An industrial park is one of the typical energy consumption schemes in power systems owing to the heavy industrial loads and their abilities to respond to electricity price changes. Therefore, energy integration in the industrial sector is significant. Accordingly, the concept of industrial virtual power plant (IVPP) has been proposed to deal with such problems. This study demonstrates an IVPP model to manage resources in an eco-industrial park, including energy storage systems, demand response (DR) resources, and distributed energies. In addition, fuzzy theory is used to change the deterministic system constraints to fuzzy parameters, considering the uncertainty of renewable energy, and fuzzy chance constraints are then set based on the credibility theory. By maximizing the daily benefits of the IVPP owners in day-ahead markets, DR and energy storage systems can be scheduled economically. Therefore, the energy between the grid and IVPP can flow in both directions: the surplus renewable electricity of IVPP can be sold in the market; when the electricity generated inside IVPP is not enough for its use, IVPP can also purchase power through the market. Case studies based on three wind-level scenarios demonstrate the efficient synergies between IVPP resources. The validation results indicate that IVPP can optimize the supply and demand resources in industrial parks, thereby decarbonizing the power systems.