Poverty in terms of conventional energy but abundant renewable energy resources coincide in solar-rich areas, so the on-site supply of solar energy is essential for alleviating energy poverty and decarbonizing buildin...
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Poverty in terms of conventional energy but abundant renewable energy resources coincide in solar-rich areas, so the on-site supply of solar energy is essential for alleviating energy poverty and decarbonizing buildings. We propose a novel energy structure based on a solar-driven energy system combining battery and thermal storage under the power-to-heat concept. Dual-objective optimization models were developed for PV-PT hybrid system and PV-dominant system to identify the optimal technological portfolio and design parameters with the aim of minimizing both the annual total cost (ATC) and carbon emission intensity (CEI), and the models were solved using the biologically-inspired algorithms. Considering a rural household in Lhasa as an example, the optimum design consists of 1.7 kW of photovoltaic (PV), 28.2 m2 of photothermal (PT), 4.8 kWh of battery, 1.7 m3 of thermal storage, and 3.2 kW of auxiliary heat source. The ATC is 44.5 % lower than that using conventional energy and CEI can be reduced by 94.8 %. Furthermore, the proposed system could achieve a CO2 reduction cost of 0.3 CNY & sdot;kg-1, compared with the two PV-dominant systems, i.e., 2.8 and 0.5 CNY & sdot;kg- 1 CO2, respectively. The proposed methodology can identify the optimal technology portfolio and balance environmental with economic.
In systems of active programmable matter, individual modules require a constant supply of energy to participate in the system's collective behavior. These systems are often powered by an external energy source acc...
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ISBN:
(纸本)9781450389334
In systems of active programmable matter, individual modules require a constant supply of energy to participate in the system's collective behavior. These systems are often powered by an external energy source accessible by at least one module and rely on module-to-module power transfer to distribute energy throughout the system. While much effort has gone into addressing challenging aspects of power management in programmable matter hardware, algorithmic theory for programmable matter has largely ignored the impact of energy usage and distribution on algorithm feasibility and efficiency. In this work, we present an algorithm for energy distribution in the amoebot model that is loosely inspired by the growth behavior of Bacillus subtilis bacterial biofilms. These bacteria use chemical signaling to communicate their metabolic states and regulate nutrient consumption throughout the biofilm, ensuring that all bacteria receive the nutrients they need. Our algorithm similarly uses communication to inhibit energy usage when there are starving modules, enabling all modules to receive sufficient energy to meet their demands. As a supporting but independent result, we extend the amoebot model's well-established spanning forest primitive so that it self-stabilizes in the presence of crash failures. We conclude by showing how this self-stabilizing primitive can be leveraged to compose our energy distribution algorithm with existing amoebot model algorithms, effectively generalizing previous work to also consider energy constraints.
In recent years, various types of control algorithms have been proposed for cognitive radios (CR), ranging from algorithms coordinated by centralized control to ones coordinated in a distributed manner. These algorith...
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ISBN:
(纸本)9789639799127
In recent years, various types of control algorithms have been proposed for cognitive radios (CR), ranging from algorithms coordinated by centralized control to ones coordinated in a distributed manner. These algorithms, however, all require communication to either peer nodes or a master node, thus creating communication overhead and potential vulnerability. We introduce a new class of control algorithms to the area of CRs derived from observations of emergent design in nature. Specifically, we introduce an algorithmic approach based on swarm behavior to the task of configuration management in CR networks. Without requiring the exchange of information among peers or a central authority, CRs equipped with such an algorithm are able to globally optimize the configuration of a CR network in the presence of interference and jammers, while only relying on local information, thus providing a fast and efficient way for configuration management especially for large networks.
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