Distributed energy systems (DES) can help in achieving less carbon-intensive energy systems through efficiency gains over centralized power systems. This paper presents a novel optimization framework that combines the optimal design and operation of distributed energy systems with calculations of electrical grid constraints and building energy use. The framework was used to investigate whether the negative impact of distributed generation on distribution grids can be mitigated and grid upgrades avoided by properly designing and determining operation strategies of DES. Three new methods for integrating grid constraints were developed based on different combinations of a genetic algorithm and a mixed-integer linear programme. A case study is defined in order to analyze the optimality, accuracy of power flow calculation and solving performance of each method. The comparison showed that each method has advantages and disadvantages and should therefore be chosen based on the application and objectives. The results showed that the electrical grid constraints have a significant impact on the optimal solutions, especially at high levels of renewable energy use, highlighting their importance in such optimization problems. The inclusion of such constraints directly in the operational scheduling achieved an additional 18% reduction in carbon emissions for a given cost compared to checking the validity of solutions a posteriori. Furthermore, by properly designing and determining operation schedules of DES, it is possible to integrated 40% more renewables without grid upgrades. (C) 2016 Elsevier Ltd. All rights reserved.