Sharif Digital Repository

In the future smart grids, Plug-in Hybrid Electric Vehicles (PHEVs) are seen as an important means of transportation to reduce greenhouse gas emissions. One of the main issues regarding to this sort of vehicles is managing their charging time to prevent high peak loads over time. Deploying advanced metering and automatic chargers can be a practical way not only for the vehicle owners to manage their energy consumption, but also for the utilities to manage the electricity load during the day by shifting the charging loads to the off-peak periods. Additionally, an efficient charging schedule can reduce the users' electricity bill cost. In this paper we propose a new practical demand response... 

Speed and accuracy of under frequency load shedding (UFLS) has a vital role in its effectiveness for preserving system stability. In any case load-shedding still remains the ultimate resource for emergency condition. Initial rate of change of frequency is a fast and potentially useful signal to detect the overload when a disturbance happens. In order to improve the under-frequency load shedding performance, in this paper, a global load shedding scheme integrated with rate of frequency decline as an extra variable is proposed. The new SCADA based scheme is devised to overcome the shortcomings of previous adaptive UFLS procedures, and to provide a fast and yet reliable method to maintain... 

The potential of end-users to modify their consumption pattern makes them an interesting resource for providing energy flexibility in energy communities. Thus, active end-users require sufficient incentives and automated trading and management schemes. In order to enable increased small-scale end-users participation for flexibility service provision, a new design for flexibility trading is required to model the behavior of different agents and their interactions in energy communities. The novelty of our work lies in proposing an iterative game-based approach in which all agents - consisting of the distribution system operator (DSO), aggregators, and customers- can determine their decision... 

Application of residential demand response (DR) programs are currently realized up to a limited extent due to customers' difficulty in manually responding to the time-differentiated prices. As a solution, this paper proposes an automatic home load management (HLM) framework to achieve the household minimum payment as well as meet the operational constraints to provide customer's comfort. The projected HLM method controls on/off statuses of responsive appliances and the charging/discharging periods of plug-in hybrid electric vehicle (PHEV) and battery storage at home. This paper also studies the impacts of different time-varying tariffs, i.e., time of use (TOU), real time pricing (RTP), and... 

Demand response (DR) as a state-of-the-art program is accommodated in the energy efficiency contexts of the smart grid. Lack of the customer knowledge about how to respond to the time-differentiated tariffs and offered controlling signals is the major obstacle in the way of broad DR implementing. As a solution, an optimization method, namely load control (LC), is proposed to automatically control the on/off status of the responsive appliances in a smart home. This paper focuses on the direct load control (DLC) program in the category of incentive-based DR programs. LC is extended to consider inconvenience cost of the DLC implementation for DLC program participants. Outputs of the extended LC... 

Demand response (DR) as a state-of-the-art program is accommodated in the energy efficiency contexts of the smart grid. Lack of the customer knowledge about how to respond to the time-differentiated tariffs and offered controlling signals is the major obstacle in the way of broad DR implementing. As a solution, an optimization method, namely load control (LC), is proposed to automatically control the on/off status of the responsive appliances in a smart home. This paper focuses on the direct load control (DLC) program in the category of incentive-based DR programs. LC is extended to consider inconvenience cost of the DLC implementation for DLC program participants. Outputs of the extended LC... 

Different reasons such as power system restructuring, electricity price variation in some hours of a day and growth in the fuel price, have led to more attention to demand response (DR) programmes for consumers. Two important issues in DR programmes are emergency demand response programming (EDRP) and Interruptible/Curtail able (I/C) programme that is utilised as interruptible load contracts (ILC). The EDDR is utilised to decrease the consumption in peak load or critical hours of the day. This occurs by means of customer's behaviour in response to the incentives. However, the curtailment of voluntarily loads in the critical hours considering the consumer requirements is an action that can be... 

Load pay back effect is the excess of load as a result of load curtailment, observed in direct load control programs related to thermostatically controlled appliances. In this paper, according to a stochastic difference equation, the load profile of an aggregation of customers without control will be attained. Then the assumption to consider load pay back as linear will be examined through simulations. Afterwards, based on a data structure gained from performing load curtailments at each interval, least-square method will be used to fit load pay back factors for each interval. It is notable that there are some significant differences between the results attained in this paper and what was... 

The domestic heating, ventilation, and air-conditioning load promises a good prospect for electrical aggregators to consider it for demand response. This article presents a user-centric demand response control for scheduling the electric space heating load under a price and load uncertainty environment. The objective of the framework is to minimize a weighted sum of the expected payment, loss of comfort, and financial risk of a customer while strictly considering the end-user preferences. The household thermal behavior is modeled via an accurate two-capacity building model. The price and load uncertainty is modeled using a scenario-based stochastic programming approach. The proposed decision... 

Network pricing is an effective transportation demand management scheme to reduce traffic and control air pollution, particularly in CBDs. In this study, congested area cordon entry and Park-and-Ride (P/R) facility use are priced for automobiles. Increase in these prices may reduce private auto demand by impelling some of the auto passengers to use public transport from the origin of their trips, or encouraging them to park their cars at the P/R facilities and use buses, or pay the entrance fee and drive inside the cordon. A Markov decision process has been devised to find an optimal policy for pricing the P/R facilities and cordon entry in a city within a variable demand context. This... 

This paper mainly focuses on operational reliability studies of modern power systems taking into consideration the effects of energy storage systems (ESSs). The aim is to develop a new evaluation tool to assess the effects of different factors such as penetration rate, operational strategies and capacities of the ESSs in determining the role of these systems as an operating reserve resource. In this regard, at first, some modifications are made to the PJM method aimed to precisely model the short-term variability in output generation of wind farms in reliability studies. Then, this algorithm is employed to examine the effects of ESSs operating strategies in operational reliability level of... 

Computation of Loss of Load Probability (LOLP) is a challenge in Generation Expansion Planning (GEP) problem. This paper presents a dynamic GEP model considering LOLP as a reliability criterion. The objective function of the proposed dynamic GEP model includes the discounted total costs of investment cost, operation cost, and maintenance cost. The proposed LOLP constrained GEP problem is formulated as a mixed integer nonlinear programming (MINLP) problem. The MINLP formulation of GEP problem is then converted to a mixed integer linear programming (MIP) problem by applying several approximations to LOLP constraint. The utilized approximations are divided into two clusters for low and high... 

This paper mainly focuses on operational reliability studies of modern power systems taking into consideration the effects of energy storage systems (ESSs). The aim is to develop a new evaluation tool to assess the effects of different factors such as penetration rate, operational strategies, and capacities of the ESSs in determining the role of these systems as a source of operating reserve. In this regard, at first, some modifications are made to the Pennsylvania-New Jersey-Maryland (PJM) method aimed to precisely model the short-term variability in output generation of wind farms in reliability studies. Then, this algorithm is employed to examine the effects of ESSs operating strategies... 

We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems. In this framework, we investigate the tension between storage resources, communication cost, and load balancing performance. To this end, we propose a randomized load balancing scheme which simultaneously considers cache size limitation and proximity in the server redirection process. In contrast to the classical power of two choices setup, since the memory limitation and the proximity constraint cause correlation in the server selection process, we may not benefit from the... 

This paper demonstrates how a probabilistic criterion could be explicitly integrated in the unit commitment (UC) formulation. Both spinning reserve and interruptible load are taken into account as the operating reserve facilities. Incorporating the interruption notice time of interruptible load involves some complexities in the evaluation procedure and problem formulation which is considered in this paper. The expected energy not supplied (EENS) is considered as a probabilistic criterion and a new method is proposed to calculate this index in the presence of interruptible load. The reliability-constrained unit commitment (RCUC) problem is formulated based on the mixed-integer programming... 

Three novel methods, named α, ζ and ϵ, are suggested in this paper to recover the performance loss during switching in the gas turbine control systems. The Minimum Command Selection (MCS) in the gas turbine control systems prompts this performance loss. Any step towards more productivity with less aging factors have a great impact on the gas turbine's lifetime profit and vice versa. Although many hardware upgrades have been studied and applied to accomplish this, in many cases a low-risk manipulation in the software may yield equivalent achievement. State of the art gas turbine control systems are supposed to handle various forms of disturbances, several operation modes and relatively high... 

Proliferation of photovoltaic (PV) panels may cause voltage increases in low voltage (LV) distribution feeders. This issue confines PV hosting capacity of the feeders. To overcome this issue and enable higher PV hosting capacity, a model to manage the operation cycles of the domestic electric water heater and heating, ventilation, and air conditioning loads in order to avoid the voltage rise, thereby increasing PV hosting capacity in LV feeders is presented in this study. The model respects users' thermal comfort by setting the associated temperatures within allowed ranges. To preserve customers' privacy, the presented model is then decomposed into a master problem and several sub-problems... 

This paper proposes a simultaneous approach to manage congestion, evaluate congestion cost, and to allocate this cost among consumers in a short-run market model. The proposed method consists of an iterative algorithm to search and apply a sequence of the best feasible bilateral power exchange among the generators that would optimally reduce and completely remove the congestion. The best exchanges are selected using sensitivity analysis and the AC load flow is used to apply the selected exchange on the system. Congestion cost is calculated using the change in generation cost and divided among the overloaded lines regarding the change in power flow of these lines, after applying the selected... 

Three novel methods, named α, ζ and ϵ, are suggested in this paper to recover the performance loss during switching in the gas turbine control systems. The Minimum Command Selection (MCS) in the gas turbine control systems prompts this performance loss. Any step towards more productivity with less aging factors have a great impact on the gas turbine's lifetime profit and vice versa. Although many hardware upgrades have been studied and applied to accomplish this, in many cases a low-risk manipulation in the software may yield equivalent achievement. State of the art gas turbine control systems are supposed to handle various forms of disturbances, several operation modes and relatively high... 

This paper presents a comprehensive educational model considering share resources among several departments bounded to educational limitations for optimizing energy consumption. The thermal model calculates the load based on the ambient temperature to minimize the user's knowledge of the building's thermal model. It determines the percentage reduction of the building's heating load in case of a change in room temperature, a term's start date, and sharing classes compared to standard curricula. It employs linear Boolean optimization. Class planning is carried out concerning minimizing energy use, students' preferences, charts, educational constraints, professors' schedules, classes' numbers,...