Sharif Digital Repository

The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demand response programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market... 

Due to the liberalization of the electricity market and the introduction of distributed generation (DG), the importance of distribution loss allocation (LA) has increased. This paper presents a new method for distribution power LA in radial systems. The proposed method, which is based on the results of power flow and considers active and reactive power flows of lines for LA, is composed of three steps. In the first step, starting from the source nodes (i.e., the nodes whose generation is more than their load), the power loss allocated to all nodes is calculated and then the power loss allocated to the loads connected to each node is obtained. In the next step, the total power loss is... 

A new risk-constrained bidding curve construction method is presented in this paper. A Day-ahead energy market has been chosen for competition of GenCos and the Information Gap Decision Theory (IGDT) is used for modelling the Day-ahead market price uncertainty and its corresponding risk. The bilateral contracts of the GenCo are also considered in the proposed framework. A Bi-level optimization problem is incorporated in the proposed method to guarantee a pre-specified level of revenue. The proposed IGDT based method constructs the non-decreasing bidding curve while dispatching units based on the uncertain forecasted prices of the next-day market. The verification of the proposed method is... 

The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization... 

This paper presented a combined scheduling and bidding algorithm for constructing the bidding curve of an electric utility that participated in the day-ahead energy markets. Day-ahead market price uncertainty was modeled using non-probabilistic information gap decision theory (IGDT). The considered utility consisted of generation units and a retailer part; the retailer part of the utility and its demand response program (DRP) could affect the utility's profit, which should be considered in the bidding strategy problem. The bidding strategy algorithm proposed in this paper dispatched units by optimizing the demand response programs of the retailer part. In addition, non-decreasing bidding... 

One of the major problems in liberalized power markets is loss allocation. In this paper, a different method for allocating transmission losses to pool market participants is proposed. The proposed method is fundamentally based on decomposition of loss function and current projection concept. The method has been implemented and tested on several networks and one sample summarized in the paper. The results show that the method is comprehensive and fair to allocating the energy losses of a power market to its participants  

The growing trend of electric vehicles (EVs) in recent years has led to the emergence of EV aggregators in electricity markets. Generally, the main goal of an EV aggregator is to buy electricity from the wholesale market in a cost-effective manner while satisfying the charging requirements of EV owners. Accordingly, this paper presents a decision support tool for EV aggregators which enables them to determine the optimal bidding strategy to effectively participate in the day-ahead and real-time energy, and frequency regulation markets. Indeed, the aggregator mainly obtains profit by selling energy during the high-price hours (via vehicle-to-grid (V2G) capability) and providing primary... 

This paper presents a framework for expansion planning studies of distributed energy storage systems (DESSs) in high wind penetrated power systems. The main objective is to find optimal location and capacity of DESSs in the viewpoint of independent system operator (ISO) while ensuring the maximum usage of wind farms output generation. Three different criteria are introduced for expansion planning studies. Minimizing wind curtailment cost together with transmission congestion cost are considered to properly deal with the issues associated with the curtailment of wind energy and constraints of transmission network. Furthermore, the minimum normalized profit for all DESSs' owners needs to be... 

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... 

This paper presents the application of a fuzzy logic controlled Static Compensator (STATCOM) to improve stability of power system. The nonlinear fuzzy logic controller is used to overcome the problems generated by different uncertainties exist in power systems. Different input variables are used to design the controller. Parameters of the proposed controller are adjusted by means of Neural Network techniques to improve performance of the system. Proposed controller is implemented on a single machine infinite bus system to confirm the performance of the controller through simulation results  

In this paper a fuzzy logic based controller for STATCOM is used to improve power system transient stability. As opposed to the modern control theory, fuzzy logic design is not based on the mathematical model of the process. The controller designed using fuzzy logic implements human reasoning that can be programmed into fuzzy logic language (membership functions, rules and the rule interpretation). The nonlinear fuzzy controller is proposed to supply a supplementary control signal to STATCOM to increase the critical clearing time and overcome the uncertainties existing in the power systems. Proposed method is implemented in a single machine infinite bus system and the results are compared... 

After a natural disaster, there is an urgent need to supply critical loads such as hospitals as soon as possible. Microgrid (MG) formation is one of the quickest ways to achieve this goal. However, in MG formation studies, there is a trade-off between maximizing the amount of restored loads and minimizing their risk of interruption due to the following aftershocks. For the former objective, the minimum number of MGs should be formed, whereas, for the latter objective, the maximum number of MGs should be configured. This paper tackles this contradictory situation by considering the failure risk of distribution feeders in its proposed optimization framework. In this paper, at first, a novel... 

The main purpose of this study is to provide the heating power for space heating and sanitary hot water for a residential house in sixteen stations located in Belgium using evacuated tube solar water (ETSW). A one-year dynamic simulation was performed using TSOL 5.5 software and Meteonorm 7.1 was used to obtain the climatic data. Technical and environmental studies as well as station rankings are the parameters that have been examined for the first time in the present study. The weighting results of using the Best-Worst method (BWM) revealed that total solar fraction and CO2 emission avoided have the highest and lowest weight, respectively. Station ranking was performed using ARAS technique...