CHP systems optimal allocation in the interconnected heat and electricity distribution network based on minimizing electrical and heat transfer losses

Abstract

Combined heat and power (CHP) systems are employed to supply electrical and thermal loads of distribution networks (DNs). However, the heat loss can significantly hinder the heat transfer through pipelines from CHP systems to consumers Therefore, the optimal placement and sizing of CHP systems to reduce losses, including electrical and thermal losses, are very crucial. To minimize electrical loss, many methods have been proposed for optimal resource allocation. In this paper, a new approach for the optimal allocation of CHP systems to minimize electrical loss and heat transfer loss (HTL) is presented. Accurate modeling of HTL through the pipeline is performed. The proposed method is applied to 33‐bus, 69‐bus, and 84‐bus test systems. According to the simulation results, it is concluded that considering HTL in the resources optimization problem leads to major changes in the selection of CHP systems' optimal size and location. To solve the optimization problem, a new enhanced imperialist competitive algorithm (E‐ICA) is presented. The proposed algorithm enhances the performance and efficiency of the ICA algorithm by improving exploitation and exploration to prevent getting trapped in local optimums. Comparison of CHP systems allocation results confirms the superiority of the E‐ICA algorithm over other methods.

Optimal energy management of CHP‐based microgrid examining different types of district heating networks

“…The recovered heat of CHP systems is transferred to other busses through the pipelines in order to supply thermal load. In this process, HTL through pipelines is inevitable [38]. The amount of heat losses varies and depends on the material and type of pipeline as well as environmental conditions [33].…”

“…Here, the E-ICA optimization method is introduced to improve the efficiency and performance of the ICA algorithm. This algorithm enhances exploration and exploitation to avoid getting stuck in local minimums [38]. Moreover, direction and velocity parameters are added to the characteristics of colonies in order to make the assimilation process and the movement of the colonies toward their imperialists more intelligent.…”

Reconfiguration of low-voltage distributed power sources within electric power's distribution network based on improved particle swarm-fish swarm fusibility algorithm

“…When the power grid distance is less than 10 km or more than 25 km, the model has the problem of slow data transmission. It is easy to become trapped in a local optimum when operating over expansive distances, resulting in the algorithm being terminated prematurely 4 . To solve this problem, this study creatively optimizes PSO-AF algorithm based on the strategy of mutant Birds (b) and Elite fish (e).…”

Techno-economic and environmental assessments of optimal planning of waste-to-energy based CHP-DG considering load growth on a power distribution network

“…In the work of [ 43 ], a new enhanced imperialist competitive algorithm (E-ICA) was applied for optimal allocation of CHP systems in an interconnected heat and electricity distribution network with the objective of minimising electric and heat transfer losses. Only power loss minimisation was considered.…”

“…Only power loss minimisation was considered. In all the aforementioned references [ 6 , 7 , 18 , 35 , 37 , 39 , [41] , [42] , [43] , [44] ], no cognisance is taken of simultaneous consideration of load growth and seasonal voltage dependent load model in their planning approaches. In Ref.…”