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In this paper, we study the interactions among interconnected autonomous microgrids, and propose a joint energy trading and scheduling strategy. Each interconnected microgrid not only schedules its local power supply and demand, but also trades energy with other microgrids in a distribution network. Specifically, microgrids with excessive renewable generations can trade with other microgrids in deficit of power supplies for mutual benefits. Since interconnected microgrids operate autonomously, they aim to optimize their own performance and expect to gain benefits through energy trading. We design an incentive mechanism using Nash bargaining theory to encourage proactive energy trading and fair benefit sharing. We solve the bargaining problem by decomposing it into two sequential problems on social cost minimization and trading benefit sharing, respectively. For practical implementation, we propose a decentralized solution method with minimum information exchange overhead. Numerical studies based on realistic data demonstrate that the total cost of the interconnected-microgrids operation can be reduced by up to 13.2% through energy trading, and an individual participating microgrid can achieve up to 29.4% reduction in its cost through energy trading. To appear in IEEE Transactions on Smart Grid

Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

Production of biodiesel from yellow grease (waste cooking oil and waste animal fats) is fast emerging as a promising alternative to address the twin challenges before the biodiesel industry today-fluctuation in prices of vegetable oil and the food versus fuel debate. Yellow grease has a high percentage of free fatty acids (FFA) and proves to be an unsuitable feedstock for biodiesel production from commercially viable alkali-catalyzed production systems due to saponification problems.“Green” methodologies based on heterogeneous solid acid catalyzed reactions have the potential to simultaneously promote esterification and transesterification reactions of yellow grease to produce biodiesel without soap formation and offer easy catalyst separation without generation of toxic streams. This paper presents kinetic studies for the conversion of model yellow grease feeds to biodiesel using a heteropolyacid supported on alumina (HSiW/Al2O3) using a batch autoclave. Three model yellow grease feeds were prepared using canola oil with added FFA such as palmitic, oleic and linoleic acid. A pseudo homogeneous kinetic model for the parallel esterification and transesterification was developed. The rate constants and activation parameters for esterification and transesterification reactions for the model yellow grease feeds were determined. The rate constants for esterification are higher than the transesterification rate constants. The kinetic model was validated using the experimental biodiesel data obtained from processing a commercial yellow grease feed. The kinetic model could be used to design novel processes to convert various low-value waste oils, fats and non-food grade oils to sustainable biodiesel. Keywords: Yellow grease, Canola oil, Free fatty acids, Heteropolyacid, Kinetics for esterification and transesterification

A new version of the ENERGY-10 computer program simulates the performance of photovoltaic systems, in addition to a wide range of opportunities to improve energy efficiency in buildings. This paper describes two test cases in which the beta release of ENERGY-10 version 1.4 was used to evaluate energy efficiency and building-integrated photovoltaics (BIPV) for two Federal building projects: a 16,000-ft2 (1,487 m2) office and laboratory building at the Smithsonian Astrophysical Laboratory in Hilo, Hawaii, and housing for visiting scientists [three 1400-ft2 (130 m2) and three 1564-ft2 (145 m2) houses] at the Smithsonian Environmental Research Center in Edgewater, Maryland. The paper describes the capabilities of the software, the method in which ENERGY-10 was used to assist in the design, and a synopsis of the results. The results indicate that ENERGY-10 is an effective tool for evaluating BIPV options very early in the building design process. By simulating both the building electrical load and simultaneous PV performance for each hour of the year, the ENERGY-10 program facilitates a highly accurate, integrated analysis.

The most severe failures in power grids are often characterized as cascading failures where an initial event triggers consequent failures all along the grid often leading to blackouts. Upon identifying a failure and its cascade potential, timely control actions should be performed by the grid operators to mitigate the effect of the cascade. These actions have to be delivered to one or more control devices, creating a dependency between the power grid and its control network. This paper examines the dependency of the operation of the power grid on the control network. Different from literature studies on failure control, our dependency model captures the impact of networking parameters. We formulate an algorithmic model that describes the impact of this dependency on cascade control. Based on this model, we propose an efficient cascade control algorithm using load shedding with consideration of delays in the communication network for power grids. Finally, we evaluate the impact of the power-communication network dependency with uncontrolled grids, ideal/simple control grids and our proposed control scheme. The results demonstrate that the proposed algorithm can significantly reduce the failure of power lines while sustaining larger power demand for users.

AbstractMembrane Technology and Research, Inc. has proposed a hybrid system combining amine scrubbing with membrane technology to reduce energy cost. Previous studies of CO2 absorption mainly focused on coal-fired flue gas with 12% CO2. However, in the hybrid process, the CO2 in the flue gas can be enriched to 20%. Natural gas turbines will have flue gas with as little as 3% CO2。 Based on the arrangement, the hybrid amine/membrane system provides a gas to the system that has double the CO2 concentration of normal flue gas, reduces the volume of gas sent to the capture unit, or reduces the removal requirements for the capture unit.The objective of this work is to minimize the total energy use of stripping concentrated piperazine (PZ) at rich loading when treating flue gas from 3 to 20% inlet CO2. The base-case stripping configuration is the advanced flash stripper with warm rich bypass and cold rich exchanger bypass. . This configuration includes two split cross-exchangers in series, a convective steam heater, a smaller stripper column, a low residence time flash tank, and stripping at high temperature to produce CO2 at 5 to 17bar. Rich loading in 5 and 8m PZ was varied from 0.37 to 0.43mol CO2/mol N. For each rich loading, lean loading was optimized to minimize the total equivalent work. The “Independence” model for PZ in Aspen Plus® was used to simulate the stripping performance.Because 5m PZ has a lower viscosity than 8m PZ, it can achieve a reduced approach temperature in the cross exchanger. The total energy performance for 5m PZ is practically the same as 8m PZ, even though the capacity of 5m PZ is lower. Significantly more energy is required to regenerate solvents with lower rich loading. As CO2 rich loading increases, the equivalent work requirement decreases for the same loading difference between rich and lean.Stripping data for 24 cases, including heat duty, equivalent work, CO2 output pressure, and optimal cold and warm rich bypass were used to build a correlation with CO2 rich and lean loading. The Second Law efficiency based on the ratio of stripping minimum work and total ideal work was introduced to make the most of stripping work. The Second Law efficiency has a maximum value at a specific CO2 loading.

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.