30 publications from this institution
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...
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.
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...
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.
The development of industry and the increasing of the energy demand in the today’s power system make it possible to maximize the potential of existing and renewable energy resources. On the other hand, using of these resources required efficient management and planning model, because without the adequate energy management, the power system cannot reach a high-performance model with maximum efficiency. Therefore, this paper first addresses the modeling of energy management in smart buildings having responsive/non-responsive devices and renewable photovoltaic resources. To manage the solar system employment, the KNX protocol is used. Also, the batteries are used in a way that they are charged at low power consumption and it will be as a generating unit during the peak-load time, therefore, the objective function is minimizing the power system loss and the related cost. Since the proposed model is nonlinear and has some complexity, the particle swarm algorithm (PSO) is used. To achieve the minimum losses, the best candidate buses are selected based on the proposed sensitivity analysis to manage the connected buildings. As a result, the function of the overall cost is based on the amount of energy produced and sold. Finally, the presented model is examined and evaluated on modified IEEE 30-bus test system based on the statistical analysis in different scenarios. Moreover, it is conclude from the planning that the operating cost significantly controls by the charge and discharge mechanism of the battery and the photovoltaic units.
Profit maximization for electricity companies strongly depends on the tender strategies. To trade electricity at a high price and make the most of profits, electricity companies require suitable and optimal price offer models that take into account the operational constraints of electricity and price uncertainty in the market. Nowadays, the electricity industry is mostly inclined towards creating a competitive structure for increasing its productivity as well as technical and managerial efficiency. Here, the optimal distribution of the auction offers by the companies in the fully competitive electricity market is converted into an optimization problem and solved by the developed gray wolf optimizer (GWO) algorithm based on chaos theory. In a competitive electricity market, to increase the profit of the players in the market, the auction offers should be properly selected, because each player intends to increase its own profit. Of course, each of the players can change their level of offers without disrupting the customers' welfare. This problem is even more important for large manufacturing companies and large loads because a considerable share of the market is allocated to them. Results of this method are compared with those of other evolutionary methods and indicate the suitable efficiency of the proposed method.
The novelty of this paper is very marginal.The discussion is very simple.
