<p>The large-scale development of new energy not only promotes the transformation of power structure in the power system, but also promotes the development of new resource aggregation and regulation entities such as virtual power plants (VPP). In order to further enhance the resource management capability and market profitability of VPP, this paper proposes a market-oriented joint optimization scheduling strategy that considers management costs, focusing on VPP that aggregates multiple types of power sources and adjustable loads. Based on the assumptions of accurate power and load forecasting and adequate resource response, this paper establishes a mixed integer linear programming model that takes into account management costs, with the objective function of minimizing the total cost of virtual power plants. Furthermore, based on actual data from a certain industrial park, this paper conducts a case study analysis. Adjustable loads include building air conditioning loads, charging stations, and user side energy storage, while distributed power sources include renewable energy sources such as wind power (WT) and photovoltaic (PV). The practical examples have verified the feasibility of the optimization model that incorporates management costs and is applied to optimize different types of adjustable loads and optimizing internal as well as external market-oriented transactions. In scenarios 1 and 2, the strategy proposed in this paper reduces the total cost by approximately 61.6% and 2.2%, respectively, compared to conventional methods. The proposed market-oriented joint optimization scheduling strategy cuts down power purchase and management costs, enhances the renewable energy absorption capacity and provides a reference for further exploring the operation and management methods of VPP.</p>