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  1. null (Ed.)
    Despite the increasing level of renewable power generation in power grids, fossil fuel power plants still have a significant role in producing carbon emissions. The integration of carbon capturing and storing systems to the conventional power plants can significantly reduce the spread of carbon emissions. In this paper, the economic-emission dispatch of combined renewable and coal power plants equipped with carbon capture systems is addressed in a multi-objective optimization framework. The power systems flexibility is enhanced by hydropower plants, pumped hydro storage, and demand response program. The wind generation and load consumption uncertainties are modeled using stochastic programming. The DC power flow model is implemented on a modified IEEE 24-bus test system. Solving the problem resulted in an optimal Pareto frontier, while the fuzzy decision-making method found the best solution. The sensitivity of the objective functions concerning the generation-side is also investigated. 
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  2. null (Ed.)
    In the recent years, due to the economic and environmental requirements, the use of distributed generations (DGs) has increased. If DGs have the optimal size and are located at the optimal locations, they are capable of enhancing the voltage profile and reducing the power loss. This paper proposes a new approach to obtain the optimal location and size of DGs. To this end, exchange market algorithm (EMA) is offered to find the optimal size and location of DGs subject to minimizing loss, increasing voltage profile, and improving voltage stability in the distribution systems. The effectiveness of the proposed approach is verified on both 33- and 69-bus IEEE standard systems. 
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  3. null (Ed.)
    This paper presents a multi-objective (MO) optimization for economic/emission dispatch (EED) problem incorporating hydrothermal plants, wind power generation, energy storage systems (ESSs) and responsive loads. The uncertain behavior of wind turbines and electric loads is modeled by scenarios. Stochastic programming is proposed to achieve the expected cost and emission production. Moreover, the carbon capture systems are considered to lower the level of carbon emission produced by conventional thermal units. The proposed optimization problem is tested on the IEEE 24-bus case study using DC power flow calculation. The optimal Pareto frontier is obtained, and a fuzzy decision-making tool determined the best solution among obtained Pareto points. The problem is modeled as mixed-integer non-linear programming in the General Algebraic Modelling System (GAMS) and solved using DICOPT solver. 
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  4. null (Ed.)
    Due to the dependency of electric loads on the voltage, the load consumption can be controlled by controlling the voltage level. Optimal voltage regulation can benefit the distribution system by reducing the costs of purchasing electric power in the conservation voltage reduction (CVR) mode and increasing the sold energy income in the optimal voltage increase mode. Moreover, implementing demand response programs (DRP) is an effective way to decrease the costs and increase the profit of utilities and customers. This paper investigates the impact of incentive-based DRP and CVR on the operation of the distribution system under different objective functions. The cost of electricity consumption, the profit obtained by the electricity market, and system reliability are the three objective functions. Respect to the considered objective functions, eight scenarios are studied, and their results are compared. Finally, the obtained results validate the method and confirm the positive effect of simultaneous DRP and CVR. 
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  5. null (Ed.)