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Combined heat and power systems are known for their high efficiency. On the other hand, economic dispatching of these systems is very important in terms of total efficiency and reliability of the power system. The novelty of this study is to use the Filled Function Method (FFM) to solve this optimization problem in a way different from that to be found in the literature. Moreover, the Taguchi method is combined with the FFM for the first time to obtain the best initial parameters. So the proposed hybrid deterministic optimization algorithm is called the Taguchi-based Filled Function Method (TFFM). The most important advantage of the suggested TFFM is that it always gives the same result for the same inputs and all the solutions are in the feasible region. The method is applied to four different test systems and the results obtained are compared with those of recent powerful optimization algorithms. With the proposed optimization method, a significant performance increase of 5.676% was achieved. Online supplemental data for this article can be accessed at https://doi.org/10.1080/0305215X.2022.2034802.

Due to the increasing cost of energy resources and environmental problems, higher efficiency systems such as combined heat and power units are becoming more popular. Due to the linear and non-convex properties of combined heat and power units, their optimum operation is becoming increasingly complex. The difficulties of this problem lead us to use intuitive and evolutionary methods. In this study, particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are applied to the economic distribution (ED) of combined heat and power units. The main purpose of the ED problem is to obtain the optimum output power and temperature of each unit while minimizing the total cost of production and fulfilling system operational constraints. The results are to demonstrate and compare the capabilities of these algorithms in solving the problem of economic distribution of combined heat and power systems., Enerji kaynaklarının artan maliyeti ve çevre sorunları nedeniyle birleşik ısı ve güç birimleri gibi daha yüksek verimlilikte çalışan sistemler daha popüler hale gelmektedir. Birleşik ısı ve güç ünitelerinin doğrusal ve dışbükey olmayan özelliklere sahip olmaları nedeniyle optimum çalışması giderek karmaşıklaşmaktadır. Bahsi geçen bu problemin zorlukları bizi sezgisel ve evrimsel yöntemleri kullanmaya yöneltmektedir. Bu çalışmada, parçacık sürü optimizasyon (PSO) algoritması ve genetik algoritma (GA), birleşik ısı ve güç birimlerinin ekonomik dağıtımına(ED) uygulanmaktadır. ED probleminin temel amacı, toplam üretim maliyeti en aza indirilirken ve sistem operasyonel kısıtlamaları yerine getirilirken her bir ünitenin optimum çıkış gücü ve ısısını elde etmektir. Sonuçlar bu algoritmaların birleşik ısı ve güç sistemlerinin ekonomik dağıtımı problemini çözmedeki yeteneklerinin gösterilmesi ve karşılaştırılmasıdır.

© 2020, International Organization on 'Technical and Physical Problems of Engineering'. All rights reserved.In this paper, Sine Cosine Algorithm (SCA) is proposed and applied to load frequency control (LFC) of different type single area power systems. Reheat turbine system without communication time delayed is considered for the first system. Power systems have communication time delays because of far remote units (FRUs’), communication channels (CCs’), delays between plant units and etc. Communication time delays (CTDs) have negative affect on reliability and stability of power systems. For this reason, non-reheat turbine system having communication time delayed is considered. Both systems are controlled by fractional order proportional-integral-derivative controller (FO-PID). This controller has five controllable parameters. Thus, it is very flexible and very effective controller. Analyzed single area power systems for LFC are compared with recent literature studies. Founded outputs are examined according to settling time (%0.005 band width), overshoot, undershoot and peak to peak values of frequency deviation signals. These outputs are demonstrated that system performances highly enhanced with proposed FO-PID controller and SCA method.

This chapter provides implementation of various optimization algorithms to various power system problems that utilize power flow calculations. Determination of the schedule (ON/OFF status and amount of power generated) of generating units within a power system results in great saving for electric utilities. The unit commitment problem can be formulated in order to minimize the total operating cost, satisfying the system, the unit, and several operational constraints. The power transfer limit of overhead transmission lines (OTLs) is an important constraint for power systems’ planning and operation. This constraint plays an essential role in the secure and economic management of power systems. The chapter presents economic dispatch problem by considering GAs and particle swarm optimization (PSO) in complex power system analysis. It uses a hybrid PSO to solve load flow problem while uses artificial bee colony optimization for solving the optimal power flow problem.

The necessity of consumption and energy that emerged in our world with the ever-developing industry and urbanization has become an important problem. This problem has made it necessary to conduct research on how to use existing energy resources in the most efficient way while constantly directing new energy sources. Although legal regulations have been made to remedy these problems in part, they are often seen to be inadequate. One of the most effective and efficient ways to relieve operation in electrical energy systems, increase system and energy efficiency, reduce costs and ensure voltage stability is to make reactive power compensation. In this study, in a linear welded power system, it is ensured that the capacity value of the capacitor required for compensation is reduced to a minimum by reducing the effects of the harmonics in the nonlinear loads affecting the system and reducing the voltage drop which may occur even by minimizing the effect of reactive power and optimizing the minimum apparent power, the maximum power factor is obtained and the voltage drop in the line is minimized.

Bu makale, tek-makinalı sonsuz-baralı (TMSB) birgüç sisteminin düşük frekanslı salınımlarını söndürmek için bir doğalmetasezgisel optimizasyon algoritması olan yarasa algoritmasını kullanarakgeleneksel Güç Sistemi Dengeleyicisi (PSS) ve PID tabanlı Güç SistemiDengeleyicisi (PID-PSS) parametrelerinin belirlenmesinde kullanılmasını önerir.Güç Sistemi Dengeleyicisisi parametrelerinin belirlenmesi, zaman bölgesitabanlı amaç fonksiyonu ile bir optimizasyon problemine dönüştürülmüştür. Bu problem;yarasa algoritması (YA) optimizasyonu ile belirlenen parametrelerin,Heffron-Phillips modeli temel alınarak oluşturulan tek-makinalı sonsuz-baralı(TMSB) güç sisteminin MATLAB/Simulink uygulaması üzerinde test edilerek rotorhız değişim (∆ω) kararsızlığının sönümlenmesinde çözüm olarak kullanılmıştır. Yarasaalgoritması optimizasyonu sonucu parametreleri belirlenen geleneksel GüçSistemi Dengeleyicisinin (PSS) ve PID tabanlı Güç Sistemi Dengeleyicisi (PID-PSS) performans sonuçlarıkarşılaştırılmıştır. Yarasa algoritması ile hesaplanmış geleneksel PSS’in ve PID-PSS’in rotor hız değişim (∆ω)kararsızlığını sönümlendirdiği, fakat geleneksel PSS’in kararlılığının veperformansının daha iyi olduğu gözlemlenmiştir., This paper, recommends the determination of the traditional power system stabilizer (PSS) and PID based power system stabilizer (PID-PSS) parameters using the bat algorithm, which is a natural metaheuristic optimization algorithm to suppress the low frequency oscillations of a single-machine endless-busbar (SMIB) power system. The determination of the parameters of the power system stabilizer was converted to an optimization problem by the time domain based objective function. This problem; The parameters determined by bat algorithm (BA) optimization were tested on MATLAB / simulink application of single-machine infinite-busbar (SMIB) power system based on Heffron-Phillips model and used as a solution to dampen rotor speed change (∆ω) instability. The results of the bat algorithm optimization were compared the performance results of the traditional power system stabilizer (PSS) and the PID based power system stabilizer (PID-PSS). The traditional PSS and PID-PSS, calculated by the bat algorithm, damped the rotor speed change (∆ω) instability. But the stability and performance of the traditional PSS were observed to be better.