Bio: MuhammadHamza Waseem is an academic researcher from University of Engineering and Technology, Lahore. The author has contributed to research in topics: Stand-alone power system & Smart grid. The author has an hindex of 1, co-authored 1 publications receiving 13 citations.
02 Mar 2017
TL;DR: In this paper, the design and control of a micro-grid, including various alternative energy resources (photovoltaic and wind) and battery energy storage system which operates in stand-alone as well as in grid-connected mode, is discussed.
Abstract: This paper deals with the design and control of a micro-grid, including various alternative energy resources (photovoltaic and wind) and battery energy storage system which operates in stand-alone as well as in grid-connected mode. The proposed micro-grid is controlled via various non-isolated converters while an energy management is performed through switching based algorithm. According to the strategy, the wind is used as the primary power source while the Photovoltaic (PV) is added to improve the reliability of system under different weather conditions. The battery module is utilized as an energy storage system during surplus power and/or backup device during demand. The proposed system used real record of weather pattern and load conditions for a small community at Islamabad, Pakistan. This city is gifted with several natural resources that can generate a significant amount of power energy for the region. MATLAB simulation results show the effectiveness of proposed system in terms of grid stability, power sharing, load tracking and power quality.
TL;DR: The classification and review of architectures of Hybrid Renewable Energy Systems is presented and the energy management strategies for optimal flows of electrical energy between individual systems of considered hybrid renewable energy system are developed and described.
Abstract: The aim of the paper is the study of the Hybrid Renewable Energy System, which is consisted of two types of renewable energy systems (wind and sun) and is combined with storage energy system (battery). The paper presents the classification and review of architectures of Hybrid Renewable Energy Systems. The considered Hybrid Renewable Energy System was designed as a multi-converter system with gearless Wind Turbine driven Permanent Magnet Synchronous Generator and with a Photovoltaic Array and Battery Energy System. The mathematical models of individual elements of a complex Hybrid Renewable Energy System were described. In the control of both systems of Wind Turbine with Permanent Magnet Synchronous Generator and Photovoltaic array, the algorithms of Maximum Power Point Tracking have been implemented for higher efficiency of energy conversion. The energy storage in the battery has been managed by the control system of a bidirectional DC/DC converter. For the control of the Machine Side Converter and Wind Turbine with Permanent Magnet Synchronous Generator, the vector control method has been implemented. In the control system of the Grid Side Converter, the advanced method of Direct Power Control has been applied. The energy management strategies for optimal flows of electrical energy between individual systems of considered hybrid renewable energy system are developed and described. In order to determine the operation of proposed control systems, the simulation studies have been performed for different conditions of operation of individual elements of the complex hybrid system. The considered control methods and energy management strategies were tested thorough simulation studies for different wind speed variations, different sun irradiations, and different local load demands. The performed simulations are of practical importance in terms of proper operation requirements, design selection of components and energy management of Hybrid Renewable Energy Systems.
TL;DR: An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system and results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.
Abstract: With constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may prove to be economical in the long run. However, the intermittent character of renewable energy sources is a major disadvantage. It is important to integrate them with the rest of the grid so that their benefits can be reaped while their negative impacts can be mitigated. In this article, an energy management algorithm is recommended for a grid-connected microgrid consisting of loads, a photovoltaic (PV) system and a battery for efficient use of energy. A model predictive control-inspired approach for energy management is developed using the PV power and consumption estimation obtained from daylight solar irradiation and temperature estimation of the same area. An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system. The proposed system is compared with a rule-based control strategy. Results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.
TL;DR: In this article, the authors presented a detailed analysis of a hybrid renewable energy system used for standalone operation, which consists of a wind-driven synchronous generator, a photovoltaic solar system, and a battery storage system.
Abstract: The current study aims to present a detailed analysis of a hybrid renewable energy system used for standalone operation. The hybrid system consists of a wind-driven synchronous generator, a photovoltaic solar system, and a battery storage system. The modeling of each system component is presented and described in detail. To achieve optimal energy exploitation, the maximum power point tracking algorithm is adopted. The management of synchronous generator operation is achieved through controlling the machine-side converter using a newly formulated predictive control scheme. To visualize the advantages of the proposed control algorithm, its performance is compared with the other two traditional predictive control approaches, mainly the model predictive direct power control and model predictive direct torque control systems. An effective control scheme is also adopted to manage the power storage in the battery using a bi-directional DC/DC converter. To maintain a balanced power flow between the system units, an energy management strategy is presented. Extensive tests are carried out to evaluate the performance of the hybrid system considering variable wind speed, variable sun irradiation, and variable load profiles. The obtained results for the synchronous generator performance visualize the validity and superiority of the proposed control scheme over the other two classic controllers. The results are also validating the effectiveness of the battery storage control system and confirming the validity of the constructed energy management strategy in achieving the energy balance between the system units.
TL;DR: In this article, a case study of an isolated microgrid with intermittent renewable energy sources is presented, where the sizing, operation and control of a suitable energy storage method for a case-study MG system is presented.
Abstract: Energy storage has an effective role on establishing isolated microgrids (MGs) that contain intermittent renewable energy sources. Energy storages depending upon their technologies can ensure stable and reliable operation, control, and resiliency of the MGs. Therefore, it is indispensable to study MGs operation using appropriate, cost effective and sustainable energy storages along with necessary control. In this paper, sizing, operation and control of a suitable energy storage method for a case study MG system is presented. Due to the excellent geographical location of the case study MG system, a pumped hydro storage is selected; and the sizing of this storage unit is provided using mathematical models that is based on the system physical dimension. In addition, governor-excitation control based on power-frequency droop is designed for the pumped hydro storage unit. The controller performance is tested under various load changes in the MG and the results are presented to show the effectiveness of the designed controller. The performance of the MG frequency and the voltage at the MG bus under load disturbances indicate that the proposed pumped hydro storage is capable to maintain stable operation of the study MG system. Sizing outcomes and performance analysis of the designed controller have been carried out using MATLAB/Simulink software package.
••03 Mar 2018
TL;DR: Simulations show that the H-11 grid is a good option for the integration of DREG and improves the voltage profile, reduce feeder losses and increases the reliability of the system by providing power near the consumer at the distribution level.
Abstract: There is an energy crisis in Pakistan due to the gap between demand and supply of electrical energy. This gap between demand and supply of electrical energy is hampering its economic development. In order to overcome this issue there is a need to increase the generation capacity of the country by integrating renewable energy resources in the system. In this paper the working and functioning of H-11 grid system is tested using the power world simulator software. First the grid system is modeled by incorporating the values of the power transformers and the transmission system of the grid. When the grid system is simulated the grid is tested for the four different scenarios of the Distributed Renewable Energy Generation integration. Our simulations show that Distributed Renewable Energy Generation (DREG) improves the voltage profile, reduce feeder losses and increases the reliability of the system by providing power near the consumer at the distribution level. Simulation shows that the optimal placement of DREG is at bus no 7, in case of 1MW (25% of the total feeder load). Simulation results and the comparative analysis of the respective DREG integration show that the H-11 grid is a good option for the integration of DREG.