The "14th Five-Year Plan" proposed the development of strategic emerging industries, accelerate the construction of a modern industrial system of the national major strategic deployment. Therefore, power grid enterprises need to expand new businesses to improve their own benefits. Based on RWCS algorithm, this paper optimizes the portfolio investment decision of emerging business and traditional business of power grid enterprises. Firstly, the key factors and indicators affecting the realization of investment value of emerging business are extracted, and the evaluation system of investment value of emerging business of power grid is proposed. Then, we construct a multi-business portfolio investment decision optimization model for the integration of grid emerging business and traditional business, and solve the multi-business portfolio investment decision optimization model using RWCS algorithm. Finally, the optimal model of emerging business portfolio decision-making is verified with examples to provide reference for grid business investment and support the transformation and upgrading of the grid industry and the company's high-quality development.
For the rough management of the whole process of the project, lean management is needed. First, take the power grid infrastructure project as the entry point, actively carry out cross-departmental data joint analysis, and build a “three rates in one” project investment statistical analysis system for the whole process; second, dig deeply into the internal relationship between project construction progress, investment completion, and recorded cost, and establish a theoretical curve model of the project as an analysis benchmark for the entire process of project execution; finally, determine the reasonable interval of the three-rate deviation of the project, carry out the cross analysis of the theoretical curve and the actual curve, accurately locate the abnormal progress, accurately analyze the abnormal root cause, and realize the project progress deviation dynamic warning.
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