Bio: Muhammad Khalid is an academic researcher from King Fahd University of Petroleum and Minerals. The author has contributed to research in topics: Renewable energy & Wind power. The author has an hindex of 23, co-authored 140 publications receiving 2036 citations. Previous affiliations of Muhammad Khalid include University of Naples Federico II & University of New South Wales.
Papers published on a yearly basis
TL;DR: Two constraint-based iterative search algorithms are proposed for optimal sizing of the wind turbine, solar photovoltaic and the battery energy storage system (BESS) in the grid-connected configuration of a microgrid to avoid over- and under-sizing.
Abstract: Higher cost and stochastic nature of intermittent renewable energy (RE) resources complicate their planning, integration and operation of electric power system. Therefore, it is critical to determine the appropriate sizes of RE sources and associated energy storage for efficient, economic and reliable operation of electric power system. In this study, two constraint-based iterative search algorithms are proposed for optimal sizing of the wind turbine (WT), solar photovoltaic (PV) and the battery energy storage system (BESS) in the grid-connected configuration of a microgrid. The first algorithm, named as sources sizing algorithm, determines the optimal sizes of RE sources while the second algorithm, called as battery sizing algorithm, determines the optimal capacity of BESS. These algorithms are mainly based upon two key essentials, i.e. maximum reliability and minimum cost. The proposed methodology aims to avoid over- and under-sizing by searching every possible solution in the given search space. Moreover, it considers the forced outage rates of PV, WT and utilisation factor of BESS which makes it more realistic. Simulation results depict the effectiveness of the proposed approach.
TL;DR: In this article, a controller based on model predictive control (MPC) is proposed to smooth the wind power output, which is generated from a wind farm, and subject to a variety of constraints on the system model.
Abstract: The aim of this study is to design a controller, based on model predictive control (MPC), to smooth the wind power output, which is generated from a wind farm, and subject to a variety of constraints on the system model. In order to employ the model predictive controller, we propose a wind power prediction system, which is used by the controller within its predictive optimization. The proposed controller is capable of smoothing wind power by utilizing inputs from our prediction system, and optimizes the maximum ramp rate requirement and also the state of the charge of the battery under practical constraints. The proposed prediction model is capable of predicting the wind power several steps ahead which is used in the optimization part of the controller. We illustrate the effectiveness of the proposed controller with a simulation example, employing real wind farm data under a variety of hard constraints.
TL;DR: In this paper, the authors presented a method to improve the short-term wind power prediction at a given turbine using information from numerical weather prediction and from multiple observation points, which correspond to the locations of nearby turbines at a particular wind farm site.
Abstract: This paper presents a method to improve the short-term wind power prediction at a given turbine using information from numerical weather prediction and from multiple observation points, which correspond to the locations of nearby turbines at a particular wind farm site. The prediction of wind power is achieved in two stages; in the first stage wind speed is predicted using our proposed method. In the second stage, the wind speed to output power conversion is accomplished using power curve model. The proposed wind power prediction method is tested using real measurements and NWP data from one of the wind farm sites in Australia. The performance is compared with the persistence and Grey predictor model in terms of Mean Absolute Error and Root Mean Square Error.
TL;DR: A literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy in power systems and the impact of forecasting improvement on optimal power system design and operation is presented.
Abstract: This paper presents a literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy (RE) in power systems. This review is drafted on the basis of the selected high quality research publications from the past decade. Although the development of forecast models for RE generation, i.e., wind and solar energy, is a well-researched area, however, the performance of these models is usually evaluated using statistical error metrics. With regard to application, determining the optimality of accurate forecasts in terms of system economics and major planning aspects is an emerging phenomenon, that chalks out the main subject area of this survey. Specifically, the application domains include: 1) optimal power system dispatch (unit commitment, generation scheduling, economic dispatch), 2) optimal sizing of energy storage system, 3) energy market policies and profit maximization of market participants, 4) reliability assessment, and 5) optimal reserve size determination in power systems. The application-oriented review on these vital areas can be used by the power sector for familiarization with the recent trends and for analyzing the impact of forecasting improvement on optimal power system design and operation.
TL;DR: The proposed scheme follows a decision policy to efficiently sell more energy at peak demand/price times and store it at off-peak periods in compliance with the electricity rules of the Australian National Electricity Market.
Abstract: This paper presents a novel wind farm dispatch control scheme by integrating a battery energy storage system (BESS) to manage the amount of net energy generation sold to the electricity market. The scheme is based on model predictive control to ensure the optimal operation of BESS in the presence of practical system constraints. The proposed scheme follows a decision policy to efficiently sell more energy at peak demand/price times and store it at off-peak periods in compliance with the electricity rules of the Australian National Electricity Market. The performance of the proposed control scheme is assessed under different scenarios in terms of a key performance index and earning comparison from power sale using actual wind farm and electricity price data.
01 Jan 1982
TL;DR: In this article, the authors discuss leading problems linked to energy that the world is now confronting and propose some ideas concerning possible solutions, and conclude that it is necessary to pursue actively the development of coal, natural gas, and nuclear power.
Abstract: This chapter discusses leading problems linked to energy that the world is now confronting and to propose some ideas concerning possible solutions. Oil deserves special attention among all energy sources. Since the beginning of 1981, it has merely been continuing and enhancing the downward movement in consumption and prices caused by excessive rises, especially for light crudes such as those from Africa, and the slowing down of worldwide economic growth. Densely-populated oil-producing countries need to produce to live, to pay for their food and their equipment. If the economic growth of the industrialized countries were to be 4%, even if investment in the rational use of energy were pushed to the limit and the development of nonpetroleum energy sources were also pursued actively, it would be extremely difficult to prevent a sharp rise in prices. It is evident that it is absolutely necessary to pursue actively the development of coal, natural gas, and nuclear power if a physical shortage of energy is not to block economic growth.
TL;DR: Free-living soil bacteria beneficial to plant growth, usually referred to as plant growth promoting rhizobacteria (PGPR), are capable of promoting plant growth by colonizing the plant root and can inhibit phytopathogens.
Abstract: Soil bacteria are very important in biogeochemical cycles and have been used for crop production for decades. Plant–bacterial interactions in the rhizosphere are the determinants of plant health and soil fertility. Free-living soil bacteria beneficial to plant growth, usually referred to as plant growth promoting rhizobacteria (PGPR), are capable of promoting plant growth by colonizing the plant root. PGPR are also termed plant health promoting rhizobacteria (PHPR) or nodule promoting rhizobacteria (NPR). These are associated with the rhizosphere, which is an important soil ecological environment for plant–microbe interactions. Symbiotic nitrogen-fixing bacteria include the cyanobacteria of the genera Rhizobium, Bradyrhizobium, Azorhizobium, Allorhizobium, Sinorhizobium and Mesorhizobium. Free-living nitrogen-fixing bacteria or associative nitrogen fixers, for example bacteria belonging to the species Azospirillum, Enterobacter, Klebsiella and Pseudomonas, have been shown to attach to the root and efficiently colonize root surfaces. PGPR have the potential to contribute to sustainable plant growth promotion. Generally, PGPR function in three different ways: synthesizing particular compounds for the plants, facilitating the uptake of certain nutrients from the soil, and lessening or preventing the plants from diseases. Plant growth promotion and development can be facilitated both directly and indirectly. Indirect plant growth promotion includes the prevention of the deleterious effects of phytopathogenic organisms. This can be achieved by the production of siderophores, i.e. small metal-binding molecules. Biological control of soil-borne plant pathogens and the synthesis of antibiotics have also been reported in several bacterial species. Another mechanism by which PGPR can inhibit phytopathogens is the production of hydrogen cyanide (HCN) and/or fungal cell wall degrading enzymes, e.g., chitinase and s-1,3-glucanase. Direct plant growth promotion includes symbiotic and non-symbiotic PGPR which function through production of plant hormones such as auxins, cytokinins, gibberellins, ethylene and abscisic acid. Production of indole-3-ethanol or indole-3-acetic acid (IAA), the compounds belonging to auxins, have been reported for several bacterial genera. Some PGPR function as a sink for 1-aminocyclopropane-1-carboxylate (ACC), the immediate precursor of ethylene in higher plants, by hydrolyzing it into α-ketobutyrate and ammonia, and in this way promote root growth by lowering indigenous ethylene levels in the micro-rhizo environment. PGPR also help in solubilization of mineral phosphates and other nutrients, enhance resistance to stress, stabilize soil aggregates, and improve soil structure and organic matter content. PGPR retain more soil organic N, and other nutrients in the plant–soil system, thus reducing the need for fertilizer N and P and enhancing release of the nutrients.
TL;DR: Screening approaches and practical applications of PGPR in agriculture are the major focus of this review, with researchers using different approaches for screening rhizobacteria to select effective PGPR.
Abstract: Rhizobacteria that exert beneficial effects on plant growth and development are referred to as plant growth promoting rhizobacteria (PGPR) In recent years, the use of PGPR to promote plant growth has increased in various parts of the world PGPR can affect plant growth by production and release of secondary metabolites (plant growth regulators/phytohormones/biologically active substances), lessening or preventing deleterious effects of phytopathogenic organisms in the rhizosphere and/or facilitating the availability and uptake of certain nutrients from the root environment Selection of effective PGPR is the most critical aspect to have maximum benefits from this technology Researchers are using different approaches for screening rhizobacteria to select effective PGPR including promotion of root/shoot growth under gnotobiotic conditions, in vitro production of plant growth regulators/biologically active substances and assessing of ACC-deaminase activity of the rhizobacteria However, the combined use of two or more approaches for screening of rhizobacteria could be more useful to select effective PGPR These screening approaches and practical applications of PGPR in agriculture are the major focus of this review
TL;DR: In this article, an extensive literature survey on Hybrid Renewable Energy Systems (HRES) and state-of-the-art application of optimization tools and techniques to microgrids, integrating renewable energies is presented.
Abstract: Fast depleting fossil fuels and the growing awareness for environmental protection have led us to the energy crisis. Hence, efforts are being made by researchers to investigate new ways to extract energy from renewable sources. ‘Microgrids’ with Distributed Generators (DG) are being implemented with renewable energy systems. Optimization methods justify the cost of investment of a microgrid by enabling economic and reliable utilization of the resources. This paper strives to bring to light the concept of Hybrid Renewable Energy Systems (HRES) and state of art application of optimization tools and techniques to microgrids, integrating renewable energies. With an extensive literature survey on HRES, a framework of diverse objectives has been outlined for which optimization approaches were applied to empower the microgrid. A review of modelling and applications of renewable energy generation and storage sources is also presented.