A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives

Nazari-Heris, Morteza; Mohammadi‐Ivatloo, Behnam; Gharehpetian, Gevork B.

doi:10.1016/j.rser.2017.06.024

Cited by 183 publications

(102 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, the performance of TSCO for resolving the CHPDE problems in the field of quality of solution and convergence speed is studied. Two typical test cases are chosen from literature for comparison, which are used to evaluate the algorithm in most literature of studying the CHPDE problems. The first case is the classical simple representation of the CHPDE problem, and the second case is the classical sophisticated representation.…”

Section: Case Studiesmentioning

confidence: 99%

“…To make full use of wasted heat, combined heat and power (CHP) units are introduced to simultaneously produce electricity and heat energy in the power production by conventional thermal plants. Combined heat and power units can generate conversion efficiency above than 90% through using wasted heat in thermal plant, so the cogeneration units, power units, and heat units are combined to satisfy power and heat demands in CHP plants.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Social cognitive optimization with tent map for combined heat and power economic dispatch

Sun

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Combined heat and power economic dispatch (CHPED) problem is a sophisticated constrained nonlinear optimization problem in a heat and power production system for assigning heat and power production to minimize the production costs. To address this challenging problem, a novel social cognitive optimization algorithm with tent map (TSCO) is presented for solving the CHPED problem. To handle the equality constraints in heat and power balance constraints, adaptive constraints relaxing rule is adopted in constraint processing. The novelty of our work lies in the introduction of a new powerful TSCO algorithm to solve the CHPED issue. The effectiveness and superiority of the presented algorithm is validated by conducting 2 typical CHPED cases. The numerical results show that the proposed approach has better convergence speed and solution quality than all other existing state‐of‐the‐art algorithms.

show abstract

Section: Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Social cognitive optimization with tent map for combined heat and power economic dispatch

Sun

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…According to Table 5, the sum of power generation of four hydro units and three thermal plants meets the load demand during the scheduling time of the STHS problem. Proposed method provided the minimum fuel cost of $41,101.738, which is compared with simulated annealing (SA) [25], DE [11], chaotic artificial bee colony (CABC) [26], adaptive differential evolution (ADE) [23], RCGA [13], DE [10], SPPSO [12], RQEA [10], PSO [27], chaotic differential evolution (CDE) [23], clonal selection algorithm (CSA) [28], TLBO [29], TLBO [18], improved quantum-behaved particle swarm optimization (IQPSO) [30], quasi-oppositional teaching learning based optimization (QTLBO) [29], Improved differential evolution (IDE) [21], adaptive chaotic differential evolution (ACDE) [23], real coded chemical reaction based optimization (RCCRO) [22], differential real-coded quantum-inspired evolutionary algorithm (DRQEA) [10], and adaptive chaotic artificial bee colony algorithm (ACABC) [26], quasi-oppositional group search optimization (QOGSO), as shown in Table 6. Results show that proposed method is better than previous methods used in the test system 2, case 1.…”

Section: Test Systemmentioning

confidence: 99%

“…Thermal power plants operational costs are high; however, the initial costs of such generation units are lower. On the other hand, the operational costs of hydro power plants are insignificant; however, the construction costs of such plants are high [11,12]. Accordingly, the combination of these two types of power plants can be considered as an appropriate choice considering economic viewpoints.…”

Section: Introductionmentioning

confidence: 99%

Application of Dynamic Non-Linear Programming Technique to Non-Convex Short-Term Hydrothermal Scheduling Problem

et al. 2017

View full text Add to dashboard Cite

Short-term hydro-thermal scheduling aims to obtain optimal generation scheduling of hydro and thermal units for a one-day or a one-week scheduling time horizon. The main goal of the problem is to minimize total operational cost considering a series of equality and inequality constraints. The problem is considered as a non-linear and complex problem involving the valve-point loading effect of conventional thermal units, the water transport delay between connected reservoirs, and transmission loss with a set of equality and inequality constraints such as power balance, water dynamic balance, water discharge, initial and end reservoir storage volume, reservoir volume limits and the operation limits of hydro and thermal plants. A solution methodology to the short-term hydro-thermal scheduling problem with continuous and non-smooth/non-convex cost function is introduced in this research applying dynamic non-linear programming. In this study, the proposed approach is applied to two test systems with different characteristics. The simulation results obtained in this paper are compared with those reported in recent research studies, which show the effectiveness of the presented technique in terms of total operational cost. In addition, the obtained results ensure the capability of the proposed optimization procedure for solving short-term hydro-thermal scheduling problem with transmission losses and valve-point effects.

show abstract

“…Hybrid methods are developed for solving the economic dispatch (ED) problem such as fuzzy linear programming as in El‐Ela et al for predicted and emergency operation of power systems. The chaotic krill herd optimizer that was developed for solving the ED problem in Bentouati et al The continuous development of search‐based methods is also integrated for different power systems problem such as optimal power flow . A comprehensive review on this topic for optimal combined heat and power dispatch from economic and environmental perspective was presented in Nazari‐Heris et al The fruit fly was developed to solve engineering design problem called multi‐objective framework for synchronous motor design .…”

Section: Introductionmentioning

confidence: 99%

Assessment of hurricane versus sine-cosine optimization algorithms for economic/ecological emissions load dispatch problem

El‐Sehiemy

Rizk‐Allah

Attia

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary In the current research, a comparative study of two modern optimization algorithms is carried out for finding the solution of non‐smooth economic/ecological emission load dispatch (EELD) problem. These optimization methods are hurricane optimization algorithm (HOA) and sine‐cosine algorithm (SCA). A multi‐objective optimization module is successively developed for the competitive algorithms. In the competitive algorithms, random initial populations of the search agents are created in the search space with optimizing the conflicted objectives, economic and emission, simultaneously of the EELD problem. The multi‐objective optimal solutions are achieved based on Pareto concepts. The competitive algorithms are tested on six test function and two general standard engineering problems called tension/compression design and welded beam design problem. Then, the optimization algorithms are validated for an important operation issue of power systems by solving the non‐smooth EELD on the standard six generators, IEEE 30‐bus standard test system. Single and multiobjective frameworks are considered to reduce the generation fuel costs as well as minimizing the corresponding ecological emissions. Simulation results are assessed with previous famous optimizers. Also, these results prove the reasonable performances of the proposed two competitive algorithms compared with previous optimization techniques. In addition, HOA has more competitive performance compared with SCA according to convergence rate and statistical analysis of the studied real engineering problems as well as for benchmarking and design engineering problems. Therefore, these algorithms are considered as efficient and capable algorithms for other non‐smooth large‐scale complex problems in real power networks.

show abstract

A comprehensive review of heuristic optimization algorithms for optimal combined heat and power dispatch from economic and environmental perspectives

Cited by 183 publications

References 84 publications

Social cognitive optimization with tent map for combined heat and power economic dispatch

Social cognitive optimization with tent map for combined heat and power economic dispatch

Application of Dynamic Non-Linear Programming Technique to Non-Convex Short-Term Hydrothermal Scheduling Problem

Assessment of hurricane versus sine-cosine optimization algorithms for economic/ecological emissions load dispatch problem

Contact Info

Product

Resources

About