Robust optimal scheduling of CHP-based microgrids in presence of wind and photovoltaic generation units: An IGDT approach

Application of combined heat and power (CHP) units beside the distributed energy resources (DERs) persuades the power systems via the formation of multi-carrier microgrids (MGs). This paper presents the day-ahead scheduling of multi-carrier MGs. Renewable distributed generators are known as undeniable parts of modern power systems, which may increase the chanciness of the system. Information gap decision theory (IGDT) is applied to address the uncertainties of renewable sources. Moreover, a scenario-based stochastic approach is used to model the uncertainty of electricity prices in this method. Indeed a hybrid stochastic-IGDT-based optimization problem is proposed for optimal energy management of multi-carrier MGs. According to this method, the operation of multi-carrier MGs would be robust against uncertainties and contain a minimum profit. The proposed problem has been formulated as mixed-integer linear programming (MILP). Finally, the proposed energy management has been implemented into a sample multi-carrier microgrid. The results showed that how the MG operator's risk-averse character can change her/his decision-making.

Automated summary

This paper presents a day-ahead scheduling method for multi-carrier microgrids, which uses information gap decision theory and a scenario-based stochastic approach to address the uncertainties of renewable sources and electricity prices. It proposes a hybrid optimization problem for optimal energy management, making the operation of multi-carrier microgrids robust against uncertainties. Results show that risk-averse operators can change their decision-making.