MATHEMATICAL MODEL FOR OPTIMIZING PROJECT MANAGEMENT OF IoT SOLUTION IMPLEMENTATION IN SMART GRID BASED ON A HYBRID APPROACH

Abstract

The paper addresses a relevant scientific and applied problem related to improving methods and models for managing projects of development and implementation of Internet of Things (IoT) solutions in energy systems (Smart Grid). Existing approaches to IT project management mostly focus either on ensuring a high level of flexibility in the development process, which is typical of adaptive methodologies, or on a strictly regulated, sequential model of project implementation stages, which is typical of traditional approaches. At the same time, such methods often do not fully take into account the specific features of IoT projects, which function as complex cyber-physical systems and require integrated management of both software and hardware components, network interaction, real-time data processing, and ensuring the reliability of physical devices. It is demonstrated that the exclusive use of either Agile or Waterfall methodologies in critical infrastructure environments is ineffective due to high integration risks and strict industry certification requirements. A specialized mathematical model for multi-criteria optimization is developed, which for the first time formalizes the nonlinear relationship between project release size, system architectural complexity, and the associated costs of compliance, verification, and validation procedures. Using methods of mathematical analysis, equations are derived to calculate the optimal increment size that minimizes the total project cost. Numerical simulation confirms the existence of a clearly defined optimum, thereby providing a mathematical justification for the feasibility of applying hybrid (Agile + Stage-Gate) frameworks. The obtained results provide project managers with an objective analytical toolkit for structuring the stages of cyber-physical system implementation while minimizing the risks of budget overruns and schedule delays.

Keywords: project management, Internet of Things (IoT), Smart Grid, hybrid methodology, mathematical modeling, multi-criteria optimization, release size, cyber-physical systems, integration complexity, compliance.