Ali Reza Reisi

Bio: Ali Reza Reisi is an academic researcher from Bu-Ali Sina University. The author has contributed to research in topics: Maximum power principle & Maximum power point tracking. The author has an hindex of 4, co-authored 5 publications receiving 646 citations. Previous affiliations of Ali Reza Reisi include Islamic Azad University.

Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

Abstract: In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

An Optimal Collaborative Congestion Management Based on Implementing DR

Abstract: To alleviate congestions of grids is one of the most important managerial performance indicators in the electricity market. The role of retail electricity providers (REPs) can be effective in alleviating such congestions. However, little effort has been devoted for involving REPs collaboratively in congestion alleviation. This paper addresses this shortfall in the literature. It proposes an innovative solution for the congestion problem through reinforcing a collaboration between the independent system operators (ISOs) and REPs in implementing demand response (DR) programs. The idea of economic signaling, conveyed by the ISO to REPs, is employed to assist REPs in trading with DR aggregators. Stackelberg game theory is adopted for designing such trade in the market. The effectiveness of the proposed method is evaluated using a test power system. This paper demonstrates an effective performance for the proposed method. By providing a novel game theory solution for the congestion problem based on involving REPs in the DR program, a contribution is made to the current practice of grid congestion management. This paper outcomes will be of particular interest when the grid faces the highest possible demand particularly during the hot season.

An optimal collaborative congestion management in national grid based on implementing demand response

Abstract: This paper aims to provide a novel framework for optimal congestion management via encouraging a collaboration between the independent system operator (ISO) and Retail electricity companies (Recos) in implementing demand response (DR) programs based on the market mechanism. The merit of this paper is to increase the market efficiency. Three economic signals, namely, demand reduction, congestion elasticity, and electricity spot price values, specified by the ISO, are used for assisting Recos in evaluating any benefits from implementing DR in various network buses. A Stackelberg game is adopted for designing a DR trade between Recos and demand response aggregators to help Recos identifying their optimal demands in the market, which are then used by the ISO to analyze grid congestion and consequently to re-specify the new economic signals. The game is repeated until the Nash equilibrium point, the optimal congestion reduction, and the optimal Recos' demands are obtained. The performance of the proposed frame...

Foundations and Challenges of Low-Inertia Systems (Invited Paper)

Abstract: The electric power system is currently undergoing a period of unprecedented changes. Environmental and sustainability concerns lead to replacement of a significant share of conventional fossil fuel-based power plants with renewable energy resources. This transition involves the major challenge of substituting synchronous machines and their well-known dynamics and controllers with power electronics-interfaced generation whose regulation and interaction with the rest of the system is yet to be fully understood. In this article, we review the challenges of such low-inertia power systems, and survey the solutions that have been put forward thus far. We strive to concisely summarize the laid-out scientific foundations as well as the practical experiences of industrial and academic demonstration projects. We touch upon the topics of power system stability, modeling, and control, and we particularly focus on the role of frequency, inertia, as well as control of power converters and from the demand-side.

Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

Abstract: In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

Tackling Climate Change with Machine Learning

Abstract: Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.

A comprehensive review on solar PV maximum power point tracking techniques

Abstract: In recent years solar energy has received worldwide attention in the field of renewable energy systems Among the various research thrusts in solar PV, the most proverbial area is extracting maximum power from solar PV system Application dof Maximum Power Point Tracking (MPPT) for extracting maximum power is very much appreciated and holds the key in developing efficient solar PV system In this paper, a state of the art review on various maximum power point techniques for solar PV systems covering timeworn conventional methods and latest soft computing algorithms is presented To date critical analysis on each of the method in terms of (1) tracking speed, (2) algorithm complexity, (3) Dynamic tracking under partial shading and (4) hardware implementation is not been carried out In this regard the authors have attempted to compile a comprehensive review on various solar PV MPPT techniques based on the above criteria Further, it is envisaged that the information presented in this review paper will be a valuable gathering of information for practicing engineers as well as for new researchers