With the integration of huge renewable energy sources (RESs) into active distribution networks, how to address the uncertainty outputs of RESs for the day-ahead volt/var control (VVC) is a significant challenge. This paper presents a chance constrained mixed integer second order cone model to handle the nodal power uncertainties and nonlinear branch flow equations. A direct and fast scenario generation method is proposed by employing the group division method and the seven-step probability distribution model of RESs outputs. An efficient and accurate solution method which only uses few larger probability level scenarios instead of all reserved scenarios is also proposed. Numerical simulations on the IEEE 69 standard system show the superiority of the proposed algorithm over traditional Monte Carlo sampling (MCS)-based methods.

To address the uncertainty in photovoltaic (PV) outputs for day-ahead home energy scheduling in hourly timescale, a novel stochastic optimization strategy based data-driven method is proposed. Based on available historical PV outputs, the Gaussian mixture model (GMM) algorithm combined with improved prediction strength of clustering method is applied to establish the forecasted probabilistic PV outputs model. Based on the seven-step approximation model of Gaussian distribution, only PV outputs with larger probability level at each hour are used to generate scenarios. Then the typical scenario set can be constructed by scenario reduction method. By finding the solution in typical scenario set using mixed-integer nonlinear programming (MINLP), the scheduling strategy will be closer to real cases. Test results verify the effectiveness of proposed probabilistic PV output model and solution method.

Telecom Italia, within its UltraBroadBand (UBB) development strategy, has the goal to deploy by the end of 2014 more than 25.000 “Fiber To The Cabinet” (FTTCab) nodes in all the main cities in Italy, hosting small Optical Network Units (ONU) with 48 VDSL2 ports each. Such particular architecture enables several benefits among which the possibility to use the existing primary copper network to remotely power the BB equipment from Central Office, thanks to the limited amount of power needed by the UBB equipment. This brings to the consideration that the Telecom Italia FTTCab with remote power deployment is one of the widest ever performed worldwide. This paper will firstly provide information on power consumption evolution of the UBB ONUs, highlighting the good path followed by the equipment towards greater energy efficiency. The activities towards Standardization Bodies, in particular ETSI and ITU-T, as well as European Commission (with the Code of Conduct on BroadBand equipment) will also be mentioned. The paper will then describe the associated evolution of the remote powering architectures massively adopted by Telecom Italia for its FTTCab deployment since 2012, highlighting their pros and cons. The different solutions adopted at the Main Distribution Frame and at the cabinet in order to guarantee proper protection to the technicians against discharge current will also be described. Moreover, the paper will provide an overview of the evolution of the FTTCab towards more “compact” solutions for both ONUs and remote power modules, reducing the overall physical footprint (and the total power consumption) and enabling underground and pole installations. Finally, the paper will describe the evolution of the FTTCab architecture towards the “Fiber To The distribution point” (FTTdp) architecture, involving even smaller UBB ONUs (1 to 8 lines) with even higher throughputs thanks to VDSL2 and G. Fast technologies applied to shorter loops. This will enable the shift from “remote powering” to “reverse powering” paradigm; to this end, the main features and challenges related to the latter solution will be highlighted.

Because stochastic fault cases (i.e., opportunistic maintenance strategy) of the equipment are not considered in the condition-based maintenance decision of the system, which will deviate from the actual situation, a system condition-based maintenance scheduling model considering opportunistic maintenance strategy is proposed in this paper. To implement the system maintenance strategies, the correlation set is formulated by considering the relationship among different equipment. According to renewal process theory, the availability of the correlation set considering planned maintenance and opportunity maintenance is deduced and the maintenance strategy of the system is realized. Then, to reflect the relationship between equipment maintenance and system operation, a system state scheduling model aiming at minimizing the sum of maintenance risk and failure risk as well as considering system resource constraints is proposed, thus obtaining the optimal maintenance schedule based on system state. Finally, a simple test system and IEEE-RTS79 node system are employed to demonstrate the feasibility and effectiveness of the proposed maintenance model, and it also verified that the proposed model can be integrated into the power system condition-based maintenance theory.

The research on electrical energy alternative mainly focus on alternative energy potential, expanding strategy and benefit analysis due to lack of historical data. This paper presents the total spatial load forecasting model in distribution network based on the proposed electrical energy alternative development coefficient which is generated by electricity energy objective issued by governments. To deal with fuzzy and uncertain in load forecasting for electric boiler and heater, the cloud theory and the regularity in the process of electrical energy alternative popularization are used. The component of electrical alternative spatial load forecasting is presented in sequence. The proposed method is verified in a typical case.