Optimization of Combined Heat and Power Systems by Meta-Heuristic Algorithms: An Overview

Abstract

Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed, based on numerical, experimental, parametric, and algorithmic optimization routes. Due to the significance of algorithmic optimization, as a systematic method for optimizing energy systems, this novel review paper is focused on the meta-heuristic optimization algorithms, implemented in CHP energy systems. By considering the applied objective functions, the main sections are divided into single-objective and multi-objective algorithms. In each case, the units’ combination is briefly detailed, the objective functions are introduced, and analyses are conducted. The main aim of this paper is to gather a database for the optimization of CHPs, demonstrate the effect of the applied optimization methods on the objective functions, and finally, introduce the most efficient methods. The most significant feature of this paper is that it covers all types of CHP optimization issues including scheduling, sizing, and designing problems, finding the extent of each optimization issue in the relevant papers in the last decade. Based on the findings, in the single-objective problems the combined heat and power economic dispatch (CHPED) issue as a subcategory of the scheduling problems is introduced as the most paid topic; the designing issue is known as the lowest paid topic. In the multi-objective problems, working on various types of CHP optimization problems has been conducted with an almost similar share. The combined heat and power economic emission dispatch (CHPEED) problem with the most share, and the sizing issue with the lowest share. The CHP designing and sizing optimization issues could be introduced as topics to work on more in the future. Additionally, the numerical results of CHPED and CHPEED problems solved by various algorithms are presented and compared. In this regard, specified test systems are considered.

A Survey of Combined Heat and Power-Based Unit Commitment Problem: Optimization Algorithms, Case Studies, Challenges, and Future Directions

“…Moreover, Alsagri and Alrobaian [34] have presented a complete and updated overview of meta-heuristic optimization algorithms used in CHP systems, including the CHPED and CHPEED problems, in two categories of single objective and multi-objective algorithms. They divided the suggested algorithms in single objective for CHP optimization into evolutionary algorithms (EAs) (including GAs, differential evolution (DE) algorithm, hyper-spherical search (HSS), artificial immune system (AIS), and the stochastic fractal search (SFS) algorithms), swarm intelligence-based (SI-based) algorithms (including different variants of PSO, whale optimization algorithm (WOA), cuckoo search algorithm (CSA), group search optimization (GSO), FA, bee colony optimization (BCO), ant colony search algorithm (ACSA), squirrel search algorithm (SSA), and grey wolf optimization (GWO)), human-based algorithms (including harmony search (HS), teaching learning-based optimization (TLBO), exchange market algorithm (EMA), and social cognitive optimization (SCO)), physics-based algorithms (including gravitational search algorithm (GSA), charged system search algorithm (CSSA), and heat transfer search algorithm (HTS)), and hybrid meta-heuristic methods (including combining the meta-heuristics methods such as combinatorial time-varying acceleration coefficients-gravitational search algorithm-particle swarm optimization (TVAC-GSA-PSO), combining the bat algorithm (BA) and artificial bee colony (ABC) algorithm based on the chaotic-based self-adaptive (CbSA) (CbSA-BAABC), combining the meta-heuristics and the machine learning programming, and combining the meta-heuristics and the mathematical programming methods).…”

Economic Dispatch Optimization Strategies and Problem Formulation: A Comprehensive Review

“…Others limit their scope to particular optimization strategies or theoretical frameworks, with each addressing only a fragment of the broader EDP landscape [11]. Additionally, certain reviews target specific types of power systems [12,13]. In contrast, the present research provides a comprehensive examination of the EDP, thus tracing its evolution from traditional to modern power systems.…”

Optimisation of an Integrated System: Combined Heat and Power Plant with CO2 Capture and Solar Thermal Energy

“…Ref. [29], demonstrated that optimising design strategies in cogeneration reduces the cost of CO2. [30], optimised a CHP by utilising low pressure steam and the waste heat of the plant.…”

“…Ref. [29], demonstrated that optimising design strategies in cogeneration reduces the cost of CO 2 [30], optimised a CHP by utilising low pressure steam and the waste heat of the plant. [31], continued with the previous work to demonstrate how CHP configurations can be utilised to reduce the cost of production not only by using electricity and steam, but also CO 2 for enhanced oil recovery (EOR).…”