Dynamic Economic Dispatching Strategy Based on Multi-time-scale Complementarity of Various Heterogeneous Energy

Abstract

Large-scale new energy incorporation presents great challenges to the power system economic dispatch. Complementary system can effectively enhance the accommodation of new energy. However, current complementary system day-ahead dispatch models have not considered the actual complementary and smoothing effect. Thus, a dynamic economic dispatch strategy based on multi-time-scale complementarity of wind, solar, hydro and thermal power is proposed. Wind, solar and hydro power is bundled as a virtual power (VP) according to their complementary features. The load tracking index is defined to represent the ability of the VP to track the load so that it can well follow the load curve. Meanwhile, a multi-time-scale complementary dispatch model is established, which includes a day-ahead 24h scheduling, an intra-day 4h rolling scheduling and a real-time 15min scheduling. According to the latest forecast, the day-ahead scheduling is amended continually, the VP output is adjusted continually to maintain its good tracking and the best complementary effect is also achieved. An example is calculated to verify that this strategy can effectively improve the actual complementary and smoothing effect of the complementary system, relieve the dispatch pressure as well as reduce the generation cost.

Assessing temporal complementarity between three variable energy sources through correlation and compromise programming

“…In their study they determined the best geographical locations in terms of complementarity by means of Particle Swarm Optimisation. Zhu et al [37] proposed an economic dispatch strategy based on multi-scale complementary energy sources. These authors proposed an optimisation model, whose objective function was minimising the required output from thermal plants, using as case study data from a power system in southeast China.…”

A review on the complementarity of renewable energy sources: Concept, metrics, application and future research directions

“…Naeem et al (2019) [46] used the Pearson correlation coefficient for assessing solar-wind complementarity in an optimization model whose objective function aims at maximizing economic benefits of a microgrid, by means of exploiting such spatial and temporal energetic complementarity. Some other models dealing with optimization based on complementarity can be found in [42], [44], [68], [75], [91], [92], [93] and [94].…”

“…In their scheduling optimization model, Zhu et al ( 2018) [68] combined wind, solar and hydro power output, and defined this ensemble as a virtual power (VP), according to their complementary features.…”

“…Li et al (2011) [67] using the state of Oklahoma as case study, proposed the Complementarity Index of Wind and Solar Radiation (CIWS), an index that incorporates geographic regression modeling and principal component analysis (PCA) for investigating the impacts of diverse geographic factors on complementarity.In their scheduling optimization model, [68] combined wind, solar and hydro power output, and defined this ensemble as a virtual power (VP), according to their complementary features. Then, the capacity of the VP output to follow the load is measured by the load tracking index.…”

Integration of hybrid renewable energy sources with the power system considering their economic complementarity

“…Paper [25] also conducted a similar study. Paper [26] has presented an economic dynamic dispatch strategy based on multi-time complementation of wind, solar, water, and thermal energy. A load tracking index for the hybrid energy system has been modelled.…”