In recent year, the awareness of environmental protection has made the power dispatch problem not necessarily economy-oriented. This thesis proposed the application of Particle Swarm Optimization (PSO) algorithm to solve the Unit Commitment (UC) problem for 24 hours with maximum profit in the power and carbon market. Optimal Power Flow (OPF) is used to solve the UC problem for the interconnected power network that is comprised of three independent areas to optimize the dispatching strategy. The UC problem must satisfy the constraints of the load demand, generating limits, minimum up/down time, ramp rate limits, and also the limits of power flow, buses voltage and transmission line capacity. The other objective of this thesis is to employ the Static Synchronous Series Compensator (SSSC) to integrate with OPF based on Equivalent Current Injection (ECI) power flow model, and install it at interconnected lines between each independent area controlling the power flow to reduce emission. In order to avoid the local optimality problem, this thesis proposed the utilization of the Multiple Particle Swarm Optimization (MPSO), which can quickly reach the optimal solution with a better performance and accuracy. The Independent Power Producer (IPP) can get the maximum profit with installed SSSC from the power and carbon trading with the calculation of power wheeling expense and carbon forecasting data. Furthermore, it can also assess the need of participating in the trading market or not.