نشریه سیستم های انرژی پایدار
سال یکم شماره 3 (تابستان 1401)

Archimedes screw turbines are a novel type of small hydroelectric power plant that can be used in low-altitude locations. The Archimedes screw turbine is a clean and renewable energy source and is safer for wildlife and especially aquatic life than other hydroelectric generation options. In addition to other sources of energy, the turbine is not a definitive and comprehensive solution. However, it can have many economic, social and environmental benefits. This makes this device an effective option for sustaining hydropower development. Archimedes screw turbines can produce up to 355 kW of power at low water heads (less than about 5 meters) and a range of flow rates with a practical efficiency of 60% to 80%. This device can be operated in remote areas and small communities. Therefore, it increases the potential for the sustainable development of hydropower. In many low-head situations, the Archimedes screw turbine is more cost-effective than alternative hydroelectric systems with less installation and operating costs. Also, disturbances in sedimentation and natural erosion processes and the performance of wildlife, especially aquatic animals, are associated with a significant decrease. Archimedes screw turbines can be operated at the lowest flow rate in the majority of chain power plants and outside the power generation network. This article examines the characteristics of the Archimedes screw turbine and examines its operation methods and its features and disadvantages.

Load forecasting is one of the most important aspects of the effective management of power systems and depends on various factors such as the means and sources of electricity production by each company, electric load demand, weather factors, economic factors and human activities.. The main goal of this article is the STLF in the regional electricity grid of Guilan province. In this research, after collecting data including wind speed, relative humidity, temperature, dew point, holidays, day length and the effect of corona disease, pre-processing is done on them and they are divided into five clusters using K_Means clustering algorithm. In the following, the relationships between the independent and dependent variables of electricity consumption in Guilan province, using linear regression (LR) algorithms, artificial neural network (ANN) and support vector regression (SVR) along with the Grid search optimization method, were investigated and analyzed in Python software and modeled in the Google Colab environment. The results show that the SVR algorithm has higher accuracy and longer implementation time than the two algorithms of ANN and LR.

Integrated demand response effectively promotes the use of renewable energy sources and improves energy efficiency in systems with multiple energy carriers. This paper proposes a resilient scheduling model for local energy systems based on electricity, cooling, hydrogen, and water in the presence of electric and hydrogen vehicles. In addition, the role of integrated demand response based on electricity and cooling to reduce the operating cost of the local water-energy system is investigated. The local energy system is equipped with electricity generation sources, a water desalination device, wind turbine, water, electricity, cooling, and hydrogen storage systems, an electricity to hydrogen conversion unit, and an electric chiller to simultaneously meet water and energy demands. To model the uncertainty of wind power generation, a robust optimization approach is used without the need for probability density function and scenario generation, which supports the optimal scheduling of the water-energy system against changes in wind power generation. It also enables the operator to apply a risk-averse approach. Numerical results show that using integrated demand response besides water-energy storage systems reduces the total operating cost of the local system by 5.6%.

Global economic development requires increasing water demand for various purposes. Wastewater treatment in these processes leads to an increase in the volume of sewage sludge. However, a significant amount of renewable energy can be recovered from sludge from wastewater treatment. Biomass is one of the energy sources that has the potential of sustainable replacement for fossil fuels, a significant part of which consists of municipal and industrial wastewater. Anaerobic digestion is used as a strategy to generate energy and biogas from municipal waste and sewage. In this study, the energy production potential of wastewater treatment plants in Khorramabad city has been investigated and evaluated using preliminary data (including BOD) on wastewater treatment performance over one year (2021). The results show that annually 2261728 cubic meters of biogas can be produced using the anaerobic digestion method. Using the combined heat and power system can generate 24879008 MW of thermal energy and 476.34 kWh of electricity. Also, the economic evaluation of the system shows that the annual investment costs and operating costs will be 103251697000 and 14620633 Rials, respectively. On the other hand, the refinery can save 44689938600 Rials annually by saving natural gas consumption, selling fertilizer produced, and selling electricity generated to the network. The rate of return on economic capital for implementing this plan is calculated for 3 years and 6 months. In addition to economic justification, implementing this plan will be able to prevent greenhouse gas emissions significantly.

Currently, the development of energy modeling on an urban scale is the goal of many types of research. These energy models are useful for understanding the amount of energy consumption. This research presents a dynamic energy modeling based on energy balance. Building specifications are taken from urban data. This model has been calibrated, optimized, and validated by considering Ardabil's climatic conditions and morphological parameters. The results of this work show that this model can be used with reasonable accuracy for old buildings. These data need to be improved for urban-scale analysis of new buildings. Based on field and statistical research conducted in Ardabil, Iran, which is the main focus of this report, this city's energy consumption during the past years can be achieved. The basis of this work is through statistics and the implementation of heat transfer equations in the form of electrical modeling. This modeling is done in MATLAB / Simulink software. The model is then optimized after simulation.

Usually, geothermal resources have some surface manifestations. However, there are some resources without any surface evidences of geothermal activity. According to the recent studies, it is believed that in some parts of the earth this type of natural resources is more abundant than the known geothermal resources. These resources are called blind geothermal resources. The main reasons which prevent formation of surface manifestations are very thick cap rock, heavy rainfall in tropical regions, specific structural settings of the region, very deep water table and lateral underground flow of geothermal fluid to the ocean/sea. As blind resources have not any surface manifestations so some individual exploration methods are needed to find them. These methods are divided to two different levels, preliminary and detailed levels. Both of them include geological, geochemical and geophysical studies. In preliminary studies the size of the study area is very large (more than 10,000 km2) and the main target is to find geothermal prospects. In contrast, in detailed studies scientists search for precise characteristics of a given geothermal prospect. So far, the reasonable amount of blind geothermal resources has been determined in western part of the USA especially in Nevada State.