Hierarchical Demand Response for Peak Reduction using Dantzig‐Wolfe Decomposition

Demand Response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralised agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus it is desirable to use a scalable decentralised algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for Peak Minimisation (PM) based on Dantzig-Wolfe Decomposition (DWD). In addition, a Time Weighted Maximisation option is included in the cost function which improves the Quality of Service for devices seeking to receive their desired energy sooner rather than later. The paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

Interactions between ectomycorrhizal fungi and soil saprotrophs:Implications for decomposition of organic matter in soils and degradation of organic pollutants in the rhizosphere

Ectomycorrhizal fungi and saprotrophic microorganisms coexist and interact in the mycorrhizosphere. We review what is known regarding these interactions and how they may influence processes such as ectomycorrhiza formation, mycelial growth, and the dynamics of carbon movement to and within the rhizosphere. Particular emphasis is placed on the potential importance of interactions in decomposition of soil organic matter and degradation of persistant organic pollutants in soil. While our knowledge is currently fairly limited, it seems likely that interactions have profound effects on mycorrhizosphere processes. More extensive research is warranted to provide novel insights into mycorrhizosphere ecology and to explore the potential for manipulating the ectomycorrhizosphere environment for biotechnological purposes.

A further investigation of the kinetic demixing/decomposition of La0.6Sr0.4Co0.2Fe0.8O3- δ oxygen separation membranes

Kinetic demixing and decomposition were studied on three La_0.6Sr_0.4Co_0.2Fe_0.8O_{3- δ} oxygen-separation hollow fibre membrane modules, which were operated under a 0.21/0.009bar oxygen partial pressure difference at 950°C for 1128, 3672 and 5512h, respectively. The post-operation membranes were characterized by Secondary Ion Mass Spectrometry, Scanning Electronic Microscope, Energy Dispersive Spectrum and X-ray Diffraction. The occurrence of kinetic demixing and decomposition was confirmed through the microstructural evolution of the membranes. Secondary-phase grains were found on the air-side surface of the membranes after the long-term operation and Co and Fe enrichment as well as La depletion was found on the surface and in the bulk at the air side. Cation diffusivities were found to be in the order Co>Fe>Sr>La. Kinetic demixing and decomposition rates of the membranes at the air side were found to be self-accelerating with time; the role of A-site deficiency in the perovskite lattice in the bulk near the air side surface is implicated in the mechanism. The oxygen permeability was not affected by the kinetic demixing and decomposition of the material during long-term operation (up to 5512h), however, we may expect permeability to be affected by secondary phase formation on the air-side surface at even longer operational times. © 2010 Elsevier B.V.

A constructive approach for examination timetabling based on adaptive decomposition and ordering

In this study, we investigate an adaptive decomposition and ordering strategy that automatically divides examinations into difficult and easy sets for constructing an examination timetable. The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set in the construction process. Moreover, the examinations within each set are ordered using different strategies based on graph colouring heuristics. Initially, the examinations are placed into the easy set. During the construction process, examinations that cannot be scheduled are identified as the ones causing infeasibility and are moved forward in the difficult set to ensure earlier assignment in subsequent attempts. On the other hand, the examinations that can be scheduled remain in the easy set.

Within the easy set, a new subset called the boundary set is introduced to accommodate shuffling strategies to change the given ordering of examinations. The proposed approach, which incorporates different ordering and shuffling strategies, is explored on the Carter benchmark problems. The empirical results show that the performance of our algorithm is broadly comparable to existing constructive approaches.

Simultaneous cellulose conversion and hydrogen production assisted by cellulose decomposition under UV-light photocatalysis

Photocatalytic conversion of cellulose to sugars and carbon dioxide with simultaneous production of hydrogen assisted by cellulose decomposition under UV or solar light irradiation was achieved upon immobilization of cellulose onto a TiO2 photocatalyst. This approach enables production of hydrogen from water without using valuable sacrificial agents, and provides the possibility for recovering sugars as liquid fuels.

Hierarchical Demand Response for Peak Minimization Using Dantzig-Wolfe Decomposition

Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.