Continuous access to electricity has become a fundamental demand in the modern world. However, in many countries, the rural areas either have no access to electricity or have access through a weak distribution network with inadequate transmission and distribution infrastructure. On the other hand, higher operational costs, environmental concerns, and challenges pertinent to the fuel management in the systems out of the networks based on gasoline have brought about numerous problems. As a result, making use of alternative energy resources and microgrid systems has captured a great deal of attention. Accordingly, the independent microgrid operators from the network seek appropriate energy management creation to optimize this region's potential to satisfy its energy demands. In this regard, a microgrid containing a photovoltaic generator, diesel generator, wind turbine, and energy storage system has been designed for the Ardabil region in this paper. The installation locations of these systems are selected according to their features. In this microgrid, the energy management has been turned into an optimization problem, and the Extended Artificial Bee Colony Algorithm has been used to solve it. This extended method has been proposed based on the chaos theory and the best response. The obtained results indicate the efficiency of the proposed method.
Energy plays a key role in the modern life of industrial economy, that’s why before the 1970s, the traditional concept of development was centered on economic growth, and countries to increase their economic growth rate, focused more and more on extracting and...
Photovoltaic (PV) solar technology is one of the most promising developments in renewable energy. As the cost of solar panels continues to decrease, it is becoming more accessible and widely used in both urban and rural areas. Using solar energy to power our homes, businesses and communities can help reduce our dependence on fossil fuels and move toward a more sustainable future. This study examines modern technologies used in sustainable buildings, such as beeper systems and the mandatory implementation of photovoltaic systems in advanced countries. The methods of supplying electricity to buildings through photovoltaic systems are also discussed. Storage is a crucial topic in renewable energy and is discussed in the following sections. This study also critically examines the use of phase change materials (PCMs) as heat-absorbing materials in photovoltaic panels and their impact on heating and cooling in the interior of sustainable buildings.
Demand response (DR) is one of the most cost-effective and logical smart grid terms for power systems that can be used during peak load hours, whereas load shedding (LS) is the last and most expensive solution in emergency grid situations. The aim of them is to satisfy equilibrium constraints between consumption and generation and restore the power system frequency to normal bounds at the least possible time. The rapid increase in power grid costs and limitations on electricity generation resources have resulted in the increasing need for industrial customers’ participation as an alternative solution to peak load spikes. Therefore, this paper considers the estimation of imbalance active power in a smart strategy to introduce a critical DR (CDR) in heavy industries (pulp and paper, cement, and medium density fibreboard (MDF)) based on direct load control (DLC) technique in order to reduce the need for LS in frequency restore. To evaluate the proposed model, a real case study including the typical pulp and paper, cement, and MDF industries processes with actual power consumption data is considered. The numerical and graphical results confirm that the proposed CDR can be used as an inexpensive solution to replace the costly spinning reserves and avoid load shedding.
In modern engineering, optimizing energy hub-based microgrids that incorporate renewable energy resources to meet both electrical and thermal demands presents a significant challenge. This study focuses on the stochastic optimization of a multi-carrier energy microgrid, integrating renewable energy sources to enhance efficiency and reduce operational costs. A demand response program is employed to optimize the allocation of costs and improve the load profiles for both electricity and thermal energy. To address the uncertainty of renewable resources, a scenario-based planning approach is implemented to reduce the impact of variability. The model schedules energy production and consumption for a 24-hour period, with objective functions targeting energy purchase costs, fuel costs, profits from energy sales, and greenhouse gas emission reduction. The proposed methodology is tested on a sample microgrid system using Python solvers for optimization. Results, analyzed under various scenarios, show a significant reduction in costs when compared to conventional systems. Specifically, the total cost for meeting electrical and thermal demands through the traditional electricity and gas network is 279,910 cents, while the optimized system reduces the cost to 164,682 cents, yielding a savings of approximately 41%. These findings highlight the effectiveness of the proposed optimization model in reducing both costs and environmental impact.
Demand response (DR) programs are regarded as one of the most reliable and reasonable methods to benefit electricity suppliers and consumers. This paper presents a modified approach to DR based on an Interactive Time-of-Use (ITOU) model by which volunteer industrial customers and their electricity suppliers obtain the best possible performance. Owing to this aim, when studying the region's electrical load profile to determine the peak-hours, the one-year production and sales profile of industrial customers is also studied to select off-peak hours for industrial subscribers. The results of program implementation for the selected and volunteer industrial customers at the sub-transmission level are presented to evaluate the performance of the proposed model. Considering the electricity bills of the subscribers in the program based on reduced energy consumption at peak hours (selected by the utility), and increased energy consumption at the off-peak price (selected by industrial customers), the economic benefits to industrial customers are calculated and verified. Plotting new load curves confirms load shifting from the peak to the valley of the load curve. The obtained results of the conventional TOU and ITOU models indicate that the proposed ITOU is more effective in achieving program goals.
Nowadays, the world heavily depends on the use of fossil fuels such as oil and coal, which can be a serious threat to the future of the planet and humanity. Fossil fuel consumption can cause irreversible effects such as air pollution, environmental degradation, and...
The novelty of this paper is very marginal.The discussion is very simple.
