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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... 

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... 

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... 

This paper utilizes data measured by phasor measurement units (PMUs) to extract a low-order dynamic equivalent model for power system stability studies. The estimated model is a 2-order model for synchronous machines. This model has the advantage of simplicity of classical model and considerably reduces the oversimplifying error of classical model. This method offers an alternative approach to analytical model reduction techniques based on the detailed system models. The proposed method uses the synchronized bus voltage and current phasors measured by PMUs. Using post disturbance data, electrical and mechanical parameters of the equivalent generator are estimated sequentially. Furthermore, a... 

Integrating independent dispatchable and non-dispatchable resources into a micro-grid platform enables the main power systems to benefit from the economic and environmental advantages of distributed generation while facilitating local, clean, and inexhaustible renewable energy production. Moreover, it makes the integrated components more visible and controllable for the whole power system. On the other hand, to properly handle multiple uncertainties inherent in the micro-grids, probabilistic energy management techniques are deployed. However, utilization of stochastic modeling and optimization tools for efficient, reliable, and cost-effective planning, operation, and control of micro-grids... 

A comprehensive optimal bidding strategy model has been developed for renewable micro-grids to take part in day-ahead (energy and reserve) and real-time markets considering uncertainties. A two-stage stochastic programming method has been employed to integrate the uncertainties into the problem. Moreover, the Latin hypercube sampling method has been proposed to generate the wind speed, solar irradiance, and load realizations via Weibull, Beta, and normal probability density functions, respectively. In addition, a hybrid fast forward/backward scenario reduction technique has been applied to reduce the large number of scenarios. Furthermore, the risk of participation in the markets has been... 

Food, energy, and water (FEW) resources have high interconnection and interdependencies as each resource can be affected by the other two. Thus, the Nexus approach is introduced and implemented to manage FEW. This chapter discusses each sector of FEW: availability, production, consumption, interaction, and interconnection between them, and finally suggests some action to improve the operation of the Nexus. © Springer Nature Switzerland AG 2020  

This paper proposes a new approach for corrective voltage control (CVC) of power systems in presence of uncertain wind power generation and demand values. The CVC framework deals with the condition that a power system encounters voltage instability as a result of severe contingencies. The uncertainty of wind power generation and demand values is handled using a scenario-based modeling approach. One of the features of the proposed methodology is to consider participation of demand-side resources as an effective control facility that reduces control costs. Active and reactive redispatch of generating units and involuntary load curtailment are employed along with the voluntary demand-side... 

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is... 

The main motivation of this study is to address the challenges due to high penetration of renewable distributed energy resources (DERs) and efficiently benefit from DERs in distribution system planning (DSP). This paper considers a decentralized enhanced platform for DSP which is coordinated with bulk power system planning (PSP) to keep the optimality and security of the whole power system. In the proposed coordinated approach, distribution system operators (DSOs) plan and operate DERs to upgrade their local distribution areas (LDAs), supply forecasting local load growth, and avoid or defer costly generation and transmission expansion planning at the bulk power system. The proposed DSP model... 

Owing to the development of smart grids technologies, including renewable energy resources and integrated demand response, the traditional distribution network undergoes systemic improvements and has become an active system. To meet such changes in technology, the smart distribution grid is highly dependent on communication infrastructures. Although this strong reliance can make the distribution network susceptible to cyber threats, there has been inadequate attention to the distribution network cyber-security. An intruder can disrupt communication and effectively target the distribution management system core functions, leaving the distribution grid susceptible to loss of stability... 

The universal paradigm shift towards green energy has accelerated the development of modern algorithms and technologies, among them converters such as Z-Source Inverters (ZSI) are playing an important role. ZSIs are single-stage inverters which are capable of performing both buck and boost operations through an impedance network that enables the shoot-through state. Despite all advantages, these inverters are associated with the non-minimum phase feature imposing heavy restrictions on their closed-loop response. Moreover, uncertainties such as parameter perturbation, unmodeled dynamics, and load disturbances may degrade their performance or even lead to instability, especially when...