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The stochasticity and volatility of renewable energy have become a major stumbling block to its widespread use. Complementary wind-CSP energy systems (WCES), which are consisted of low-cost wind power and dispatchable concentrating solar power (CSP) with thermal energy storage (TES), are developed to mitigate renewable energy generation instability effectively. Successful implementation of a WCES requires determining two key issues: the installed TES capacity in the system and the energy dispatch strategies in different price modes. This paper proposes a two-stage WCES decision-making framework for coordinating thermal energy storage capacity planning and energy dispatch through multi-channels: wind, solar, and TES. In the first planning stage, we proposed a stochastic model to solve the TES capacity planning problem, which considers the construction cost, the unstable supply of energy resources, and the future production dispatch of WCES. Given the TES capacity determined in the planning stage, another stochastic model is developed in the second operating stage to solve the WCES energy dispatch problem, which determines the real-time energy dispatching by considering the real-time energy supply, demand, and electricity price. The two stochastic models are converted into MILP models using scenario-based and linearization methods. The results show that the proposed models are effective. With further consideration in carbon emission control for the capacity planning, we suggest reserving an additional 20% of the existing optimized capacity for a tighter policy. We show the optimal energy dispatch strategy for the dispatch strategy is to dispatch wind power first, then solar power, and reserve TES energy for power shortage. We also show that the WCES could seize more energy arbitrage opportunities among the three different electricity price models and obtain more benefits in the real-time electricity price model. [ABSTRACT FROM AUTHOR]