Research article Special Issues

An optimal power flow solution for a power system integrated with renewable generation

  • Received: 22 December 2023 Revised: 13 January 2024 Accepted: 26 January 2024 Published: 06 February 2024
  • MSC : 68T20

  • Integrating Green Renewable Energy Sources (GRES) as substitutes for fossil fuel-based energy sources is essential for reducing harmful emissions. The GRES are intermittent and their integration into the conventional IEEE 30 bus configuration increases the complexity and nonlinearity of the system. The Grey Wolf optimizer (GWO) has excellent exploration capability but needs exploitation capability to enhance its convergence speed. Adding particle swarm optimization (PSO) with excellent convergence capability to GWO leads to the development of a novel algorithm, namely a Grey Wolf particle swarm optimization (GWPSO) algorithm with excellent exploration and exploitation capabilities. This study utilizes the advantages of the GWPSO algorithm to solve the optimal power flow (OPF) problem for adaptive IEEE 30 bus systems, including thermal, solar photovoltaic (SP), wind turbine (WT), and small hydropower (SHP) sources. Weibull, Lognormal, and Gumbel probability density functions (PDFs) are employed to forecast the output power of WT, SP, and SHP power sources after evaluating 8000 Monte Carlo possibilities, respectively. The multi-objective green economic optimal solution consisted of 11 control variables to reduce the cost, power losses, and harmful emissions. The proposed method to address the OPF problem is validated using an adaptive IEEE bus system. The proposed GWPSO algorithm is evaluated by comparing it with PSO and GWO optimization algorithms in terms of achieving an optimal green economic solution for the adaptive IEEE 30 bus system. This evaluation is conducted within the confines of the same test system using identical system constraints and control variables. The integration of a small SHP with WT and SP sources, along with the proposed GWPSO algorithm, led to a yearly cost reduction ranging from $19,368 to $30,081. Simulation findings endorsed that the proposed GWPSO algorithm executes fruitfully compared to alternative algorithms regarding a consistent convergence curve and robustness, proving its potential as a viable choice for achieving cost-effective solutions in power systems incorporating GRES.

    Citation: Hisham Alghamdi, Lyu-Guang Hua, Muhammad Riaz, Ghulam Hafeez, Safeer Ullah, Monji Mohamed Zaidi, Mohammed Jalalah. An optimal power flow solution for a power system integrated with renewable generation[J]. AIMS Mathematics, 2024, 9(3): 6603-6627. doi: 10.3934/math.2024322

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  • Integrating Green Renewable Energy Sources (GRES) as substitutes for fossil fuel-based energy sources is essential for reducing harmful emissions. The GRES are intermittent and their integration into the conventional IEEE 30 bus configuration increases the complexity and nonlinearity of the system. The Grey Wolf optimizer (GWO) has excellent exploration capability but needs exploitation capability to enhance its convergence speed. Adding particle swarm optimization (PSO) with excellent convergence capability to GWO leads to the development of a novel algorithm, namely a Grey Wolf particle swarm optimization (GWPSO) algorithm with excellent exploration and exploitation capabilities. This study utilizes the advantages of the GWPSO algorithm to solve the optimal power flow (OPF) problem for adaptive IEEE 30 bus systems, including thermal, solar photovoltaic (SP), wind turbine (WT), and small hydropower (SHP) sources. Weibull, Lognormal, and Gumbel probability density functions (PDFs) are employed to forecast the output power of WT, SP, and SHP power sources after evaluating 8000 Monte Carlo possibilities, respectively. The multi-objective green economic optimal solution consisted of 11 control variables to reduce the cost, power losses, and harmful emissions. The proposed method to address the OPF problem is validated using an adaptive IEEE bus system. The proposed GWPSO algorithm is evaluated by comparing it with PSO and GWO optimization algorithms in terms of achieving an optimal green economic solution for the adaptive IEEE 30 bus system. This evaluation is conducted within the confines of the same test system using identical system constraints and control variables. The integration of a small SHP with WT and SP sources, along with the proposed GWPSO algorithm, led to a yearly cost reduction ranging from $19,368 to $30,081. Simulation findings endorsed that the proposed GWPSO algorithm executes fruitfully compared to alternative algorithms regarding a consistent convergence curve and robustness, proving its potential as a viable choice for achieving cost-effective solutions in power systems incorporating GRES.



    Ricci flow is a technique widely used in differential geometry, geometric topology, and geometric analysis. The Yamabe flow that deforms the metric of a Riemannian manifold M is presented by the equations [1,2]

    tg(t)+r(t)g(t)=0, g(0)=g0, (1.1)

    where r(t) is the scalar curvature of M, and t indicates the time. For a 2-dimensional manifold, (1.1) is equivalent to the Ricci flow presented by

    tg(t)+2S(g(t))=0, (1.2)

    where S is the Ricci tensor of M. However, in cases of dimension >2, these flows do not coincide, since the Yamabe flow preserves the conformal class of g(t) but the Ricci flow does not in general. The Ricci flow has been widely used for dealing with numerous significant problems, such as deformable surface registration in vision, parameterization in graphics, cancer detection in medical imaging, and manifold spline construction in geometric modeling. For more utilization in medical and engineering fields, see [3]. It has also been used in theoretical physics, particularly; in the study of the geometry of spacetime in the context of general relativity. In this area, it has been applied to understand the behavior of black holes and the large-scale structure of the universe.

    The self-similar solutions of (1.1) and (1.2) are called the Ricci and Yamabe solitons, respectively [4,5]. They are respectively expressed by the following equations:

    £Fg+2S+2Λg=0, (1.3)

    and

    £Fg+2(Λr)g=0, (1.4)

    where £F is the Lie derivative operator along the smooth vector field F on M, ΛR.

    In 2010, Blair [6] defined the concept of -Ricci tensor S in contact metric manifolds M as:

    S(X,Y)=g(QX,Y)=Trace{φR(X,φY)},

    for any vector fields X and Y on M, here Q is the -Ricci operator, R is the curvature tensor, and φ is a (1,1) tensor field. It is to be noted that the notion of the -Ricci tensor on complex manifolds was introduced by Tachibana [7]. Later, Hamada [8] studied -Ricci flat real hypersurfaces of complex space forms.

    If we replace S with S in (1.3), then we recover the expression of -Ricci soliton, proposed and defined by Kaimakamis and Panagiotidou [9] as follows:

    Definition 1.1. On a Riemannian (or a semi-Riemannian) M, the metric g is called a -Ricci soliton; if

    £Fg+2S+2Λg=0 (1.5)

    holds and ΛR.

    In 2019, a modern class of geometric flows, namely, the Ricci–Yamabe (RY) flow of type (ρ,σ) was established by Güler and Crasmareanu [10]; and is defined by

    tg(t)+2ρS(g(t))+σr(t)g(t)=0, g(0)=g0

    for ρ,σR.

    The RY flow can be Riemannian, semi-Riemannian, or singular Riemannian due to the involvement of the scalars ρ and σ. This kind of different choice is useful in differential geometry and physics, especially in general relativity theory (i.e., a new bimetric approach to space–time geometry [11,12]).

    A Ricci–Yamabe soliton (RYS) is a solution of RY flow; if it depends only on one parameter group of diffeomorphism and scaling. A Riemannian manifold M is said to admit an RYS if

    £Fg+2ρS+(2Λσr)g=0, (1.6)

    where ρ,σR.

    If F=gradf, fC(M), then the RYS is called the gradient Ricci–Yamabe soliton (gradient RYS), and then (1.5) takes the form

    2f+ρS+(Λσr2)g=0, (1.7)

    where 2f indicates the Hessian of f. A RYS of types (ρ,0) and (0,σ) is respectively known as ρ-Ricci soliton and σ-Yamabe soliton.

    A manifold M is said to admit a -Ricci–Yamabe soliton (-RYS) if

    £Fg+2ρS+(2Λσr)g=0 (1.8)

    holds, where ρ,σ, ΛR and r is the -scalar curvature tensor of M.

    In a similar way to (1.7), the gradient -Ricci–Yamabe soliton (gradient -RYS) is defined by

    2f+ρS+(Λσr2)g=0. (1.9)

    A -RYS is said to be shrinking if Λ<0, steady if Λ=0, or expanding if Λ>0. A -RYS is called a

    (i) -Yamabe soliton if ρ=0,σ=1,

    (ii) -Ricci soliton if ρ=1,σ=0,

    (iii) -Einstein soliton if ρ=1,σ=1,

    (iv) -ρ-Einstein soliton if ρ=1,σ=2ρ.

    Note that the -Ricci–Yamabe soliton is the generalization of the aforementioned cases (i)(iv). Thus, the research on -Ricci–Yamabe soliton is more significant and promising.

    On the other hand, the Lorentzian manifold, which is one of the most important subclasses of pseudo-Riemannian manifolds, plays a key role in the development of the theory of relativity and cosmology [13]. In 1989, Matsumoto [14] proposed the notion of LP-Sasakian manifolds, while the same notion was independently studied by Mihai and Rosca [15] in 1992, and they contributed several important results on this manifold. Later, this manifold was studied by many researchers. Recently, in 2021, Haseeb and Prasad proposed and studied LP-Kenmotsu manifolds [16] as a subclass of Lorentzian paracontact manifolds.

    Since the turn of the 21st century, the study of Ricci solitons and their generalizations has become highly significant due to their wide uses in various fields of science, engineering, computer science, medical etc. Here we are going to mention some works on Ricci solitons and their generalizations that were carried out by several authors, such as: the geometric properties of Einstein, Ricci and Yamabe solitons were studied by Blaga [17] in 2019; Deshmukh and Chen [18] find the sufficient conditions on the soliton vector field, where the metric of a Yamabe soliton is of constant scalar curvature; Chidananda et al. [19] have studied Yamabe and Riemann solitons in LP-Sasakian manifolds; the study of LP-Kenmotsu manifolds and ϵ-Kenmotsu manifolds admitting η-Ricci solitons have been carried out by Haseeb and Almusawa [20], and Haseeb and De [21]; in [22], the authors studied conformal Ricci soliton and conformal gradient Ricci solitons on Lorentz-Sasakian space forms; RYSs have been studied by Haseeb et al. [23], Singh and Khatri [24], Suh and De [25], Yoldas [26], Zhang et al. [27]. The study of Ricci solitons and their generalizations has been extended to -Ricci solitons and their generalizations on various manifolds and has been explored by the authors: Dey [28], Dey et al. [29], Ghosh and Patra [30], Haseeb and Chaubey [31], Haseeb et al. [32], and Venkatesha et al. [33]. Recently, Azami et al. [34] investigated perfect fluid spacetimes and perfect fluid generalized Roberston–Walker spacetimes.

    A differentiable manifold M (dim M=n) with the structure (φ,ζ,η,g) is named a Lorentzian almost paracontact metric manifold; in case φ: a (1,1)-tensor field, ζ: a contravariant vector field, η: a 1-form, and g: a Lorentzian metric g satisfy [13]

    η(ξ)=1, (2.1)
    φ2=I+ηξ, (2.2)
    φξ=0,ηφ=0, (2.3)
    g(φ,φ)=g(,)+η()η(), (2.4)
    g(,ξ)=η(). (2.5)

    We define the 2-form Φ on M as

    Φ(X,Y)=Φ(Y,X)=g(X,φY), (2.6)

    for any X,Yχ(M), where χ(M) is the Lie algebra of vector fields on M. If

    dη(X,Y)=Φ(Y,X), (2.7)

    here d is an exterior derivative, then (M,φ,ξ,η,g) is called a paracontact metric manifold.

    Definition 2.1. A Lorentzian almost paracontact manifold M is called a Lorentzian para-Kenmotsu (in brief, LP-Kenmotsu) manifold if

    (Xφ)Y=g(φX,Y)ξη(Y)φX, (2.8)

    for any X and Y on M [16,23,35].

    In the case of an LP-Kenmotsu manifold, we have

    Xξ=Xη(X)ξ, (2.9)
    (Xη)Y=g(X,Y)η(X)η(Y), (2.10)

    where indicates the Levi–Civita connection with respect to g.

    Furthermore, in an LP-Kenmotsu manifold of dimension n (in brief, (LP-K)n), the following relations hold [16]:

    g(R(X,Y)Z,ξ)=η(R(X,Y)Z)=g(Y,Z)η(X)g(X,Z)η(Y), (2.11)
    R(ξ,X)Y=R(X,ξ)Y=g(X,Y)ξη(Y)X, (2.12)
    R(X,Y)ξ=η(Y)Xη(X)Y, (2.13)
    R(ξ,X)ξ=X+η(X)ξ, (2.14)
    S(X,ξ)=(n1)η(X),S(ξ,ξ)=(n1), (2.15)
    Qξ=(n1)ξ, (2.16)

    for any X,Y,Zχ(M).

    Lemma 2.1. [36] In an (LP-K)n, we have

    (XQ)ξ=QX(n1)X, (2.17)
    (ξQ)X=2QX2(n1)X, (2.18)

    for any X on (LP-K)n.

    Lemma 2.2. [37] In an (LP-K)n, we have

    S(Y,Z)=S(Y,Z)ng(Y,Z)η(Y)η(Z)+ag(Y,φZ), (2.19)
    r=rn2+1+a2, (2.20)

    for any Y,Z on (LP-K)n, and a is the trace of φ.

    Lemma 2.3. In an (LP-K)n, the eigenvalue of the -Ricci operator Qcorresponding to the eigenvector ξ is zero, i.e., Qξ=0.

    Proof. From (2.19), we have

    QY=QYnYη(Y)ξ+aφY, (2.21)

    which, by putting Y=ξ; and using (2.1), (2.3), and (2.16) gives Qξ=0.

    Lemma 2.4. The -Ricci operator Q in an (LP-K)n satisfies the following identities:

    (XQ)ξ=QXnXη(X)ξ+aφX, (2.22)
    (ξQ)X=2QX2(n1)X+ξ(a)φX, (2.23)

    for any X on (LP-K)n.

    Proof. By the covariant differentiation of Qξ=0 with respect to X and using (2.9), (2.21) and Qξ=0, we obtain (2.22). Next, differentiating (2.21) covariantly with respect to ξ and using (2.8)–(2.10), (2.18), and (2.21), we obtain (2.23).

    Lemma 2.5. In an (LP-K)n, we have [23]

    ξ(r)=2(rn(n1)), (2.24)
    X(r)=2(rn(n1))η(X), (2.25)
    η(ξDr)=4(rn(n1)), (2.26)

    for any X on M, and Dr stands for the gradient of r.

    Remark 2.1. From the equation (2.24), it is observed that if r of an (LP-K)n is constant, then r=n(n1).

    In this section, we first prove the following result:

    Theorem 3.1. In an (LP-K)n admitting a -RYS, the scalar curvature r of the manifold satisfies the Poisson's equation Δr=Ψ, where Ψ=4(n1)Λσ+2r(n3)+(n1){h2a22(n24n+1)}, σ0.

    Proof. Let the metric of an (LP-K)n be a -RYS, then in view of (2.19), (1.8) takes the form

    (£Fg)(X,Y)=2ρS(X,Y)+2{ρnΛ+σr2}g(X,Y)+2ρη(X)η(Y)2aρg(X,φY),      (3.1)

    for any X, Y on M.

    Taking the covariant derivative of (3.1) with respect to Z, we find

    (Z£Fg)(X,Y)=2ρ(ZS)(X,Y)+σ(Zr)g(X,Y)2ρ{g(X,Z)η(Y)+g(Y,Z)η(X)}+2aρ{g(φZ,Y)η(Y)+g(φZ,X)η(Y)}4ρη(X)η(Y)η(Z). (3.2)

    As g is parallel with respect to , then the following formula [38]

    (£FXgX£Fg[F,X]g)(Y,Z)=g((£F)(X,Y),Z)g((£F)(X,Z),Y)

    turns to

    (X£Fg)(Y,Z)=g((£F)(X,Y),Z)+g((£F)(X,Z),Y).

    Due to the symmetric property of £V, we have

    2g((£F)(X,Y),Z)=(X£Fg)(Y,Z)+(Y£Fg)(X,Z)(Z£Fg)(X,Y),

    which, by using (3.2), becomes

    g((£F)(X,Y),Z)=ρ{(ZS)(X,Y)(XS)(Y,Z)(YS)(X,Z)}+σ2{(Xr)g(Y,Z)+(Yr)g(X,Z)(Zr)g(X,Y)}2ρ{g(X,Y)+η(X)η(Y)}η(Z)+2aρg(φX,Y)η(Z).

    By putting Y=ξ and using (2.3), (2.1), (2.5), (2.17), and (2.18), the preceding equation gives

    (£F)(Y,ξ)=2ρ{QY(n1)Y}+σ2{(Yr)ξ+(ξr)Y(Dr)η(Y)}. (3.3)

    By using the relation (2.20) in (3.3), we have

    (£F)(Y,ξ)=2ρ{QY(n1)Y}+σ2{g(Dr,Y)ξ+2(rn(n1))Y(Dr)η(Y)}+σ2{(Ya2)ξ+(ξa2)Y(Da2)η(Y)}. (3.4)

    The covariant derivative of (3.4) with respect to X leads to

    (X£F)(Y,ξ)=(£F)(Y,X)2ρ{QY(n1)Y}η(X)2ρ(XQ)Y+σ(rn(n1)){η(Y)Xη(X)Y}+σ2(ξa2)η(X)Y+σ2g(XDr,Y)ξσ2(XDr)η(Y)+σ2(Dr)g(X,Y)+σ2{(Ya2)X+X(ξa2)YX(Da2)η(Y)+(Da2)g(X,Y)}, (3.5)

    where (2.1), (2.4), and (3.4) are used.

    Again, in [38], we have

    (£FR)(X,Y)Z=(X£F)(Y,Z)(Y£F)(X,Z),

    which, by setting Z=ξ and using (3.5), becomes

    (£FR)(X,Y)ξ=2ρ{η(Y)QX(n1)η(Y)Xη(X)QY+(n1)η(X)Y}2ρ{(XQ)Y(YQ)X}+σ2(ξa2){η(X)Yη(Y)X}+σ2{g(XDr,Y)ξg(YDr,X)ξ(XDr)η(Y)+(YDr)η(X)}+2σ(rn(n1)){η(Y)Xη(X)Y}+σ2{(Ya2)X+X(ξa2)YX(Da2)η(Y)+(Xa2)YY(ξa2)X+Y(Da2)η(X)}. (3.6)

    Now, by putting Y=ξ in (3.6) and using (2.5), (2.1), (2.17), and (2.18), we have

    (£FR)(X,ξ)ξ=σ2{(ξa2)4(rn(n1))}(X+η(X)ξ)+σ2{η(XDr)ξg(ξDr,X)ξ+(XDr)+(ξDr)η(X)}+σ2{(ξa2)X+X(ξa2)ξ+X(Da2)+(Xa2)ξξ(ξa2)X+ξ(Da2)η(X)}. (3.7)

    For the h constant, we assume that Da2=hξ, and hence we deduce the following values:

    (i)ξa2=h, (ii)X(Da2)=hXhη(X)ξ,(iii)X(a2)=hη(X). (3.8)

    In light of (3.8), (3.7) reduces to

    (£FR)(X,ξ)ξ=σ2{h+4(rn(n1))}(X+η(X)ξ)+σ2{η(XDr)ξg(ξDr,X)ξ+(XDr)+(ξDr)η(X)}. (3.9)

    By contracting (3.9) over X, we lead to

    (£FS)(ξ,ξ)=hσ(n1)22σ(n2)(rn(n1))+σ2Δr, (3.10)

    where (2.26) is used and Δ symbolizes the Laplacian operator of g.

    The Lie derivative of (2.15) along F gives

    (£FS)(ξ,ξ)=2(n1)η(£Fξ). (3.11)

    By setting X=Y=ξ in (3.1) and using (2.3), (2.1), (2.5), and (2.16), we have

    (£Fg)(ξ,ξ)=2Λσr. (3.12)

    The Lie derivative of 1+g(ξ,ξ)=0 gives

    (£Fg)(ξ,ξ)=2η(£Fξ). (3.13)

    Now, combining (3.10)–(3.13), we deduce

    Δr=Ψ, (3.14)

    where Ψ=4(n1)Λσ+2r(n3)+(n1){h2a22(n24n+1)}, σ0.

    For the smooth functions θ and Ψ, an (LP-K)n satisfies Poisson's equation if θ=Ψ holds. In the case; where θ=0, Poisson's equation transforms into Laplace's equation. This completes the proof of our theorem.

    A function υC(M) is said to be subharmonic if Δυ0, harmonic if Δυ=0, and superharmonic if Δυ0. Thus, from (3.14), we state the following corollaries:

    Corollary 3.1. In an (LP-K)n admitting a -RYS, we have

    The values of scalar curvature (r) Harmonicity cases
    (n1)(n3){a2+(n24n+1)h22Λσ} subharmonic
    =(n1)(n3){a2+(n24n+1)h22Λσ} harmonic
    (n1)(n3){a2+(n24n+1)h22Λσ} superharmonic

    Corollary 3.2. In an (LP-K)n admitting a -RYS, the scalar curvature r of the manifold satisfies the Laplace equation if and only if

    r=2(n1)Λ(n3)σ(n1)(n3){h2a2(n24n+1)},σ0. (3.15)

    Let an (LP-K)n admit a -RYS, and if the scalar curvature r of the manifold satisfies Laplace's equation, then (3.15) holds. If this value of r is constant, then by virtue of Remark 2.1, we find Λ=σ2(n+h2a21). Thus, we have:

    Corollary 3.3. In an (LP-K)n admitting a -RYS, we have

    Condition Values of σ Values of Λ Conditions for the -RYS to be shrinking, steady, or expanding
    n1+h2>a2 (i) σ>0 (ii) σ=0 (iii) σ<0 (i) Λ<0 (ii) Λ=0 (iii) Λ>0 (i) shrinking
    (ii) steady
    (iii) expanding
    n1+h2=a2 σ>0, =0 or <0 Λ=0 steady
    n1+h2<a2 (i) σ>0 (ii) σ=0 (iii) σ<0 (i) Λ>0 (ii) Λ=0 (iii) Λ<0 (i) shrinking
    (ii) steady
    (iii) expanding

    This section explores the properties of gradient -RYS on (LP-K)n.

    Let M be an (LP-K)n with g as a gradient -RYS. Then (1.9) can be written as

    XDf+ρQX+(Λσr2)X=0, (4.1)

    for all X on (LP-K)n, where D indicates the gradient operator of g.

    The covariant differentiation of (4.1) along Y leads to

       YXDf=ρ{(YQ)X+Q(YX)}+σY(r)2X(Λσr2)YX. (4.2)

    By virtue of (4.2) and the curvature identity R(X,Y)=[X,Y][X,Y], we find

    R(X,Y)Df=ρ{(YQ)X(XQ)Y}+σ2{X(r)YY(r)X}. (4.3)

    By contracting (4.3) along X, we have

    S(Y,Df)={ρ(n1)σ2}Y(r). (4.4)

    From (2.15), we have

    S(ξ,Df)=(n1)g(ξ,Df). (4.5)

    Thus, from (4.4) and (4.5), it follows that

    g(ξ,Df)=ρ(n1)σ2(n1)g(ξ,Dr). (4.6)

    Now, we divide our study into two cases, as follows:

    Case I. Let ρ=(n1)σ. For this case, we prove the following theorem:

    Theorem 4.1. Let an (LP-K)n admit a gradient -RYS and ρ=(n1)σ. Then, (LP-K)n possesses a constant scalar curvature r.

    Proof. Let ρ=(n1)σ. Then, from (4.6), we obtain

    g(ξ,Df)=0. (4.7)

    The covariant derivative of (4.7) along X gives

    X(f)+(Λσr2)η(X)=0, (4.8)

    where (2.9), (2.19), (4.1), and (4.7) are used.

    By setting X=ξ in (4.8), and then using (4.7) and (2.1), we infer that

    Λ=σr2, (4.9)

    which informs us that r is constant. This completes the proof.

    Corollary 4.1. Let an (LP-K)n admit a gradient -RYS and ρ=(n1)σ. Then, we have:

    Values of σ Values of r Values of Λ Conditions for the -RYS to be shrinking, steady, or expanding
    σ>0 (i) r>0
    (ii) r=0
    (iii) r<0
    (i) Λ>0
    (ii) Λ=0
    (iii) Λ<0
    (i) expanding
    (ii) steady
    (iii) shrinking
    σ=0  r>0, =0 or <0  Λ=0 steady
    σ<0 (i) r>0
    (ii) r=0
    (iii) r<0
    (i) Λ<0
    (ii) Λ=0
    (iii) Λ>0
    (i) shrinking
    (ii) steady
    (iii) expanding

    Now, from (4.8) and (4.9), we conclude that

    X(f)=0. (4.10)

    This indicates that the gradient function f of the gradient -RYS is constant on (LP-K)n. Thus, we have

    Corollary 4.2. Let an (LP-K)n admit a gradient -RYS and ρ=(n1)σ. Then the function f is constant, and hence the gradient -RYS is trivial. Moreover, (LP-K)n is an Einstein manifold.

    Case II. Let ρ(n1)σ. For this case, we prove the following theorem:

    Theorem 4.2. Let an (LP-K)n admit a gradient -RYS and ρ(n1)σ. Then the gradient of the potential function f is pointwise collinear with ξ.

    Proof. Replacing X=ξ in (4.3), then using (2.12) and Lemma 2.5, we have

    R(ξ,Y)Df=ρ{QY+(n2)Yη(Y)ξ+aφYξ(a)φY}+σ2{ξ(r)YY(r)ξ}.

    Also from (2.12), we have

    R(ξ,Y)Df=g(Y,Df)ξη(Df)Y=Y(f)ξξ(f)Y.

    By equating the last two equations, we have

    Y(f)ξξ(f)Y=ρ{QY+(n2)Yη(Y)ξ+aφYξ(a)φY}+σ2{ξ(r)YY(r)ξ}. (4.11)

    By contracting Y in (4.11), we have

    ξ(f)=ρn1{rn(n2)1a(aξ(a))}σ2ξ(r). (4.12)

    Now, from (2.20), (2.24), (2.25), and (3.8), we easily find

    X(r)=2(rn(n1))η(X)+X(a2). (4.13)

    This implies

    ξ(r)=h+2(rn(n1)), (4.14)

    where g(ξ,Da2)=h.

    By using (4.14) in (4.12), we obtain

    ξ(f)=ρn1{rn(n2)1a(aξ(a))}σ(rn(n1))hσ2. (4.15)

    From (4.11) and (4.15), it follows that

    Y(f)ξ=ρn1{rn(n2)1a(aξ(a))}Yρ{QY(n2)Y+η(Y)ξaφY+ξ(a)φY}+σ(rn(n1))η(Y)ξσ2Y(a2)ξ. (4.16)

    The inner product of (4.16) with ξ and using (2.2), (2.1), (2.5), and (2.15) gives

    Y(f)=ρn1{rn(n2)1a(aξ(a))}η(Y)+σ(rn(n1))η(Y)hσ2η(Y), (4.17)

    where we assumed Da2=hξ.

    From (4.17), we conclude that Df=kξ, where k is a smooth function given by

    k=ρn1{rn(n2)1a(aξ(a))}+σ(rn(n1))hσ2.

    This completes the proof.

    We consider the 3-dimensional manifold M={(u1,u2,u3)R3,u3>0}, where (u1,u2,u3) are the standard coordinates in R3. Let e1,e2, and e3 be the vector fields on M given by

    e1=eu3u1,   e2=eu3u2,   e3=eu3u3=ξ,

    which are linearly independent at each point of M.

    Define a Lorentzian metric g on M such that

    g(e1,e1)=g(e2,e2)=1,   g(e3,e3)=1.

    Let η be the 1-form on M defined by η(X)=g(X,e3)=g(X,ξ) for all X on M; and let φ be the (1, 1)-tensor field on M is defined as

    φe1=e2,   φe2=e1,   φe3=0.

    By applying the linearity of φ and g, we have

    {η(ξ)=g(ξ,ξ)=1,   φ2X=X+η(X)ξ,   η(φX)=0,g(X,ξ)=η(X),   g(φX,φY)=g(X,Y)+η(X)η(Y), (5.1)

    for all X, Y on M.

    Let be the Levi–Civita connection with respect to the Lorentzian metric g. Thus, we have

    [e1,e2]=[e2,e1]=0,   [e1,e3]=e1,   [e2,e3]=e2.

    With the help of Koszul's formula, we easily calculate

    eiej={e3,  1i=j2,ei,  1i2, j=3,0,otherwise. (5.2)

    One can also easily verify that

    Xξ=Xη(X)ξ   and   (Xφ)Y=g(φX,Y)ξη(Y)φX.

    Hence, M is a Lorentzian para-Kenmotsu manifold of dimension 3. By using (5.2), we obtain

    R(e1,e2)e1=e2,   R(e1,e3)e1=e3,   R(e2,e3)e1=0,
    R(e1,e2)e2=e1,   R(e1,e3)e2=0,   R(e2,e3)e2=e3,
    R(e1,e2)e3=0,   R(e1,e3)e3=e1,   R(e2,e3)e3=e2.

    Now, with the help of the above components of the curvature tensor, it follows that

    R(X,Y)Z=g(Y,Z)Xg(X,Z)Y. (5.3)

    Thus, the manifold is of constant curvature.

    From (5.3), we get S(Y,Z)=2g(Y,Z). This implies that

    QY=2Y. (5.4)

    Now, by putting Y=ξ in (2.21), then using (5.1) and (5.4), we obtain Qξ=0. This proves Lemma 2.3. Next, by contracting S(Y,Z)=2g(Y,Z), we find r=6. Since r is constant, therefore, (2.24) leads to ξ(r)=0r=6, where n=3. This proves Remark 2.1.

    In the present study, we obtain certain important results on (LP-K)n admitting a -RYS and a gradient -RYS. First, we prove that the scalar curvature r of (LP-K)n admitting a -RYS satisfies Poission's equation, and we discuss the conditions for the -RYS to be shrinking, steady, and expanding. Furthermore, we deal with the study of gradient -RYS on (LP-K)n in two cases: (i) ρ=(n1)σ; in this case, we showed that the gradient function f of the gradient -RYS is constant, and hence the gradient -RYS is trivial. Moreover, (LP-K)n is an Einstein manifold; (ii) ρ(n1)σ, in this case, we proved that if an (LP-K)n admits a gradient -RYS, then the gradient of the potential function f is pointwise collinear with ξ.

    Abdul Haseeb: Conceptualization, investigation, methodology, writing–original draft; Fatemah Mofarreh: Investigation, methodology, writing–review & editing; Sudhakar Kumar Chaubey: Conceptualization, methodology, writing–review & editing; Rajendra Prasad: Conceptualization, investigation, writing–review & editing. All authors have read and approved the final version of the manuscript for publication.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The authors are really thankful to the learned reviewers for their careful reading of our manuscript and their insightful comments and suggestions that have improved the quality of our manuscript. The author Fatemah Mofarreh (F. M.), expresses her thankful to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R27), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Also, the author Sudhakar Kumar Chaubey was supported by the Internal Research Funding Program of the University of Technology and Applied Sciences, Shinas, Oman.

    The author Fatemah Mofarreh (F. M.), expresses her thankful to Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R27), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

    The authors declare no conflicts of interest.



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