An Regional Market Manager (RMM) is supposed to take into account a variety of items including the participants in the market, technical constraint, price variation/reaction, electricity-price uncertainty, and types of the applied demand response program, to name a few. One of the demand response programs is Emergency Demand Response Program (EDRP) which is employed in this paper. In the present study, the objective function of the RMM is formulated in a market environment in order to determine the optimal demand, incentive, and power purchased with considering some of technical constraints such as incentive limits, demand limits, power purchased, and power balance. Co-evolutionary Improved Teaching Learning-Based Optimization (C-ITLBO) is applied to maximize the RMM's prot. In addition, the demand level in the EDRP is determined based on a logarithmic model that includes Price Elasticity Matrix (PEM). The reserve supplied due to Aggregators (AGGs) is also prioritized using Reserve Margin Factor (RMF). Further, Information-Gap Decision Theory (IGDT) is applied to model uncertainty in the initial electricity price. The above-mentioned items are modeled in a multi-level formulation

Operation scheduling of a Virtual Power Plant (VPP) includes several challenges for the system according to the uncertain parameters, and security requirements, which intensify the need for more efficient models for energy scheduling and power trading strategies. Making suitable Decisions under uncertainties, related to Renewable Energy Resources (RES), loads, and market prices impose extra considerations for the problem to make a clearer insight for the system operators to participate in local markets. This paper proposes a new risk-based hybrid stochastic model to investigate the effects of wind turbine power fluctuations on profit function, energy scheduling, and market participating strategies. Also, an incentivized Demand Response Program (DRP) is used, to enhance the system’s efficiency. The results of the study indicate that the proposed model based on Information Gap Decision Theory (IGDT) approach makes a clearer environment for the Decision-maker to be aware of the effects of risk-taking or a risk-averse strategy on financial profits. The results show that a 30% of robustness and opportunity consideration would change the profit function from -12.5% up to 14.5%, respectively. A modified IEEE 33 bus test system is used to simulate a technical VPP considering the voltage stability and thermal capacity of line requirements.

The integration of the distributed energy resources into a single entity can do with virtual power plants. VPP is a cluster of dispatchable and non-dispatchable resource with flexible loads which distributed in allover the grid that aggregated and acts as a unique power plant. Flexible load is able to change the consumption so demand response program is applied to use them to improvement of the power system performance. Virtual power plant generation has uncertainty and it make hard to schedule the VPP. To deal this matter Information Gap Decision theory hint us to optimal schedule of the VPP. To show the effects of VPP and DRP on power system operation cost a bi-level unit commitment with regard the VPPs and DRP is solved in modified IEEE 24 bus reliability test system. Results in presence of VPP and DRP in both IGDT strategies are compared with disregard VPP and DRP and effectiveness of the proposed model is reflected.

This study compared the effect of Information Gap and opinion Gap tasks on introvert and extrovert EFL learners‟ speaking. Accordingly, 138 learners out of 180 intermediate learners were chosen through their scores on a sample Preliminary English Test (PET). These learners further responded to the Eysenck Personality Inventory (EPI) which categorized them into introverts and extroverts. Altogether, four subgroups were established: 32 introverts and 37 extroverts undergoing the opinion Gap task instruction and 33 introverts and 36 extroverts experiencing the Information Gap task treatment. All groups received 10 sessions of treatment and at the end sat for another sample PET speaking section as the posttest. A two-way ANOVA was run to respond to all the four questions showing that while extrovert learners benefited more from opinion Gap tasks, introverts outperformed extroverts as a result of Information Gap tasks. The findings support the notion of using appropriate tasks for different personalities.