EEE

https://doi.org/10.62909/ejeee.2024.008 Edison Journal for Electrical and Electronics Engineering

Review

An Examination of Optimization Techniques for Resolving Hy-

dro Generation Scheduling Issues

Bassam Mohsin Atiyah

and Anwar H. Hameed

School of Electrical and Electronic Engineering, Engineering campus, Universiti Sains Malaysia, Penang, Ma-

laysia; bassamatiyah@student.usm.my

Department of Power and Electrical Machines, Islamic Azad University, Kermanshah, Iran; hus-

seinanwar156@gmail.com

* Correspondence: Tel.: +7-9312449642

Abstract: Hydropower plants' optimal scheduling of energy (OSE) is a crucial component of electric

power systems and is a topic of intense academic investigation. Compared to other sustainable

power sources, hydropower has a negligible impact on the environment and society. The goal of the

three-time period hydro scheduling (TPHS) challenges is to maximize energy generation by exploit-

ing the accessible possible within a certain term of time by optimizing the power generating schedule

of the available hydropower units. First, a variety of conventional optimization techniques are of-

fered to help solve the TPHS problem. Recently, a number of optimization techniques were used to

determine the best solution for the energy production scheduling of hydro systems. These tech-

niques were allocated as a technique rely on involvements. This article provides a thorough analysis

of the application of numerous techniques to obtain the OSE of hydro units via looking at the tech-

niques used from different angles. The best answers from a variety of meta-heuristic optimization

procedures are determined for a range of experience situations. The methods that are offered are

contrasted according to this particular research, parameter limitations, optimization strategies, and

primary objective consideration. The majority of prior research has concentrated on hydro schedul-

ing, which is according to a reservoir of hydroelectric units. Issues of forthcoming studies—which

are outlined as the main concern surrounding the TPHS problem—are also taken into account.

Keywords: hydropower; generations; scheduling

1. Introduction

The need for power has grown throughout time, leading to the construction of sev-

eral power generating facilities. Scholars in the field of power systems study the optimal

scheduling of energy (OSE) of available generation systems, which is considered an im-

portant topic [1, 2].

The OSE of cascaded hydropower facilities is driven by three-time period term hydro

scheduling (TPHS) optimization issues to match load demand in a way that minimizes all

operating expenses while taking a variety of limitations into account [3]. Under a variety

of hydro unit constraints, such as the balance between water and power, water release

limitations, storage capacity restrictions, and power output limitations, the TPHS problem

should be optimized. Moreover, the TPHS optimization issue is characterized as non-lin-

ear and non-convex by the unexpected fluctuation of input parameters, losses of electrical

energy program from power production systems, and compound hydraulic connections

[4, 5]. An example of an architecture for producing hydroelectric power is shown in Figure

Citation: B. M. Atiyah and A. H.

Hameed, An Examination of Optimi-

zation Techniques for Resolving Hy-

dro Generation Scheduling Issues.

Edison Journal for Electrical and

Electronics Engineering, 2024. 2: p.

50-56

Academic Editor: Assoc. Prof. (Dr.)

N. Manoj Kumar

Received: 25/10/2024

Revised: 17/11/2024

Accepted: 6/12/2024

Published: 13/12/2024

Submitted for possible open access

publication under the terms and

conditions of the Creative Commons

Attribution (CC BY) license

(https://creativecommons.org/license

s/by/4.0/).

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Figure 1. hydropower Production Schedule Modelling and Solutions Approaches 
 
For a number of decades, scholars have been particularly interested in the  OSE of 
hydro parts, which is a crucial field of research. Several optimization techniques have been 
proposed to address this challenging issue. These include mixed, which predictable, and 
heuristic optimization techniques as well as traditional mathematical optimization tech-
niques.  For  example,  the  short-term  hydro  scheduling  (STHS)  issue  can  be  optimally 
solved by first applying the concept of the quantity at danger, followed by a maximum 
amount theory-genetic algorithm (GA) [6], non-linear programming frameworks for ac-
quiring rules of operation with various characteristics [7], and mixed-integer linear pro-
gramming (MILP) [8]. Secondly, real-time optimization [9], an assessment technique [10], 
dual  dynamic  programming  (DDP), and  stochastic  DDP  [11] are  used  to  the  mid-term 
hydro scheduling issue. In addition, a number of approaches have been explored to ad-
dress the long-term hydro scheduling problem: separate different dynamic programming 
(DP)  and  parallel  separate  differential  dynamic  programming  [12],  traditional  particle 
swarm optimization (PSO), the total learning of the PSO and enhanced in general acquir-
ing of the PSO [13], separate different dynamic programming and uniform DP [14], a cost-
paid yearly optimization simulation based on discrete DP and the MILP [15], and a multi-
objective complex development worldwide optimization technique with main factor in-
vestigation and a congestion space operator have been tried as well.   
Using the  benchmark  operations,  a comparison  of  the suggested approaches—the 
multi-objective GA, the multi-objective imitation annealing technique, the multi-objective 
PSO technique, the multifaceted differential evolutionary technique, and the traditional 
multi-objective  complex  development  global  optimization  method—has  been  demon-
strated [16]. The gravity search method based on collective interactions and the gravity 
rule was just released. For solving benchmarking functions, the algorithm's effectiveness 
is contrasted with that of the original GA. Additionally, other heuristic, meta-heuristic, 
and mathematical techniques are acknowledged as experience-based techniques. 
2. Materials and Methods 
2.1  Examine the Methods 
The main reason optimum hydro generation is challenging is that choices must be 
made in actual time. The optimization issue comprises state-variables, such reservoir wa-
ter level, and random, weather-dependent factors, like water flow, that are particularly 
efficient. As a result, the entire multifaceted optimization challenge is broken down into 
smaller issues. Long-, mid-, and short-term parts are routinely broken down, and a rem-
edy is developed using predetermined approaches for every issue [17]. 
it makes handling the relevant calculations challenging. 

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2.2  Short-Term Schedule Optimization 
This investigation demonstrates why the recommended strategy, which includes a 
water wait interval, may improve schedule utilization's practical viability and profitabil-
ity. A contemporary method for mixed-integer non-linear programming (MINP) was pre-
sented by ref. [18], which considered a non-linear equation for the discharge of water and 
the net head. Due to the greater degree of accurate modelling, a better method is used, 
and it is  favorably applied to transmitted hydro subunits  while  ignoring the  computa-
tional cost constraint. In addition to head reliance, irregular operation zones and water 
release constraints are also taken into account by ref. [19]. The numerical findings demon-
strate the recommended technique's excellent efficacy. Furthermore, considering the head 
dependency, ref. [20] offer a novel nonlinear approach to the hydro schedule issue with 
fulfilled restrictions. The outcomes demonstrate the effectiveness of the recommended ir-
regular approach. 
A model for practical probabilistic hydroelectric scheduling has been proposed by 
ref. [21]. The suggested method is predicated on chaotic sequential.   
In [22]improved the top people in the socialization technique with differential evolu-
tion (DE) by using the population's initialization phase. It makes more sense to select a 
method of operation where the total height of the water for hydropower production is 
enhanced and split cheaply for plant internal operation in order to maintain a continuous 
water release operation. In [23] proposed a mixed method that solves the related issues of 
unit commitment and dispatching economic loads by combining the multi-ant colony en-
ergy  units  with  the  DE  approach.  The  results  of  the  simulation  show  that  the  recom-
mended method for water discharge has the best convergence characteristics and compu-
tational efficiency with reduced consumption. In [24], examined the usage of many groups 
to satisfy system demands while using less water for every created item. The reservoir' 
basic and ultimate conditions had been satisfied. 
A flexible generating stream strategy has been proposed by Jiayang et al. [40] utiliz-
ing the reservoir's constantly organizing net head of water and the number of waters con-
sumed. The outcomes demonstrate that this novel strategy can enhance cascaded hydro-
power plants synthesized generating utilization. The multi-objective optimum peak shav-
ing method was developed by ref [25]. In order to divide the plant's power across specific 
power lines, it must minimize its maximum residual loads per power network. A real-life 
instance demonstrates that the planned method is practical, adjustable, and powerful to 
effectively achieve outcomes that are almost ideal. A real bipolar bee colony optimization 
technique was proposed by ref. [26] and is utilized to address the unit commitment and 
financial  load  distribution  concurrent  sub-problems.  The  outcomes  of  the  experiment 
demonstrate that the recommended method may generate top-advantage answers while 
lowering water use and computation time. A competent model that takes the form of a 
mixed-integer quadratic programmed was proposed by ref. [27]. It demonstrates a trou-
ble-stage technique rely on a price investigation that generates quick, almost optimal so-
lutions for real-world situations. A framework for hydropower request based on the OSE 
from a stochastic model has been offered by ref. [28]. They also provided an algorithmic 
technique for shrinking the offer matrices to a size that the market operators would like. 
The findings demonstrate why uncontrolled imports could alter bidding. 
2.3  Enhancement of Interim Planning 
The ideal organization of hydroelectric assets was discussed by ref. [29] according to 
maximizing a provider's predicted earnings. Production and future agreements for each 
period of time are the choice factors. A probabilistic self-scheduling approach for a hydro 
price supplier was provided by ref. [30]. The seller wants to maximise daily marketplace 
income. The outcomes point  to the potential  for obtaining a special  business solver. In 
order to prevent revenue volatility, ref. [31] suggested an original approach to demand 
volatility, which is offered in a prototype that uses price plans and threat control via the 
notion  of  dependent  matter  at  chance.  In  addition,  hydropower  providers'  pools 

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contributions and plant schedule are taken into consideration simultaneously to offer an 
acceptable option for cascading hydropower complexes. 
2.4  Enhancement of Extended-Term Scheduling 
In order to minimise the total costs of energy production,  ref. [32] suggested a re-
stricted Markov choice strategy for controlling the water release to complete water collec-
tion requirements and  the design needs for  electric energy. The activity, as well as  the 
competence of the configuration and the solution approach, are demonstrated by numer-
ical results. The Markovian stochastic DP was introduced by ref. [33] through the model-
ling of monthly discharges using probability allocation processes. The findings show that 
the frequency of steady and suggested programmed development is identical compara-
ble.   
A novel chaotic GA was proposed by ref. [34]. The findings indicate that the median 
annual energy is the highest while its convergence rate is faster than both the GA and the 
DP. As a result, the solution-based method is practical and effective for the combined res-
ervoir units' best feasible operations. A novel chaotic PSO method was proposed by ref. 
[35], who also compared the effectiveness of single to tribble dimensional muddled dia-
grams within the normal range. Validations and arithmetic findings demonstrate the im-
pact  and  efficiency  of  several  processes  for  a  truthful  hydro-system.  With  the  goal  of 
achieving a consistent and optimal level of power generation utilization, in [36] concen-
trated on improving the optimization model through the application of the PSO and Fire-
fly Algorithm (FA) techniques. The outcomes demonstrate the FA's superiority, compe-
tence, and resilience. They have also devised a novel plan to enhance PSO and FA through 
the use of serial subdivision. The outcomes demonstrate the power, excellent effective-
ness, and robustness of the Series Division Firefly Algorithm  [36]. A method for multi-
core parallel PSO was put forward by ref. [35]. The outcomes demonstrate the best pro-
duction's increased reliability, low execution cost, and effectiveness. The suggested ap-
proach has a good chance of operating at its best in the years to come. 
in [37, 38], it presented new ideas including a Tabu search technique for producing 
potential solutions with a configurable stage vector direction. The statistical findings show 
that the presented method is better than alternatives. 
For the scenario where the release arrives as probability density functions via multi-
commodity net releases, in [38] used stochastic discharge. It's been shown that difficulties 
involving many reservoir units with insufficient dependance on releases can also be ade-
quately modelled. A model centered around maximizing production while accounting for 
spot market costs was developed by ref. [39]. The outcome demonstrates how to carry out 
the water value management calculations. A multi-phase stochastic MIP prototype that 
includes a choice made at the recent surcharge period and a tougher determination made 
later was reported by ref. [40]. Since it is intended to be used during the winter, it takes 
deterministic water discharge into account and handles cost as a stochastic parameter. 
In an excellent market, it has been suggested linear determination practices that max-
imize  the  demand  expense  from  the  power  display  deal.  Both  reservoirs'  releases  and 
market prices take the uncertainty notion into account. The outcomes demonstrate how 
effectively  the  recommended  estimate  can  lower  the  computational  complexity.  Water 
discharge was taken into account by ref. [41] as an additional case variable to ascertain the 
issue in the scenario definition. The water discharge results as a state variable do not show 
a significant impact on the anticipated annual earnings; nonetheless, guaranteed differ-
ences are noted for specific time periods of the year that may demonstrate their consider-
ation in shorter term prospects. 
The goal of ref. [42] was to investigate the potential for load demands and the pro-
duction of electricity. The findings demonstrate that when energy production and load 
demands are integrated in the planning, a system's affordability grows. 
 
 

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5. Conclusions

Heuristic optimization techniques are among the many optimization methods that

are used to address the hydro system's optimal scheduling of energy (OSE). The TPHS

optimization problem's goal function definition demonstrates the many discrepancies and

groups associated with hydroelectric power systems. This article provides a comprehen-

sive and updated overview of the optimization process performance for the hydro sched-

uling explanation, looking at methods from several angles. This article examines the prin-

ciples of several optimization techniques for resolving the hydro scheduling issue, as well

as unique algorithmic parameters. Numerous techniques address statistical analysis of the

obtained OSE of hydro tonic remedies, taking into consideration multiple case studies.

The paper examines the qualitative and numerical evaluation of the several optimization

strategies for the hydro scheduling issue. It might be very helpful to academic writers who

are working to solve the TPHS trouble and are constrained by the use of optimization

techniques.

More realistically, the OSE of hydro and thermal systems in irregular present influ-

ence stream may be solved; this could be the subject of future studies in the area. Hydro

system scheduling could prove more beneficial and required if alternative sustainable en-

ergy sources, such as wind and solar power, were taken into account. These resources are

now managed through the use of optimization techniques. Further research on the effects

of driven water stowage on the resolution of the TPHS issue could be conducted in the

years to come.

Acknowledgments: All authors would like to convey their genuine appreciation to their universi-

ties for providing scientific searching support form multi sides.

Conflicts of Interest: “The authors declare no conflict of interest.”

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