Sharif Digital Repository

Wind power producers have recently gained a significant penetration in the electric power network, which might cause some challenges for the system operation due to the uncertainties in the generated power. In this way, wind power owners may offer different services, such as providing reserve capacity besides their conventional role of delivering just energy. Currently, conventional generators are the main responsible for providing some reserve in case of uncertainty in renewable generation and demand changes. Therefore, this article introduces a novel approach that allows wind power producers to participate in both energy and reserve markets alongside conventional generators. A two-stage... 

This paper investigates the role of parking lots in improving the reliability of renewable-based distribution systems, through provision of vehicle-to-grid (V2G) programs during outage events. In this regard, municipal parking decks are viewed as distributed energy storage systems and the amount of available energy from these units in random contingency events is probabilistically modeled for reliability studies. Appropriate stochastic models are also introduced to capture the volatility and intermittency of renewable sources. Moreover, it is discussed that how the adopted outage management scheme (OMS) in contingency events can affect the reliability level of customers. In response, several... 

This paper presents a stochastic framework for day-ahead scheduling of microgrid energy storage systems (ESSs) in the context of multi-objective (MO) optimization. Operation cost of microgrid in normal conditions and load curtailment index in case of unscheduled islanding events (initiated by disturbances in the main grid) are chosen as main criteria of the proposed scheme. In practice, duration of disconnection from the upstream network is unknown in unscheduled islanding incidents and cannot be predicted with certainty. To properly handle the uncertainties associated with time and duration of such events as well as microgrid load and renewable power generation, stochastic models are... 

In diffusive molecular communication (DMC), the transmitter has to be able to control the release of signaling molecules for modulation of the information bits. In natural cells, pumping ions is an important control mechanism for releasing molecules which is carried out by ion pumps embedded in the membrane. The activity of the ion pumps is controlled by a driving parameter. In particular, light driven pumps are controlled by light intensity and enable a high degree of spatial and temporal control for modulation functionality. In this paper, a modulator based on ion pumps is proposed for DMC which controls the release rate of the molecules from the transmitter by modulating a light intensity... 

The aim of this paper is to model and evaluate the performance of intrusion detection systems (IDSs) facing black-hole and grey-hole attacks within wireless ad hoc networks (WANETs). The main performance metric of an IDS in a WANET can be defined as the mean time required for the IDS to detect an attack. To evaluate this measure, two types of stochastic models are used in this paper. In the first step, two different continuous time Markov chains (CTMCs) are proposed to model the attacks, and then, the method of computing the mean time to attack detection is presented. Since the number of states in the proposed CTMCs grows rapidly with increasing the number of intermediate nodes and the... 

This paper presents an improved stochastic simulation method for calculating current dependent energy losses in distribution networks. The method is based on power load curves and integrates the stochastic nature of the load curves with power and voltage covariance matrices. The method reduces calculation effort using the factor analysis of covariance matrices and provides a few quantities needed to calculate energy losses. The method has no limitation for network configuration and gives accurate results several times faster than other existing methods. Therefore, it is appropriate for considering losses in optimization and decision making purposes in operating and planning of distribution... 

This paper deals with energy management of microgrids during unscheduled islanding events, initiated by disturbances in the main grid. In these situations, the main challenge is uncertainty about duration of disconnection from the main grid. In order to tackle this issue, a stochastic framework is proposed for optimal scheduling of microgrid resources over this period. The presented framework addresses the prevailing uncertainties of islanding duration as well as prediction errors of demand and renewable power generation. According to this framework, the probability distribution of islanding duration needs to be estimated, instead of predicting its exact value. The objective is to minimize... 

An adaptive approach for distribution system reconfiguration and charging management of plug-in electric vehicles (PEV) is presented in this study. A stochastic model predictive control is applied to stochastically, adaptively, and dynamically reconfigure the system, manage the incidental charging pattern of PEVs, and deal with the variable and uncertain power of renewable energy sources. The objective function of problem is minimizing daily operation cost of system. Herein, the geography of area is considered and the behavior of PEVs' drivers (based on their income level) is modeled with respect to the value of incentive and their hourly distance from each charging station. It is shown that... 

This article presents a mixed-integer linear stochastic model for the optimal expansion planning of electricity distribution networks and distributed generation (DG) units. In the proposed framework, autonomous DG units are aggregated and modeled using the well-known energy hub concept. In this model, the uncertainties of heat and electricity demand as well as renewable generation are represented using various scenarios. Although this is a standard technique to capture the uncertainties, it drastically increases the dimensions of this optimization problem and makes it practically intractable. In order to address this issue, a novel iterative method is developed in this article to enhance the... 

We have recently introduced a high-level extension for stochastic activity networks (SANs) called coloured stochastic activity networks (CSANs). CSANs have several distinguishing properties, which make them quite appropriate for modeling and evaluation of software performance and dependability. CSANs have introduced a construct called coloured place for data manipulation. A coloured place holds a list of tokens of a userdefined token type. CSAN models can be evaluated by state space analysis techniques or discrete-event simulation. However, their state spaces will become very large, even for a small CSAN model. For efficient evaluation of these models by state space analysis methods, we will... 

As multi-hop wireless networks are attracting more attention, the need to evaluate their performance becomes essential. In order to evaluate the performance metrics of multi-hop wireless networks, including sending and receiving rates of a node as well as the collision probability, a model based on Stochastic Reward Nets (SRNs) is proposed. The proposed SRN models a typical node in such networks, considered as a general template to be applied to any wireless node. The SRN model of a single node is designed to take transmission effects of all neighboring nodes into account, while ignoring the ones whose transmission has no effect on the node under-study. Applying the proposed SRN to each node... 

PV generation variability and uncertainty significantly influence operation of the power systems with high penetration of PV sources. The potential impact of distributed PV generation on ramp rate requirements in the IEEE 24-bus system is evaluated in this paper. PV generation and load are, here, probabilistically modeled using actual data and curve fitting approach. Probabilistic unit commitment (UC) based on unit de-commitment method combined with two point estimate method (2-PEM) is used to determine the ramp rate required to compensate for the PV power fluctuations. The proposed method considers stochastic factors and their effects on the dispatch results. Two scenarios are studied to... 

Making proper decisions in today's complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling (ABM). ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making (DM) aspect to ABM can support the decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In... 

Time-interleaved analog to digital converters (TI-ADC) offer high sampling rates by passing the input signal through C parallel low-rate ADCs. We can achieve C-times the sampling rate of a single ADC if all the shifts between the channels are identical. In practice, however, it is not possible to avoid mismatch among shifts. Besides, the samples are also subject to jitter noise. In this paper, we propose a blind method to mitigate the joint effects of sampling jitter and shift mismatch in the TI-ADC structure. We assume the input signal to be bandlimited and incorporate the jitter via a stochastic model. Next, we derive an approximate model based on a first-order Taylor series and use an... 

A space dependent model for the second moment of a stochastic field has been presented. The derivation procedure is simple and avoids non-physical assumptions for completeness. Moreover, a program has been developed which obtains the solutions to this equation in the three dimensional space. Two benchmarks, namely the fissile cube and the subcritical slab, show the accuracy of the results obtained using this method  

The railroad blocking problem is classified in the tactical level of freight rail transportation problems. The objective of this problem is to determine the optimal paths for each shipment such that the railway limitations are satisfied. In this problem, the quantities of both demand and supply resource indicators are often assumed to be certain and known, but because a blocking solution is designed for a relatively long period of time, this assumption is not reasonable. In this paper, we have developed a two-stage stochastic program for this problem to consider the uncertainty inherent in demand and supply resource indicators. Due to the size and complexity of the stochastic program and the... 

Besides increasing the installation of distributed generation plants, investigation on multi-carrier energy systems leads recent studies to focus on several aspects of Smart Energy Hub (S. E. Hub) systems. An S. E. Hub incorporates several modules which calculation of optimal size and operation of each have already attracted a great deal of research. Uncertainty in the modeling of these modules is an imperative factor that was not paid attention in S. E. Hub models properly. To build up a more precise framework for S. E. Hubs, here we present a stochastic model for real time electricity and natural-gas prices and electricity demands. In this paper, an S. E. Hub operates in order to minimize... 

In this paper, we develop a stochastic programming model for the capacitated location-allocation problem in the heterogeneous environment where the demands are distributed according to the Bernoulli function with different probabilities. The capacitated sub-sources of facilities are also involved to satisfy customers’ demands in this work. This study aims to find optimal locations of facilities and optimal allocations of existing customers to the facilities so that the total cost of operating facilities, allocating the customers, expected servicing and outsourcing is minimized. Due to the large amount of customers with different demand probabilities, accurate estimation of the outsourcing... 

The fast growth of technologies most of which depend on natural sources of energy has resulted in a huge consumption of fossil fuels. In this regard, many solutions have been suggested to alleviate the side effects such as air pollution and global warming. Among these solutions, mobile storages like electric vehicles (EVs) and renewable generations, have grown significantly due to being more applicable. But uncoordinated operation and uncertain nature of these distributed energy resources (DERs) can bring forward new challenges and issues to the operators of power system. Thus, in many cases it is more efficient to co-operate them in a hybrid system. In this study, we address a virtual power... 

Persian Gulf is a semi-enclosed highly saline reverse estuary that is exposed to the risk of oil spills in offshore oil and gas activities. In the early 2000s, a specific version of NOAA's Trajectory Analysis Planner (TAP II) was developed for Persian Gulf to assist regional organizations in preparing oil spill contingency plans. In this research, a new stochastic model is developed to cover the limitations of TAP II. The new model is based on an advanced trajectory model, which is now linked with high resolution spatiotemporal data of the wind and sea current. In a case study, the developed model is compared with TAP II, and evaluated by multiple tests designed for analysis of uncertainty,...