Abstract
Participation of consumers in Demand Response (DR) programs improves system stability and reliability as well as market efficiency. Retailers and distributors purchase DR to advance business and system reliability, respectively. Meanwhile, large consumers, Distribution System Operators (DSOs), Load Service Entities (LSEs), and DR aggregators sell DR to increase their own profits. In this context, DR aggregators are key elements of power systems that enhance the participation of consumers in electricity markets. These market participants can negotiate their aggregated DR with other market players in Demand Response eXchange (DRX) markets, and participate in the energy and ancillary service markets. Hence, this paper proposes a stochastic model to optimize the performance of a DR aggregator to take part in the day-ahead energy, ancillary services and intraday DRX markets. In order to mitigate the negative impacts of uncertainties, Conditional Value at Risk (CVaR) is also incorporated to the proposed model. Numerical studies indicate that the proposed model for DR aggregator can arrange its offering/bidding strategies to participate in the mentioned markets simultaneously. © 2016 IEEE.

Abstract
The ever increasing environmental concerns together with depletion risk of conventional fossil fuels that can threat the energy independence of energy importing countries have led to more interest in renewable energy sources of locally produced energy. Increase in such sources together with new types of integrated loads has required new concepts to operate bulk electricity power grid. Accordingly, a relatively new concept - the smart grid - has been widely publicized recently with huge investments of both developed and developing country governments in this area. The smart grid concept is currently in the test phase and insular grids have been generally considered as one of the most suitable structures to evaluate the applicability of "smart" solutions. Thus, the general structure and applicable smart grid based strategies are presented in this study to promote the overall operating performance of such systems. The opportunities as well as the possible challenges of smart solutions are discussed, and the future requirements are evaluated.

Abstract
This paper introduces a control strategy for assessing the role of shunt active power filters (SAPF) in electrical power networks. The proposed control scheme is based on the Lyapunov control theory and defines a stable operating region for the interfaced converter during the integration with utility grid. The compensation of instantaneous variations of reference current components in the control loop of SAPF in ac-side, and dc-link voltage oscillations in dc-side of the proposed model, is considered accurately, which is the main contribution of this work in comparison with the other potential control approaches. The proposed control scheme can confirm the injection of all the harmonic current components and reactive power of grid-connected loads with a fast dynamic response, and a unity power factor between the grid currents and voltages. An extensive simulation study is performed, assessing the effectiveness of the proposed control plan in the utilization of SAPF in power networks.

Abstract
This study proposes a model for the prediction of smart household load demand influenced by a dynamic pricing demand response (DR) program. Price-based DR programs have a considerable impact on household demand pattern due to the expected choice of customers or their home energy management systems (HEMSs) to use more energy in low price periods in order to reduce their electricity procurement cost. Many studies in the literature have dealt with power prediction, but the authors are prior in the field attempting to include the impact of different DR strategies on load demand prediction of smart households. The proposed methodology is expected to be valuable for utilities, retailers, aggregators, etc., in order to evaluate the success of their price-based DR strategies and predict adverse effects such as power peaks in normally off-peak periods and stress of infrastructure.

Abstract
This paper deals with a control concept for enhancing the stable operation of microgrid plan during the grid connected and islanding modes. The Lyapunov control theory is considered in this paper to analyze the dynamic behavior of distributed generation (DG) units during the power sharing with utility grid and loads. The compensation of instantaneous variations in the reference current components of DG units in ac-side and dc-voltage variations in dcside of the interfaced converters are considered properly in this control scheme, which is the main contribution of this work in comparison with the other potential control strategies. By utilization of the proposed control scheme, DG units can provide the continuous injection of active power from the dispersed energy sources to the local loads and/or main grid during the islanding and grid-connected modes. Furthermore, reactive power and harmonic current components of loads can be provided with a fast dynamic response in a stable operational region. Simulation results confirm the effectiveness of the proposed control strategy in the proposed microgrid plan during the dynamic and steady-state operating conditions.

Abstract
Environmental issues raised by the use of fossil fuels lead to the search for alternatives that promote the reduction of emissions of greenhouse gases. CO2 has been identified as being the most important and urgent to control. Co-firing is a technique that allows the simultaneous combustion of different types of fuels, for example coal and biomass, combining the advantages of both. This study characterises the advantages of the system and the possibilities of using waste biomass as fuel in a coal-fired thermal power plant. For this, co-firing biomass waste, from forestry operations, with bituminous coal was simulated. Then reductions in CO2 emissions into the atmosphere from Sines Thermal Power Plant in Portugal were calculated, showing a reduction of more than 1,000,000 tons/year of CO2. Also it was verified that although environmentally advantageous, co-firing is still not economically viable due to the high cost of the residual biomass, combined with its low-energy density and high transportation costs.