Fast yet balanced trade-offs for multi-timescale multi-objective economic-environmental dispatch under varying conflicts

The conflicts between generation cost and the power generation-induced effects on the environment are always considered to be constant. However, the conflicts can vary with weather conditions and have typical daily fluctuations if the air pollutant dispersion process is considered when minimizing the generation-induced air pollution. Although understanding the conflicting situation by a Pareto front (PF) can contribute to a better economic-environmental balance, the PF calculation is inherently time-consuming and a threat to fast computation, especially when the time granularity is constantly increasing in today’s multi-timescale-based power operation. This paper proposes a novel multi-timescale multi-objective economic-environmental dispatch (MTMO-EED) method to solve the “fast computation or good balance” dilemma from the following two aspects: On the modeling side, we establish a new MTMO-EED framework with intra-day offline–online coordination (IOOC), where the intra-day PF is calculated offline while only a simple single-objective optimization is needed online. We quantify the error bounds of the deviations between the offline estimated PF and the accurate PF induced by offline forecast errors, and then provide explicit operational conditions under which the offline PF can closely approximate the accurate online PF despite the offline forecast errors; On the solution method side, we propose a new multi-objective algorithm, termed basis changing boundary intersection (BCBI), to improve the PF computational efficiency at the day-ahead stage and the intra-day offline stage. Specifically, mathematical properties of the MTMO-EED’s PFs are exploited in the BCBI. Case studies are conducted on a modified IEEE 39-bus system, which validate the proposed method can achieve fast yet balanced economic-environmental trade-offs at both the day-ahead and intra-day stages.