Multi-objective energy management system in multi-energy communities based on optimal user clusters of multi-agent systems
A technology of multi-agent system and energy management system, applied in the field of multi-objective energy management system, can solve problems such as difficult to realize collaborative optimization of MEC energy utilization mode, does not consider the similarities and differences of different energy consumption groups, single optimization objective, etc., to maximize Effects of using green energy, reducing energy loss, and improving energy quality
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Embodiment 1
[0121] see Figure 1 to Figure 5 , a multi-objective energy management system in a multi-energy community based on the optimal user cluster of a multi-agent system, including a user cluster module, a multi-agent module, and an energy scheduling module to achieve energy quality optimization, energy price optimization, energy consumption optimization, The purpose of green energy utilization optimization.
[0122] The user clustering module clusters users to obtain several optimal user clusters.
[0123] The correlation matrix between two user clusters is denoted as Correlation matrix The eigenvalues of are recorded as The correlation matrix between two time series profiles in the same user cluster is denoted as Correlation matrix The eigenvalues of are recorded as
[0124] Correlation matrix Entropy of eigenvalues Correlation matrix eigenvalue They are as follows:
[0125]
[0126]
[0127] where K is the number of MECs. p is the time node.
[01...
Embodiment 2
[0227] see Figure 1 to Figure 5 , a multi-objective energy management system in a multi-energy community based on the optimal user cluster of a multi-agent system, the contents are as follows:
[0228] The MAS-based MEC structure proposed in this embodiment is as follows figure 1 shown. The MEC diagram is composed of various energy supply agents, including PV agents, WT agents, ESS agents, thermal agents, and gas agents that constitute the virtual energy center; relevant load agents represent thermal, electrical, and gas loads . The virtual energy center can play the dual role of energy supply and load according to the real-time demand of the energy center. The agents associated with each unit are responsible for collecting local information, transforming information, formulating energy scheduling schemes and executing energy management decisions. At the same time, CEMS will be responsible for forecasting day-ahead load, collecting all generation / demand information, and m...
Embodiment 3
[0318] A multi-objective energy management system in a multi-energy community based on the optimal user cluster of a multi-agent system, the contents are as follows:
[0319] Within the same MEC, there will be multiple clusters of consumers with different energy usage profiles and preferences. Therefore, these four optimization objectives are coordinated to make them applicable to multiple MECs with mixed consumption clusters.
[0320] The proposed coordination strategy for the four optimization objectives is as follows: image 3 shown. When allocating energy reserves to HEMS, optimization objective 4) (energy quality) will be prioritized, since high energy quality can only be ensured if the energy reserves are sufficient. Therefore, optimization objective 4) will be accomplished first when allocating household energy reserves, and the energy curve will be at the bottom of the total energy curve, as in image 3 shown. At the same time, an adjustable range will be reserved,...
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