A host of technologies has been developed to achieve these aims of the smart grid. Some of these technologies include plug-in electric vehicle, demand response program, energy storage system and renewable distributed generation. However, the integration of the smart grid technologies in the power system operation studies such as economic emission unit commitment problem causes two major challenges. Pumped storage unit with the capability of storing energy can provide spinning reserve and consequently decrease total cost and environmental emission. The goal of this study is to develop and examine a hybrid GA-heuristic and deterministic optimization algorithm for solving the UC problem for a smart grid with considerations for pumped storage as an energy storage system. Simulation results show improvements in total cost and environmental emission by 1.27 and 4.09%, respectively. Manuscript profile

In an electricity market, every generation company (GENCO) attempts to maximize profit according to other participants bidding behaviors and power systems operating conditions. The goal of this study is to examine the optimal bidding strategy problem for GENCOs in energy and spinning reserve markets based on a hybrid GA-heuristic optimization algorithm. The heuristic optimization algorithm used in this study is successfully applied for validation and, it is determined that the heuristic optimization algorithm improves profits of a GENCO by 4.15-47.95% and 20.84-31.30% in single-sided and double-sided auctions, respectively. Manuscript profile

The integration of renewable wind and pumped storage with thermal power generation allows for dispatch of wind energy by generation companies (GENCOs) interested in participation in energy and ancillary services markets. However, to realize the maximum economic profit, optimal coordination and accounting for reduction in cost for environmental emission is necessary. The goal of this study is to develop a simulation model for maximizing economic profit from coordination of renewable wind and pumped storage with thermal power generation for a GENCO with participation in energy and ancillary services markets with considerations for environmental emission and uncertainty associated with wind power based on a newly developed GA-based heuristic optimization algorithm. It is determined that for a GENCO with 13 MW wind farm capacity and 1662 MW thermal units, for meeting an average demand of 1129 MW, the utilization of 120 MW pumped storage in a coordinated wind-pumped storage-thermal system results in reduction of environmental emission by 13.54%, which leads to an increase in profit by 2.10%, as compared with operation with no pumped storage unit. Manuscript profile

Combined cooling, heat, and power (CCHP) units can be integrated with conventional separate cooling, heat, and power production units to meet demands. The goal of this study is to develop and examine a hybrid GA-heuristic optimization algorithm for solving the unit commitment problem for integrated CCHP-thermal-heat only system with considerations for electricity boiler. When environmental emission cost and valve-point effects are considered, the utilization of CCHP units in an integrated CCHP-thermal-heat system results in environmental emission and total cost reduction by and 38.37 and 0.03% respectively. Also, using electricity boiler, environmental emission and total cost reduction of 0.53 and 0.03 are reached, respectively. Manuscript profile