Abstract
This paper contrasts the Genetic Algorithm (GA) strategies to solve the problem of Economic Dispatch (ED) in a Microgrid (MG). An environmental ED strategy for MG is proposed through maintaining the system reliability requirements at acceptable level. Two additional cost terms such as the CO2 emission penalties and load curtailment charges are added to the traditional objective function of the ED problem. Also, cost and reserve supply of the network are considered. Since the load curtailment cost is highly dependent to the network reliability indices, specifically those determining network inability to supply demand, the Expected Energy Not Served (EENS) reliability index is used to calculate the curtailment costs. By illustrating the advantages of Inherit Based Genetic Algorithm (IBGA) over the other two strategies, namely Simple Genetic Algorithm (SGA) and 3-matrices Genetic Algorithm (3MGA), IBGA is used to solve the proposed Reliable, Environmental Economic Dispatch (REED) problem in a MG.

Abstract
This paper demonstrates day-ahead operation of power systems in the presence of a Demand Response Program (DRP) for serving exact amounts of demanded energy over the operational horizon. The proposed two-stage model features a here-and-now framework for shaping the aggregated demands during operation. First, the day-ahead scheduling problem is solved by adopting Unit Commitment (UC) to determine the generation level of power generation units as well as the Locational Marginal Prices (LMPs). Afterwards, the obtained LMPs are considered as the Time of Use (ToU) for the second step of the scheduling and reshaping the demanded loads of each aggregator. A new methodology is provided in this paper to estimate the reaction of consumers behavior in terms of encouraging their participation in DRPs. Unlike classical models which adopt load reduction over the operational horizon, this model ensures that the total demanded loads will be served. Therefore, the total supplied energy for the operational period before and after DRP implementation remains unchanged. Meanwhile, the total payment of consumers will be considerably reduced by adopting this strategy. The simulation results on the 6-bus test system clarify that the proposed model can reduce the total operational cost as well as smoothen the load profile and nodal prices over the operational horizon.

Abstract
This study aims to evaluate the implications of the use of maritime pine non-debarked wood chips as an alternative solid fuel in industrial boilers in Portugal, highlighting the energy properties and chemical composition of the produced ash. Several samples are collected from different sources, on which a proximate analysis is carried out in order to determine the volatile matter content, fixed carbon content, ash content and higher heating value (HHV). The chemical composition of the ash samples is determined by the scanning electron microscope (SEM) method. Then, empirical indices were used to assess the utilization of the ash and its tendency to create slagging and fouling deposits in industrial boilers during the combustion process. It was concluded from the obtained results that the use of maritime pine non debarked wood chips can significantly contribute to the formation of slagging and fouling phenomena in industrial boilers. These phenomena will be responsible for a higher number of technical stoppages of the equipment and for an increase in maintenance costs.

Abstract
In this study, a non-probabilistic program is proposed to a trading framework for demand response (DR) aggregators. Both sides of the aggregator, including upper side and down side of this entity, have been taken into account. In the down-side of the aggregator, two popular programs are considered such as reward-based program and time-of-use (TOU) program, where DR is obtained from these resources. The acquired DR is being sold to the purchasers in the other side of the aggregator through DR options and fixed DR contracts. To the aim of increasing the desired target profit of risk-seeker aggregator, an opportunity function of information-gap decision theory (IGDT) is used to handle the uncertainty, which is solved in General Algebraic Modeling System (GAMS) software. This model is implemented in a realistic case study.

Abstract
As a contribution for sustainability, electric vehicles (EVs) are seen as one of the most effective influences in the transport sector. As complement to the challenges that entails the EVs integration into the grid considering the bidirectional operation (grid-to-vehicle and vehicle-to-grid), there are new concepts associated with the EV operation integrating various benefits for smart homes. In this sense, this paper proposes an improved voltage control of the EV operating as uninterruptible power supply (UPS) in smart homes. With the EV plugged-in into the smart home, it can act as an off-line UPS protecting the electrical appliances from power grid outages. Throughout the paper, the foremost advantages of the proposed voltage control strategy are comprehensively emphasized, establishing a comparison with the classical approach. Aiming to offer a sinusoidal voltage for linear and nonlinear electrical appliances, a pulse-width modulation with a multi-loop control scheme is used. A Kalman filter is used for decreasing significantly the time of detecting power outages and, consequently, the transition for the UPS mode. The experimental validation was executed with a bidirectional charger containing a double stage power conversion (an ac-dc interfacing the grid-side and a dc-dc interfacing the batteries-side) and a digital stage. The computer simulations and the acquired experimental results validate the proposed strategy in different conditions of operation. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
Wind energy sources have created new challenges in power system scheduling to follow the network load. Gas fired units with high ramping could better deal with inherent uncertainties of wind power compared to other power generation sources. The natural gas system constraints affect the flexibility of natural gas- fired power plants in the electrical market. In this paper, three solutions have been proposed to cover the challenges of gas system constraints and the uncertainty of wind power: 1) using information-gap decision theory (IGDT) based robust approach to address the uncertainty caused by the intrinsic nature of wind power, 2) Integration of compressed air energy storage (CAES), and demand response (DR) in day-ahead scheduling and 3) considering flexible ramping products in order to ensure reliable operations, there must be enough ramp to eliminate the variability of wind power in real-time dispatch stage. This paper proposes an IGDT-based robust security constrained unit commitment (SCUC) model for coordinated electricity and natural gas systems with the integration of wind power and emerging flexible resources while taking the flexible ramping products into account. Numerical tests demonstrate the effect of emerging flexible resources on a reduction of system operation cost and the uncertainty of predicted wind power.