Sharif Digital Repository

In recent years, while energy consumption is still increasing, system peak load is decreasing due to deregulation in power systems, application of demand response programmes, microgrids and smart grids implementation, and so on. Thus, transmission system operators (TSOs), which are usually a public entity, must reinforce the transmission systems to maintain power system reliability. They are not interested in investing transmission network because of high investment costs. In this regard, this study presents a new bi-level model for co-planning of transmission system and merchant distributed energy resources (DERs). The upper level takes the TSOs perspective and aims to minimise the line... 

This work proposes comprehensive empirical predictive equations for generating stochastic synthetic 3-dimensional accelerograms for the Iranian plateau based on the existing database. First, the databank of Iranian accelerograms is collected, sorted, processed, declustered and categorized into the pulse-like and non-pulse-like data. To simulate the artificial accelerograms, a stochastic model capable of handling both the temporal and spectral non-stationarity of accelerograms is adopted. By implementing nonlinear curve fitting, parameters of the stochastic model are estimated. Then, the recorded events are categorized into eight distinct groups based on the existence of pulse-like... 

A bi-objective stochastic capacitated multi-facility location–allocation problem is presented where the customer demands have Bernoulli distributions. The capacity of a facility for accepting customers is limited so that if the number of allocated customers to the facility is more than its capacity, a shortage will occur. The problem is formulated as a bi-objective mathematical programming model. The first objective is to find optimal locations of facilities among potential locations and optimal allocations of stochastic customers to the facilities so that the total sum of fixed costs of establishment of the facilities and the expected values of servicing and shortage costs is minimized. The... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst these strategies, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through... 

In this paper, the problem of statistical reconstruction and prediction of chaotic systems with unknown governing equations using stochastic Markov models is investigated. Using the time series of only one measurable state, an algorithm is proposed to design any orders of Markov models and the approach is state transition matrix extraction. Using this modeling, two goals are followed: first, using the time series, statistical reconstruction is performed through which the probability density and conditional probability density functions are reconstructed; and second, prediction is performed. For this problem, some estimators are required and here the maximum likelihood and the conditional... 

In some applicable scenarios, such as community patrolling, mobile nodes are restricted to move only in their own communities. Exploiting the meetings of the nodes within the same community and the nodes within the neighboring communities, a delay tolerant network (DTN) can provide communication between any two nodes. In this paper, two analytical models based on stochastic reward nets (SRNs) are proposed to evaluate the performance of the epidemic content retrieval in such multi-community DTNs. Performance measures computed by the proposed models are the average retrieval delay and the average number of transmissions. The monolithic SRN model proposed in the first step is not scalable, in... 

Oil spills are serious environmental issues that potentially can cause adverse effects on marine ecosystems. In some marine areas, like the Baltic Sea, there is a large number of wrecks from the first half of the 20th century, and recent monitoring and field work have revealed release of oil from some of these wrecks. The risk posed by a wreck is governed by its condition, hazardous substances contained in the wreck and the state of the surrounding environment. Therefore, there is a need for a common standard method for estimating the risks associated with different wrecks. In this work a state-of-the-art model is presented for spatial and stochastic risk assessment of oil spills from... 

Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing... 

A new heuristic controller, called the continuous ant colony controller, is proposed for non-linear stochastic Gaussian/non-Gaussian systems. The new controller formulates the state estimation and the model predictive control problems as a single stochastic dynamic optimization problem, and utilizes a colony of virtual ants to find and track the best estimated state and the best control signal. For this purpose, an augmented state space is defined. An integrated cost function is also defined to evaluate the points of the augmented state space, explored by the ants. This function minimizes simultaneously the state estimation error, tracking error, control effort and control smoothness. Ants... 

This paper develops a stochastic geometry-based approach for the modeling and analysis of finite millimeter wave (mmWave) wireless networks where a random number of transmitters and receivers are randomly located inside a finite region. We consider a selection strategy to serve a reference receiver by the transmitter providing the maximum average received power among all transmitters. In our system model, we employ the unique features of mmWave communications such as directional transmit and receive beamforming and different channels for line-of-sight (LOS) and non-line-of-sight (NLOS) links. Accordingly, deploying a blockage process suitable for mmWave networks, we study the coverage... 

Continuous-time Stochastic Game (CTSG) can be seen as a proper model to analyze probabilistic, non-deterministic, and competitive behaviors as found in Stochastic Multi-Player Game (SMG). The difference is that in an SMG the system under design is analyzed in the discrete-time setting. In comparison, in a CTSG, the system transitions occur in the continuous-time setting with exponentially distributed delays. This paper focuses on the model checking of CTSGs and presents a uniformization-based algorithm, called TPA, to approximate the time-bounded reachability probabilities with an arbitrary error bound. We concentrate on CTSGs with bounded transition rates. To illustrate the strength points... 

Single-molecule experiments have found near-perfect thermodynamic efficiency in the rotary motor F1-ATP synthase. To help elucidate the principles underlying nonequilibrium energetic efficiency in such stochastic machines, we investigate driving protocols that minimize dissipation near equilibrium in a simple model rotary mechanochemical motor, as determined by a generalized friction coefficient. Our simple model has a periodic friction coefficient that peaks near system energy barriers. This implies a minimum-dissipation protocol that proceeds rapidly when the system is overwhelmingly in a single macrostate but slows significantly near energy barriers, thereby harnessing thermal... 

Growing widespread outages in power systems caused by natural disasters have highlighted the necessity of applying defensive approaches with the goal of prompt service restoration. In this context, this paper proposes a stochastic model with the goal of optimally using proactive operational actions before the upcoming disturbance hits. The actions considered in this study include network reconfiguration and crew prepositioning. To take the effective actions, the model simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method. The proposed model aims at minimizing the expected load curtailment caused by the event over the scenarios. To... 

Growing widespread outages in power systems caused by natural disasters have highlighted the necessity of applying defensive approaches with the goal of prompt service restoration. In this context, this paper proposes a stochastic model with the goal of optimally using proactive operational actions before the upcoming disturbance hits. The actions considered in this study include network reconfiguration and crew prepositioning. To take the effective actions, the model simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method. The proposed model aims at minimizing the expected load curtailment caused by the event over the scenarios. To... 

Long and continuous running of software can cause software aging-induced errors and failures. Cloud data centers suffer from these kinds of failures when Virtual Machine Monitors (VMMs), which control the execution of Virtual Machines (VMs), age. Software rejuvenation is a proactive fault management technique that can prevent the occurrence of future failures by terminating VMMs, cleaning up their internal states, and restarting them. However, the appropriate time and type of VMM rejuvenation can affect performance, availability, and power consumption of a system. In this paper, an analytical model is proposed based on Stochastic Activity Networks for performance evaluation of... 

In this paper, Stochastic Activity Networks (SANs) are used to model and evaluate the performance and power consumption of an Infrastructure-as-a-Service (IaaS) cloud. The proposed SAN model is scalable and flexible, yet encompasses some details of an IaaS cloud, such as Virtual Machine (VM) provisioning, VM multiplexing, and failure/repair behavior of VMs. Using the proposed SAN, a power-aware self-adaptive resource management scheme is presented for IaaS clouds that automatically adjusts the number of powered-on Physical Machines (PMs) regarding variable workloads in different time intervals. The proposed scheme respects user-oriented metrics by avoiding Service Level Agreement (SLA)... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects the RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through conditional... 

Energy Harvesting (EH) is a novel technique to prolong the lifetime of the wireless Ad-hoc and sensor networks with replenishable nodes. In this sense, it has emerged as a promising technique for Green Communications. On the other hand, cooperative communication with the help of relay nodes improves the performance of wireless communication networks. In this paper, we investigate the cooperation in EH nodes. We consider the optimal power and rate allocation in the full-duplex Gaussian relay channel in which source and relay can harvest energy from their environments. In our model, the energy arrivals at the source and the relay are general stochastic processes with known EH times and amounts... 

This paper introduces an efficient stochastic method to produce fully nonstationary records having multiple peaks in power spectrum. The zero-crossing characteristics of the acceleration, velocity, and displacement time histories of the output signal are used to estimate the model parameters. This procedure is utilized to resimulate 252 non-pulse-like, horizontal near-field records with rupture distance of less than 10 km and strike–slip mechanism. The model parameters are regressed against moment magnitude, rupture distance, hypo-central depth, and shear wave velocity, enabling the scenario-based simulation of the records. The response spectra of the simulated records are compared with... 

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...