Lighting is a fundamental requirement of our daily life. A lot of research and development is carried out in the field of daylight harvesting, which is the need of the hour. One of the most desirable attributes of daylight harvesting is that daylight is available universally and it is a very clean and cost-efficient form of energy. By using the various methods of daylight harvesting, it is possible to attain the global Sustainable Development Goals. Daylight harvesting in the most fundamental sense is the lighting strategy control of the artificial light in an interior space where daylight is also present so that the required illumination level is achieved. This way, a lot of energy can be saved. Recently, in addition to energy efficiency, other factors such as cost-efficiency, user requirements such as uniform illuminance, and different levels of illuminance at different points are being considered. To simulate the actual daylight contribution for an office building in urban Chennai, India before construction, ECO TECH software is used by providing the inputs such as building orientation, and reflectance’s values of the ceiling, wall, and floor to analyze the overall percentage of daylight penetration available versus the percentage prescribed in the Indian Green Building Council to obtain the credit points. Thus, the impact of architectural design on daylight harvesting and daylight predictive technology has experimented with office building in Chennai, India. This article will give an insight into the current trends in daylight harvesting technology and intends to provide a deeper understanding and spark a research interest in this widely potential field.
In recent decades, Renewable Energy Sources (RES) have become more attractive due to the depleting fossil fuel resources and environmental issues such as global warming due to emissions from fossil fuel-based power plants. However, the intermittent nature of RES may cause a power imbalance between the generation and the demand. The power imbalance is overcome with the help of Distributed Generators (DG), storage devices, and RES. The aggregation of DGs, storage devices, and controllable loads that form a single virtual entity is called a Virtual Power Plant (VPP). In this article, the optimal scheduling of DGs in a VPP is done to minimize the generation cost. The optimal scheduling of power is done by exchanging the power between the utility grid and the VPP with the help of storage devices based on the bidding price. In this work, the state of charge (SOC) of the batteries is also considered, which is a limiting factor for charging and discharging of the batteries. This improves the lifetime of the batteries and their performance. Energy management of VPP using the teaching-and-learning-based optimization algorithm (TLBO) is proposed to minimize the total operating cost of VPP for 24 hours of the day. The power loss in the VPP is also considered in this work. The proposed methodology is validated for the IEEE 16-bus and IEEE 33-bus test systems for four different cases. The results are compared with other evolutionary algorithms, like Artificial Bee Colony (ABC) algorithm and Ant Lion Optimization (ALO) algorithm.
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