This research focuses on optimizing energy management in organizations to reduce costs and increase revenues. It emphasizes the importance of proactive, coordinated, and systematic energy utilization, highlighting the necessity of informed decision-making through building management, energy audits, and equipment retrofits. The Combined Compromise Solution (CoCoSo) method, a powerful technique for multi-attribute group decision-making (MAGDM), merges a compromise decision algorithm with an aggregation strategy to achieve a balanced solution. In MAGDM, the type of information is crucial, as effectively addressing uncertainty in the information type leads to better outcomes. The Pythagorean Linguistic Number (PLN) is an effective tool for managing uncertainty related to information. This research extends the original CoCoSo approach to operate within a PLN context, thus enhancing its applicability in addressing qualitative decision-making problems under quantum decision theory (QDT). We propose an innovative CoCoSo methodology using QDT within a PLN-based framework, demonstrating flexibility and scalability that extend beyond QDT. The method’s superior performance and resilience are validated in the context of sustainable solar energy management.