXUS approach, in addition to managing energy supply through replacing resources and using water and heat recovery technologies, applying energy demand management policies based on energy efficiency and its environmental effects is suggested..

In this research, a hybrid renewable system based on the use of solar and oceanic thermal energy to produce power and hydrogen by using a flat plate solar collector was investigated from a thermodynamic and economic point of view. The objective functions investigated in this research were exergy efficiency and cost rate. Collector mass flow rate, collector area, turbine inlet temperature, and solar radiation intensity were considered as four decision variables, and the effect of these parameters on system performance and system exergy loss was investigated. The optimization of objective functions was done by the Nelder-Mead method. From single-objective optimization, it was concluded that the best system exergy efficiency rate is 7.31% and the system cost rate is 27.48 $/hour in the optimal state. From the sensitivity analysis, it was concluded that increasing the parameters of the collector area, solar radiation intensity, and turbine inlet temperature had a positive effect on the system performance, and increasing the mass flow rate parameter of the solar collector had a negative effect on the system performance. Also, from the analysis of the exergy loss of the system, it was concluded that the increase in the intensity of solar radiation, the area of the collector, and the mass flow rate of the collector increase the overall exergy loss of the system, but the increase in the inlet temperature to the turbine decreases the exergy loss of the system.

In recent years, the tendency to use renewable energy resources in remote areas has been raised due largely to increase in the energy demand and fossil fuel costs. In this paper, the aim is to find the optimal number of components of the off-grid hybrid PV/wind/battery/diesel system, in the presence of the load and renewable power generation uncertainty. Optimization is based on minimizing the value of the annualized cost of system, which meets the requirements of the desired loss of power supply probability (LPSP).Three various optimization algorithms including PSO, CPSO, and Modified PSO are proposed to solve the optimization problem. To exam the efficiency of the proposed model and optimization strategies, the proposed approach has been applied to a stand-alone hybrid energy system in Sistan and Bluchestan, Iran. Furthermore, the effect of different desired LPSP and optimization algorithms on the economic operation have been discussed. The results demonstrate that the MPSO has a faster solution and better performance than the PSO and CPSO. In this paper, while previous research has mainly focused on theoretical results only, for practical implementation, the maximum allowed constraint for diesel fuel consumption is added to the optimization algorithm and practical implementation has been done based on the simulation results and actual data.

In this paper, the optimal planning of renewable energy systems including the wind turbine photovoltaic solar panels and energy storage systems has been done for a sample garrison considering the weather condition’s uncertainty. The target case study is Tatavar1 garrison which has been located in Kermanshah province of Iran. Utilizing renewable based energy system for providing the energy demand of areas which are far from main grid is a suitable and practical suggestion. Consideration of uncertainty of energy production of these systems during the optimization studies affords more comprehensive and more practical results. The simulation results show that the using of renewable based energy systems caused considerable reduction of energy cost. Simulation results indicate that for case study of Tatavar 1, using the renewable energy system decrease the consumption of gasoil fuel about 87% and total cost up to 81% during the 5 years of optimization period, beside the eliminating the whole of load shedding hours.

Using of modern energy systems is the one of ways for supplying energy in hard transition zones. In this investigation, a technical-economic feasibility study on energy production systems from renewable sources was done for three hard transition rural areas including Pichbon, Narmellat and Dinehroud, located in the eastern Alamut, Qazvin. Among different renewable energy production systems, solar and biogas systems were selected based on the rural areas potential. Technical calculation reveals that Pichbon, Narmellat and Dinehroud require 1200, 150 and 1000 Photovoltaic (PV) panels, respectively. The gas produce from animal waste, in these rural areas, are 145008, 62000 and 50000 m3, respectively. According to economic calculations, a hybrid PV-biogas system was chosen as the most viable economic, with payback period equal to 5.5 years and internal rate of return equal to 16.13 percent.

Recently, with growth in utilization of renewable resources engineers and researchers have been motivated to offer new methods for their application in distribution networks. In this regard, optimal sitting and sizing of renewable resources as two main parameters in designing distribution network can reduce loss, operation costs and voltage deviations. In this paper, a multi-objective evolutionary algorithm based on fuzzy methods has been proposed for sitting and sizing of renewable resources. The provided algorithm minimizes economic, environmental and technical objective functions on 70-bus distribution test system. The results show that with optimal sitting and sizing of renewable resources in different scenarios costs, pollution and loss can be reduced significantly.