A hybrid optimization approach to analyze the risk-constrained operation of a residential hybrid energy system incorporating responsive loads

Abstract

Hybrid energy systems are developed recently due to their applicability in small scales. This paper presents a hybrid approach to optimize the operation and handle the uncertainties of a residential energy system composed of photovoltaic, fuel cell, boiler and storage units. In this regard, the uncertain parameters are divided into two categories including badly-behaved and well-behaved parameters and then, robust optimization and stochastic programming are utilized for modeling, respectively. As well, conditional value-at-risk is implemented to evaluate the risk of well-behaved parameters. According to the simulations, it is proved that badly-behaved uncertainties have higher impacts on system operation. Moreover, changing the control parameters of robust optimization and conditional value-at-risk from 0 to 24 and 0 to 1 increase the total cost by 5.2% and 0.47%, respectively. The comparative results also show that the proposed hybrid method takes less conservative decisions to optimize cost.