Stochastic analysis and reliability-cost optimization of distributed generators and air source heat pumps

This paper presents a framework for stochastic analysis, simulation and optimisation of electric power grids combined with heat district networks. In this framework, distributed energy sources can be integrated within the grids and their performance is modelled. The effect of uncertain weather-operational conditions on the system cost and reliability is considered. A Monte Carlo Optimal Power Flow simulator is employed and statistical indicators of the system cost and reliability are obtained. Reliability and cost expectations are used to compare 4 different investments on heat pumps and electric power generators to be installed on a real-world grid. Generators' sizes and positions are analysed to reveal the sensitivity of the cost and reliability of the grid and an optimal investment problem is tackled by using a multi-objective genetic algorithm.