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Energy internet and energy system integration with multi-energy complementation are vital developing directions of future energy supply systems. Combined cooling, heating and power(CCHP) realizes the coupling use of various forms of energy, and is one of the fundamental elements of the energy internet. During the concentrated CCHP operation analysis, due to the restriction of the fixed heat-electricity ratio, the coordination of the system and the combustion units will greatly impact the running efficiency of concentrated CCHP. In this paper, optimal operation strategy for the concentrated CCHP with the incorporation of the phase-change energy storage devices is analyzed. The flexible load participating in the demand response is also taken into consideration. On this basis, the economy objective function of CCHP is established and the units' output is scheduled. The results of an example in a micro grid applying CCHP show that the energy consumption is reduced, and the working efficiency of the system is improved.

Direct power purchase by large consumers is a good attempt to adjust the power price by market means, which is in favor of exploring a reasonable price formation mechanism and promotes the establishment of an open electricity market. To make the wheeling price and power loss minimum as the target, the paper presents a method based on the flow tracing, tracing the source of large power users, establishing the power grid optimization scheduling model considering the direct power purchase by large consumers. This paper simulates and analyzes the power grid optimization scheduling strategy under different numbers of large consumers in IEEE 30-bus system, the results demonstrate that the model presented can achieve comprehensive optimization of power loss and wheeling price satisfying the requirements of large consumers.

Benefited from the flexibility of Smart Grids, various dynamic lightning protection and Artificial Intelligence-based lightning protection methods become available. Based on Artificial Intelligence technologies, the paper proposes a method of lightning-caused faults forecasting for Smart Grid distribution systems. A self-balancing dynamic lightning protection, which assists the self-healing function of a Smart Grid distribution network, is also presented in the paper. The Artificial Intelligence-based Lightning Protection, which is defined and described in the paper, provides more comprehensive lightning protection solutions to improve system reliability for the Smart Grids.

Benefited from the interactivity and flexibility of Smart Grids, various dynamic lightning protection methods become available. A System-level lightning protection mode named Dynamic Lightning Protection is presented in the paper. Combined with real time lightning tracking and warning, a Dynamic Lightning Protection System carries out preventive protection actions during the lightning storms. It results in minimizing the impacts of lightning-caused disturbances, trips and interruptions, and improving the robustness of a Smart Grid transmission system.

For the purpose of improving reliability and robustness of a Smart Grid, a Dynamic Lightning Protection mode was developed. While the conventional mode focuses on the protection for each grid component individually, this dynamic mode focuses on protecting the whole electric grid in its entirety. Based on real time lightning detection, the dynamic protection system carries out flexible protection actions in advance. Furthermore, the mode results in minimizing the impacts of lightning-caused trips, disturbances and interruptions, which reduces the risk of a grid-scale blackout and facilitates the self-healing during the lightning storms. The dynamic protection mode, as discussed in the paper, provides more available applications of lightning detection and interactive Smart Grid lightning protection.

New approaches are being explored towards a successful thin film ZnO/Si heterojunction solar cell. The current approach involves Al-doped ZnO and microcrystalline Si grown by metal-induced growth. Nanoparticles added to the ZnO layer may introduce plasmonic effects and light scattering. Current work using an Al-ZnO/Buffer/Bulk-Si device has achieved a J SC of 28.26 mA/cm2, a V OC of 360 mV, and an efficiency of 5.91%. Fabricated Schottky photodiode devices using MIG-Si have achieved a J SC of around 5.4 mA/cm2 and V OC of 245 mV. According to simulations, an Al-ZnO/MIG-Si device can reach a JSC of 18.54 mA/cm2, a V OC of 670 mV, and an efficiency of 10.359% without plasmonic effects.

AZO/Si heterojunction solar cells were fabricated and investigated. In this structure AZO plays a role as a transparent current spreading layer and rectifying junction with silicon (Si). Furthermore, by introducing silver nanoparticles (Ag NPs) inside of the AZO film, light harvesting was enhanced because of plasmonic and light scattering effects ensuring minimized electrical and optical loss within the AZO. AZO was grown by co-sputtering of ZnO and Al. AZO (Al 5.78 wt%) was deposited on Si with 20, 40 nm of thickness. Ag NPs were then spread by spin coating and 230 nm of AZO was deposited again having a sandwich-like structure. In SEM observation, Ag NPs covered 4.7 % of the front surface. Solar cells were fabricated using Al front and back contacts with the size of 0.25 cm2. Computer simulations were carried out to optimize current gain regarding a total photon energy into Si. In calculation, absorption enhancement is maximized when Ag NPs are located as close to the Si layer in the range of 10 ∼ 40 nm. Experimentally, 20 nm of bottom AZO showed the best result in terms of efficiency. Spectral response showed 15 % enhancement at 430 nm and 5 ∼ 10% enhancement within 600 ∼ 1000 nm. Best performance was shown to have 0.36 V of V oc , 28.3 mA/cm2 of J sc and an efficiency of 5.91 %.

For the purpose of improving the stability and robustness of Smart Grid, a dynamic lightning protection mode which based on real time lightning detection was developed. While the conventional mode focuses on the protection for each individual grid element or component (transmission line, distribution line, transformer, substation, electronic equipment, etc) separately, the dynamic mode that named Active Lightning Protection (ALP) concentrates on protecting the whole electrical grid in its entirety. According the real time lightning detection information, the ALP mode carries out dynamic measures in advance, including adjusting the grid operation mode, optimizing the gird power flow distribution, controlling the generation units, switching the Microgrid. Furthermore, it leads the load to those parts of smart grid which are not threatened by lightning, so as to reduce the risk of grid-scale blackout. The dynamic protection mode, which discussed in the paper, provides more optional applications of lightning detection in the Smart Gird.

For the power grid lightning protection, an ACTIVE mode had been introduced in this paper, which is different from the traditional passive protection ways. Active Lightning Protection (ALP) means carrying out preventive measures in advance according to the real time lightning detection or tracing information. The ACTIVE mode more emphasizes the defensive measures for power grid before potential hazards but not just waiting to be stroke when thunderstorm approaching.

Community Question Answering (cQA) services, such as Yahoo! Answers and MSN QnA, facilitate knowledge sharing through question answering by an online community of users. These services include incentive mechanisms to entice participation and self-regulate the quality of the content contributed by the users. In order to encourage quality contributions, community members are asked to nominate the ‘best’ among the answers provided to a question. The service then awards extra points to the author who provided the winning answer and to the voters who cast their vote for that answer. The best answers are typically selected by plurality voting, a scheme that is simple, yet vulnerable to random voting and collusion. We propose a weighted voting method that incorporates information about the voters’ behavior. It assigns a score to each voter that captures the level of agreement with other voters. It uses the voter scores to aggregate the votes and determine the best answer. The mathematical formulation leads to the application of the Brouwer Fixed Point Theorem which guarantees the existence of a voter scoring function that satisfies the starting axiom. We demonstrate the robustness of our approach through simulations and analysis of real cQA service data.