Abstract-Nowadays, w ith the unprecedented penetration of renewable distributed energy resources (DERs), the necessity of an efficient energy forecasting model is more demanding than before. Generally, forecasting models are trained using observed weather data while the trained models are applied for energy forecasting using forecasted weather data. In this study, the performance of several commonly used forecasting methods in the presence of weather predictors with uncertainty is assessed and compared. Accordingly, both observed and forecasted weather data are collected, then the influential predictors for solar PV generation forecasting model are selected using several measures. Using observed and forecasted weather data, an analysis on the uncertainty of weather variables is represented by MAE and bootstrapping. The energy forecasting model is trained using observed weather data, and finally, the performance of several commonly used forecasting methods in solar energy forecasting is simulated and compared for a real case study.

Abstract-Reliability assessment of distribution system, based on historical data and probabilistic methods, leads to an unreliable estimation of reliability indices since the data for the distribution components are usually inaccurate or unavailable. Fuzzy logic is an efficient method to deal with the uncertainty in reliability inputs. In this paper, the ENS index along with other commonly used indices in reliability assessment are evaluated for the distribution system using fuzzy logic. Accordingly, the influential variables on the failure rate and outage duration time of the distribution components, which are natural or human-made, are explained using proposed fuzzy membership functions. The reliability indices are calculated and compared for different cases of the system operations by simulation on the IEEE RBTS Bus 2. The results of simulation show how utilities can significantly improve the reliability of their distribution system by considering the risk of the influential variables.

Changing the structure of electrical energy markets from traditional to the restructured state, considering the loss allocation has been unavoidable. The importance of this matter is because the amount of loss consist significant part of total electrical energy. Loss in power system is a nonlinear function of power so using linear methods could not be efficient. On the other hand, applied function must consider both network characterizes and participation rate in power supplying and power consumption. The purpose of this paper is to present an applicable and modern solution based on the cooperative game theory for loss allocation of transmission lines in both pool and bilateral markets. This method has been tested on a 4 bus systems and a 14 bus IEEE.

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This study presents a new and practical way for the loss allocation in the restructuring systems problem. The restructured markets sell the electricity in two main categories; bilateral exchanges and pool based. The method which is used in this study investigates the loss allocation in pool based market. The deregulated systems are not under control of one person but there are other players such as generators and loads at which every one of such players has to pay the cost for some parts of network loss. The importance of this matter is that the loss ratio is a considerable part of the whole production. The method used in this study is to justify the loss allocation. This method is consisted of two different categories; finding the losses and the other is loss allocation using Game Theory. And to test this method, two systems of 4 and 14 IEEE bus is put in use. The results referring the generators show that the suggested method for the loss allocation to generators is close to the Pro Rata method and the results for the loads are something between the Proportion method and the ITL method.