Multi-Objective Optimal Configuration of the CCHP System

Abstract

The combined cooling, heating and power (CCHP) system not only has high energy efficiency but also has different load structures. Traditional separate production (SP) system and power supply system do not consider the land cost in terms of the environmental benefits, and in the aspect of the power supply reliability, the grid-connected inverter cost is also ignored. Considering the deficiency of the traditional energy supply system, this paper builds the CCHP system construction cost model. The particle swarm optimization (PSO) is adopted to find out the minimum value of the construction cost, and the optimal system construction scheme is constructed from three aspects which are system reliability, economic benefits and environmental benefits. In this paper, the typical daily data, as well as the meteorological data and the load data, in the last four years are taken as experimental dataset. The experimental results show that compared with the traditional SP system and power supply system, the CCHP system established in this paper not only achieves lower cumulative investment cost, but also has a good power supply reliability and environmental benefits.

Study on Integrated Demand Response Strategy and System Coordination and Optimization of Park Integrated Energy System

“…C is the total cost of operating the energy system, M C is the cost of gas turbine production consuming natural gas, BL C is the cost of gas boiler consuming natural gas, NP C is the cost of new energy losses, O C is the cost of purchased electricity, I C is the cost of operation and maintenance of each equipment unit, and IDR C is the cost of integrated demand-side response [4] .…”

Modeling, Control, and Optimization of Multi-Generation and Hybrid Energy Systems

“…The design of the system can be adapted in order to optimize different objective functions. Their study shows that this system is capable of reducing total investment costs, increasing environmental benefits, and increasing system reliability [5]. In terms of operational optimization of CCHP systems, Xu et al proposed a staged optimization strategy designed to help with scheduling of the system.…”

Detecting and Characterizing Multiple Oscillations in Process Control Loop Based on PSO-NCMD

“…PSO [29] is a kind of swarm intelligence optimization algorithm, which imitates the birds' foraging. It has been widely used in various applications, such as controller design [30], [31], optimal scheduling [32], [33], to name a few.…”

“…In order to verify the improvement of PSO on the optimization of NCMD parameters, a synthesized signal (29) is tested as the subject. s = cos (2πt) + cos (10πt) + 2 cos(16πt + 40πt 2 ) + η (29) where η ∈ N (0, 0.1) is noise. The PSO settings are as follows: the maximum iteration number and particle number are 20 and 30, respectively.…”

“…For the sake of contrast, the decomposition performance of VMD and EMD are provided in Figure 7 and 8, respectively. It is observed that both VMD and EMD cannot correctly decompose signal (29), because they are not good at dealing with time-varying signals. Therefore, compared with VMD and EMD, the proposed PSO-NCMD has better performance in processing complex signals.…”