Sharif Digital Repository

Recently in electricity markets, a massive focus has been made on setting up opportunities for participating demand side. Such opportunities, also known as demand response (DR) options, are triggered by either a grid reliability problem or high electricity prices. Two important challenges that market operators are facing are appropriate designing and reasonable pricing of DR options.In this paper, time-of-use program (TOU) as a prevalent time-varying program is modeled linearly based on own and cross elasticity definition. In order to decide on TOU rates, a stochastic model is proposed in which the optimum TOU rates are determined based on grid reliability index set by the operator. Expected... 

Renewable energy resources, notably wind power, are expected to provide considerable portion of the world energy requirements in the near future. Many system operators around the world are challenged by the problems associated with integrating these intermittent resources into the grid. As one of the potential solutions, demand response (DR) is expected to play a major role for mitigating integration issues of intermittent renewable energy resources. In this context, this paper proposes a DR program which helps to integrate wind power by reshaping the load of the system. The DR program provides a framework to procure load reduction from DR resources in the wholesale energy market. The... 

Reducing the emissions produced by the electric power production may be one of the most challenging problems of the electricity sector in the coming future. As one of the potential solutions, demand response (DR) can play an important role to reduce emissions and costs associated with emission reduction activities. This paper aims to assess the short-term impacts of running a DR program on a power system constrained by emissions caps. The DR program is designed to procure operating reserve from demand-side participants. A day-ahead network-constrained market clearing model with emission cap constraints is used as the assessment tool, where the DR program participants along with generating... 

Although the simple assembly line balancing problem (SALBP) is the topic of many studies, typically they either consider minimizing the number of stations for a given cycle time (called type one), or minimizing the cycle time for a given number of stations (called type two). Rarely, type E of the problem has been considered. In the type E, cycle time and number of stations are both decision variables, and the objective is to maximize the line efficiency. This paper presents a mixed integer linear programming formulation for the type E simple assembly line balancing problem. Moreover, to further strengthen the presented formulation, two enhancement techniques in the form of valid inequalities... 

Time varying prices by motivating customers to reduce their consumption in peak periods propel the electricity industry towards a higher efficiency compared to that of common flat prices. Focusing on time-of-use (TOU) sale prices, this paper establishes a stochastic model for the medium-term decision making problem faced by a distribution company (DisCo). The developed model deals with the DisCo's decisions on the level of involvement in forward contracts and in the pool as well as the sale prices offered to customers. The demand response to TOU prices is captured using a price elasticity matrix (PEM). The objective is to maximize the DisCo's profit while the exposure risk imposed by... 

A two-stage framework for transformer maintenance management is introduced and formulated in Part I of this two-part paper in the context of transmission asset management strategies (TAMS). The proposed model optimizes maintenance outage schedule over a predefined period of time by taking into account the actual and expected transformer assets' condition dynamics in terms of failure rate and resource limitations in midterm horizons, as well as operating constraints, economic considerations and N-1 reliability in the shorter term. In Part II, a small six-bus system is first used to demonstrate how the two-stage maintenance framework works using a step-by-step procedure. Then, IEEE-RTS is used... 

The emergence of smart grid technologies in terms of advanced communication infrastructure, embedded intelligence, diagnostics and monitoring capabilities offers new opportunities for improved transmission asset management strategies (TAMS). Accordingly, power system operators are currently looking for analytics that can make use of transmission asset condition monitors and data already available to make better-informed decisions. This two-part paper introduces a two-stage maintenance scheduler for power transmission assets. Part I begins with the motivation for TAMS and then continues with a two-stage maintenance management model that incorporates joint midterm and short-term maintenance.... 

Gas detectors play an important role in safety of process plants. In-time detection of flammable gas releases may prevent major fire and explosion as well as property loss in process plants. One of the challenges of the gas detection system design is determining the best layout for detectors in order to reduce the risk of gas releases as much as possible. However, current methods do not address the risk concept in placement of detectors quantitatively. A risk-based methodology is proposed for optimal placement of point type flammable gas detectors in which first the risk (defined as a combination of scenario frequency, delayed ignition probability and damage) is estimated for any release... 

This paper studies a simultaneous weekly assignment and scheduling decisionmaking problem in operating theaters with elective patients. Because of limited recourses in hospitals, considering assignment and scheduling decisions simultaneously can help mangers exploit the available resources more efficiently and make the work-load uniformly distributed during the planning horizon. This procedure can significantly reduce hospital costs and increase satisfaction of patients and personnel. This paper formulates the mentioned problem as a Mixed Integer Linear Program (MILP) considering applicable assumptions like finite recovery beds and limitation of equipment. Since the problem is NP-hard, in... 

Increasing redundant paths in transmission grids has always been thought to be a tool to enhance service reliability. However, network equations by intertwining power flows through redundant paths impose more limits on systems with more redundancy. Accordingly, autonomous removing of a few lines may relief capacity limit violations in some contingency events thereby enhancing service reliability. This paper aims to study impacts of manual removing of transmission lines on composite system reliability. For doing so, the existing model is extended to consider optimal transmission switching (OTS) as a remedial action. The model minimizes total damage cost imposed by load curtailments. The... 

Increasing redundant paths in transmission grids has always been thought to be a tool to enhance service reliability. However, network equations by intertwining power flows through redundant paths impose more limits on systems with more redundancy. Accordingly, autonomous removing of a few lines may relief capacity limit violations in some contingency events thereby enhancing service reliability. This paper aims to study impacts of manual removing of transmission lines on composite system reliability. For doing so, the existing model is extended to consider optimal transmission switching (OTS) as a remedial action. The model minimizes total damage cost imposed by load curtailments. The... 

Data envelopment analysis (DEA) is a mathematical programming approach to efficiency measurement in many applications. In some real-life applications, three situations are established. First, the input and output data are imprecise. Second, it is necessary to use the weight restrictions in order to consider the management view. Third, the decision maker needs to find the best decision making units (DMUs). In the traditional DEA model, it is supposed that the input and output data are precise and the weights are free. This paper proposes a new mixed integer assurance-region imprecise DEA (AR-IDEA) model to find the best DMU by solving only one model. Also, a new algorithm is developed to find... 

Efficient utilization of renewable generation inside microgrids remains challenging. In most existing studies, the goal is to optimize the energy cost of microgrids by working in synergy with the main grid. This work aimed at maximizing the self-consumption of on-site photovoltaic (PV) generation using an electrical storage, as well as demand response solutions, in a building that was also capable of interacting with the main grid. Ten-minute resolution data were used to capture the temporal behavior of the weather. Extensive mathematical models were employed to estimate the demand for hot-water consumption, space cooling, and heating loads. The proposed framework is cast as mixed-integer... 

Large customers are considered as major flexible electricity demands which can reduce their electricity costs by choosing appropriate strategies to participate in demand response programs. However, practical methods to aid the large customers for handling the complex decision making process for participating in the programs have remained scarce. This paper proposes a novel decision-making tool for enabling large customers to determine how they adjust their electricity usage from normal consumption patterns in expectation of gaining profit in response to changes in prices and incentive payments offered by the system operators. The proposed model, formulated as a mixed-integer linear... 

This study proposes an optimal day-ahead (DA) electricity market offering model for a virtual power plant (VPP) formed by a mix of renewable distributed energy resources along with energy storage, such as electric vehicles. Two sources of uncertainty are considered, namely, wind power generation, modelled by an uncertainty set, and DA market price, modelled by scenarios. Opposite to classical robust optimisation approaches, the authors model maps minimal (worst-case) profits to a conservativeness parameter, while the classical robust optimisation maps conservativeness parameter to worst-case profits. In this regard, by using their optimisation framework, a VPP operator only deals with... 

In the past decade, enhancing the reliability of distribution networks by means of optimal switch placement has attracted much attention. In the case of failures in a distribution feeder, such disconnect switches will isolate the faulted section, and the customers downstream of the faulted point can be supplied by neighboring feeders through tie lines. Nevertheless, such reserve branches not only might experience failures themselves but also may not even exist prior to the switch placement. Accordingly, this paper presents a mathematical-programming-based model for the concurrent placement of disconnect switches and tie lines in the distribution networks to enhance the service reliability,... 

Extreme weather events can devastate parts of power grids. Thus, the appropriate post-disaster reaction is a crucial duty for power utilities. To address this important concern, a new two-stage framework is proposed in this paper. Stage I optimally coordinates disaster mutual assistance between affected and supporting utilities. To this end, distance between the damaged and supporting utilities, extent of damage, and repair resources are taken into consideration as decision criteria. Then, a novel formulation in the form of mixed integer linear programming (MILP) is developed for mutual aid management problem. The results of stage I are used as inputs to stage II. A new multi-horizon... 

This article proposes a new three-stage stochastic framework for dealing with predictable two-phase natural disasters in distribution systems. This framework is a multiobjective optimization, in which the amount of curtailed energy, the number of switching actions, and the vulnerability of operational components are selected as the main criteria for decision-making process. The optimization problem is formulated in the form of a stochastic mixed-integer linear programming (MILP) problem. In this article, a windstorm event followed by flooding is analyzed as a two-phase natural disaster. In this regard, the uncertainties associated with gust-wind speed, floodwater depths, and load demands are... 

This paper proposes a transient stability constrained controlled islanding (TSC-CI) approach against cascading events in power systems. Using the wide area measurements, the proposed islanding algorithm is implemented regarding the actual dynamic conditions of the resulted islands. Since the main concern, right after the execution of controlled network splitting, is the transient stability of synchronous machines, a transient energy function is utilized for proper network partitioning. The proposed transient stability criterion is expressed as a function of the transfer impedance between each pair of generators in the resulted islands. Transfer impedance between each pair of coherent... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a...