Blockchain-Based Water-Energy Transactive Management with Spatial-Temporal Uncertainties

Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-topeer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatialtemporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.</p

Preparation and Characterization of Stimuli-Responsive Magnetic Nanoparticles

In this work, the main attention was focused on the synthesis of stimuli-responsive magnetic nanoparticles (SR-MNPs) and the influence of glutathione concentration on its cleavage efficiency. Magnetic nanoparticles (MNPs) were first modified with activated pyridyldithio. Then, MNPs modified with activated pyridyldithio (MNPs-PDT) were conjugated with 2, 4-diamino-6-mercaptopyrimidine (DMP) to form SR-MNPs via stimuli-responsive disulfide linkage. Fourier transform infrared spectra (FTIR), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) were used to characterize MNPs-PDT. The disulfide linkage can be cleaved by reduced glutathione (GHS). The concentration of glutathione plays an important role in controlling the cleaved efficiency. The optimum concentration of GHS to release DMP is in the millimolar range. These results had provided an important insight into the design of new MNPs for biomedicine applications, such as drug delivery and bio-separation

Design and Analysis of the Measurement Characteristics of a Bidirectional-Decoupling Over-Constrained Six-Dimensional Parallel-Mechanism Force Sensor

The measurement of large forces and the presence of errors due to dimensional coupling are significant challenges for multi-dimensional force sensors. To address these challenges, this paper proposes an over-constrained six-dimensional force sensor based on a parallel mechanism of steel ball structures as a measurement module. The steel ball structure can be subject to rolling friction instead of sliding friction, thus reducing the influence of friction. However, because the structure can only withstand unidirectional pressure, the application of steel balls in a six-dimensional force sensor is difficult. Accordingly, a new design of the sensor measurement structure was designed in this study. The static equilibrium and displacement compatibility equations of the sensor prototype’s over-constrained structure were established to obtain the transformation function, from which the forces in the measurement branches of the proposed sensor were then analytically derived. The sensor’s measurement characteristics were then analysed through numerical examples. Finally, these measurement characteristics were confirmed through calibration and application experiments. The measurement accuracy of the proposed sensor was determined to be 1.28%, with a maximum coupling error of 1.98%, indicating that the proposed sensor successfully overcomes the issues related to steel ball structures and provides sufficient accuracy

Data-driven aggregate thermal dynamic model for buildings: a regression approach

The thermal inertia of buildings brings considerable flexibility to the building heating and cooling loads, which is believed to be a promising demand response resource in energy systems. However, it is challenging to utilize the thermal inertia of buildings in the operation of energy systems because of the complicated thermal dynamics and high computational cost. This paper proposes a data-driven aggregate thermal dynamic model (ATDM) for the multi-zone building and building cluster, respectively, which offers an equivalent and low-complexity building model for the operation and control of energy systems. The ATDM consists of the aggregation equation and the state equation. The former projects the detailed real states of buildings into the characteristic state (i.e., aggregate state) using an affine function, and the latter describes the thermal dynamics of buildings using the aggregate state. The ATDM is formulated for two practical load control strategies for the building cluster, including direct load control and indirect load control. Then, the constrained nonlinear regression model is proposed to estimate the model parameters and occupant behavior, for which an efficient algorithm based on the block coordinate descent method is developed by exploiting the decomposable structure of the regression model. Simulation results based on real-world data show that the root mean square error and mean absolute percentage error for the multi-zone building (or building cluster) are below 0.72 °C and 1.44% (or 0.32°C and 1.39%), respectively, verifying the effectiveness of the proposed methods

Analysis of a novel six-degree of freedom foldable parallel mechanism with optimized under-balance springs

The capacities of parallel mechanisms are limited by their height for the narrow space applications, such as the shipboard stability platforms, household simulators, aerospace mechanisms, etc. This paper proposes a novel foldable six-DOF parallel manipulator which has three main limbs with each actuated by two actuators. With the ability to fold in the vertical direction, this mechanism can be deployed from a height of about 0.278 m to 2.218 m, and the required driving stroke is only 0.67 m by the analysis results of the workspaces. However, this stroke enlargement leads to large driving forces. In order to improve the capacity for the heavy loading of this foldable mechanism, each leg is assisted by a balance spring. Static and dynamics models are built for the calculation of the driving forces and constraint forces. Two methods to calculate the optimal balance force for objective driving force are also proposed and based on the designed trace in the workspace, the springs’ linear stiffness is optimized. The simulation results demonstrate that the actuators’ driving forces are much reduced, and the homogeneity between the fully folded and deployed configuration is much improved by adding balance springs

Multi‐stage flexible planning of regional electricity‐HCNG‐integrated energy system considering gas pipeline retrofit and expansion

Abstract The development of hydrogen‐enriched compressed natural gas (HCNG) can make full use of the existing natural gas infrastructure, thereby alleviating the economic and technical pressure on the development of pure hydrogen. This paper proposes a multi‐stage flexible planning method for the regional electricity‐HCNG‐integrated energy system (E‐HCNG‐IES), which considers the medium and long‐term dynamic characteristics of the E‐HCNG‐IES. For each sub‐regional energy station, an energy‐hub type model including hydrogen/HCNG‐related equipment and facilities is established. Considering the influence of hydrogen blending on the energy delivery capacity and line pack of pipelines, a hydrogen‐resistant retrofit model for existing natural gas pipelines between sub‐regions is proposed. Meanwhile, the model for newly constructed hydrogen pipelines is also presented. Subsequently, a series of flexibility evaluation indicators are proposed to support the performance analysis of planning schemes. The lateral comparison of sub‐cases in Changzhou, China demonstrates that considering the hydrogen‐resistant retrofit of natural gas pipelines can reduce the construction cost of hydrogen pipelines by about 37.12%. The peak shaving capacity of underground hydrogen storage (UHS), the energy recycling ability of turbo expander (TE), and the space‐time decoupling ability of hydrogen in energy supply and demand have also been confirmed