Computational Intelligence Approaches for Energy Optimization in Microgrids

The future electrical system termed as smart grid represents a significant paradigm shift for power industry. Nowadays, microgrids are becoming smarter with the integration of renewable energy resources (RESs) , diesel generators , energy storage systems (ESS), and plug-in electric vehicles (PEV or EV) . However, these integration bring with new challenges for intelligent management systems. The classical power generation approaches can no longer be applied to a microgrid with unpredictable renewable energy resources. To relive these problem, a proper power system optimization and a suitable coordination strategy are needed to balance the supply and demand. This thesis presents three projects to study the optimization and control for smart community and to investigate the strategic impact and the energy trading techniques for interconnected microgrids. The first goal of this thesis is to propose a new game-theoretic framework to study the optimization and decision making of multi-players in the distributed power system. The proposed game theoretic special concept-rational reaction set (RRS) is capable to model the game of the distributed energy providers and the large residential consumers. Meanwhile, the residential consumers are able to participate in the retail electricity market to control the market price. Case studies are conducted to validate the system framework using the proposed game theoretic method. The simulation results show the effectiveness and the accuracy of the proposed strategic framework for obtaining the optimum profits for players participating in this market. The second goal of the thesis is to study a distributed convex optimization framework for energy trading of interconnected microgrids to improve the reliability of system operation. In this work, a distributed energy trading approach for interconnected operation of islanded microgrids is studied. Specifically, the system includes several islanded microgrids that can trade energy in a given topology. A distributed iterative deep cut ellipsoid (DCE) algorithm is implemented with limited information exchange. This approach will address the scalability issue and also secure local information on cost functions. During the iterative process, the information exchange among interconnected microgrids is restricted to electricity prices and expected trading energy. Numerical results are presented in terms of the convergent rate of the algorithm for different topologies, and the performance of the DCE algorithm is compared with sub-gradient algorithm. The third goal of this thesis is to use proper optimization approaches to motivate the household consumers to either shift their loads from peaking periods or reduce their consumption. Genetic algorithm (GA) and dynamic programming (DP) based smart appliance scheduling schemes and time-of-use pricing are investigated for comparative studies with demand response

Indefinite causal order enables perfect quantum communication with zero capacity channel

Quantum mechanics is compatible with scenarios where the relative order between two events is indefinite. Here we show that two instances of a noisy process, used in a superposition of two alternative orders, can behave as a perfect quantum communication channel. This phenomenon occurs even if the original processes have zero capacity to transmit quantum information. In contrast, perfect quantum communication does not occur when the message is sent along a superposition of paths, with independent noise processes acting on each path. The possibility of perfect quantum communication through noisy channels highlights a fundamental difference between the superposition of orders in time and the superposition of paths in space.Comment: 5+9 pages (minor modifications

Quantum Nonlocality: Multi-copy Resource Inter-convertibility & Their Asymptotic Inequivalence

Quantum nonlocality, pioneered in Bell's seminal work and subsequently verified through a series of experiments, has drawn substantial attention due to its practical applications in various protocols. Evaluating and comparing the extent of nonlocality within distinct quantum correlations holds significant practical relevance. Within the resource theoretic framework this can be achieved by assessing the inter-conversion rate among different nonlocal correlations under free local operations and shared randomness. In this study we, however, present instances of quantum nonlocal correlations that are incomparable in the strongest sense. Specifically, when starting with an arbitrary many copies of one nonlocal correlation, it becomes impossible to obtain even a single copy of the other correlation, and this incomparability holds in both directions. Remarkably, these incomparable quantum correlations can be obtained even in the simplest Bell scenario, which involves two parties, each having two dichotomic measurements setups. Notably, there exist an uncountable number of such incomparable correlations. Our result challenges the notion of a 'unique gold coin', often referred to as the 'maximally resourceful state', within the framework of the resource theory of quantum nonlocality, which has nontrivial implications in the study of nonlocality distillation.Comment: 4+2 pages and 2 figures. Comments are welcom

Effect of osmolytes and chaperone-like action of p-protein on folding of nucleocapsid protein of Chandipura virus

Amino acid sequences of nucleocapsid proteins are mostly conserved among different rhabdoviruses. The protein plays a common functional role in different RNA viruses by enwrapping the viral genomic RNA in an RNase-resistant form. Upon expression of the nucleocapsid protein alone in COS cells and in bacteria, it forms large insoluble aggregates. In this work, we have reported for the first time the full-length cloning of the N gene of Chandipura virus and its expression in Escherichia coli in a soluble monomeric form and purification using nonionic detergents. The biological activity of the soluble recombinant protein has been tested, and it was found to possess efficient RNA-binding ability. The state of aggregation of the recombinant protein was monitored using light scattering. In the absence of nonionic detergents, it formed large aggregates. Aggregation was significantly reduced in the presence of osmolytes such asd-sorbitol. Aggregate formation was suppressed in the presence of another viral product, phosphoprotein P, in a chaperone-like manner. Both the osmolyte and phosphoprotein P also suppressed aggregation to a great extent during refolding from a guanidine hydrochloride-denatured form. The function of the phosphoprotein and osmolyte appears to be synergistic to keep the N-protein in a soluble biologically competent form in virus-infected cells

Spatial wavefront shaping with a multipolar-resonant metasurface for structured illumination microscopy

Structured illumination microscopy (SIM) achieves superresolution in fluorescence imaging through patterned illumination and computational image reconstruction, yet current methods require bulky, costly modulation optics and high-precision optical alignment. This work demonstrates how nano-optical metasurfaces, rationally designed to tailor the optical wavefront at sub-wavelength dimensions, hold great potential as ultrathin, single-surface, all-optical wavefront modulators for SIM. We computationally demonstrate this principle with a multipolar-resonant metasurface composed of silicon nanostructures which generate versatile optical wavefronts in the far field upon variation of the polarization or angle of incident light. Algorithmic optimization is performed to identify the seven most suitable illumination patterns for SIM generated by the metasurface based on three key criteria. We find that multipolar-resonant metasurface SIM (mrm-SIM) achieves resolution comparable to conventional methods by applying the seven optimal metasurface-generated wavefronts to simulated fluorescent objects and reconstructing the objects using proximal gradient descent. The work presented here paves the way for a metasurface-enabled experimental simplification of structured illumination microscopy.Comment: TR and PTB contributed equally to this wor

Local Inaccessibility of Random Classical Information : Conditional Nonlocality demands Entanglement

Discrimination of quantum states under local operations and classical communication (LOCC) is an intriguing question in the context of local retrieval of classical information, encoded in the multipartite quantum systems. All the local quantum state discrimination premises, considered so far, mimic a basic communication set-up, where the spatially separated decoding devices are independent of any additional input. Here, exploring a generalized communication scenario we introduce a framework for input-dependent local quantum state discrimination, which we call local random authentication (LRA). Referring to the term nonlocality, often used to indicate the impossibility of local state discrimination, we coin the term conditional nonlocality for the impossibility associated with the task LRA. We report that conditional nonlocality necessitates the presence of entangled states in the ensemble, a feature absent from erstwhile nonlocality arguments based on local state discrimination. Conversely, all the states in a complete basis set being entangled implies conditional nonlocality. However, the impossibility of LRA also exhibits more conditional nonlocality with less entanglement. The relation between the possibility of LRA and local state discrimination for sets of multipartite quantum states, both in the perfect and conclusive cases, has also been established. The results highlight a completely new aspect of the interplay between the security of information in a network and quantum entanglement under the LOCC paradigm.Comment: An appropriate example for Proposition 2 is added and the details of which is supplemented in the Appendi