The Combined Economic Emission Dispatch (CEED) problem is central to the power plant units whose performance is evaluated by minimizing the fuel cost and the quantity of gases emitted to the environment along with several equality and inequality constraints. It aims at minimizing economic input and environmental emissions hence, it is multi-objective. In this paper, the batch framework-enabled Particle Swarm Optimization named Batch Particle Swarm Optimization (BPSO) is used to solve the CEED problem. It has been solved using two test cases i.e. 10 Power Generating Units (PGU) and IEEE 30 system having 6 PGU. The results received are juxtaposed with other approaches reported in contemporary literature.

1.
S.
Shalini
and
K.
Lakshmi
, “
Solution to economic emission dispatch problem using lagrangian relaxation method
,” in
2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)
(
IEEE
,
2014
) pp.
1
6
.
2.
N.
Nabona
and
L.
Freris
, “
Optimisation of economic dispatch through quadratic and linear programming
,” in
Proceedings of the Institution of Electrical Engineers
, Vol.
120
(IET,
1973
) pp.
574
580
.
3.
S.
Muralidharan
,
K.
Srikrishna
, and
S.
Subramanian
, “
Emission constrained economic dispatch—a new recursive approach
,”
Electric Power Components and Systems
34
,
343
353
(
2006
).
4.
X.-S.
Yang
,
S. S. S.
Hosseini
, and
A. H.
Gandomi
, “
Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect
,”
Applied soft computing
12
,
1180
1186
(
2012
).
5.
L.
Benasla
,
A.
Belmadani
, and
M.
Rahli
, “
Spiral optimization algorithm for solving combined economic and emission dispatch
,”
International Journal of Electrical Power & Energy Systems
62
,
163
174
(
2014
).
6.
A.
Srivastava
and
D. K.
Das
, “
Criminal search optimization algorithm: a population-based meta-heuristic optimization technique to solve real-world optimization problems
,”
Arabian Journal for Science and Engineering
47
,
3551
3571
(
2022
).
7.
A.
Srivastava
and
D. K.
Das
, “
A new kho-kho optimization algorithm: An application to solve combined emission economic dispatch and combined heat and power economic dispatch problem
,”
Engineering Applications of Artificial Intelligence
94
,
103763
(
2020
).
8.
P.
Verma
and
R. P.
Parouha
, “
An innovative hybrid algorithm for solving combined economic and emission dispatch problems
,”
Soft Computing
26
,
12635
12666
(
2022
).
9.
H.
Nourianfar
and
H.
Abdi
, “
Environmental/economic dispatch using a new hybridizing algorithm integrated with an effective constraint handling technique
,”
Sustainability
14
,
3173
(
2022
).
10.
S.
Zaoui
and
A.
Belmadani
, “
Solution of combined economic and emission dispatch problems of power systems without penalty
,”
Applied Artificial Intelligence
36
,
1976092
(
2022
).
11.
N.
Aswan
,
M.
Abdullah
, and
A. A.
Bakar
, “
A review of combined economic emission dispatch for optimal power dispatch with renewable energy
,”
Indones. J. Electr. Eng. Comput. Sci
16
,
33
40
(
2019
).
12.
D.
Kaushik
,
M.
Nadeem
, and
S. A.
Mohsin
, “
Batch metaheuristic: a migration-free framework for metaheuristic algorithms
,”
Evolutionary Intelligence
,
1
33
(
2023
).
13.
M.
Basu
, “
Economic environmental dispatch using multi-objective differential evolution
,”
Applied soft computing
11
,
2845
2853
(
2011
).
14.
A. Abou
El Ela
,
R. A.
El-Sehiemy
,
A.
Shaheen
, and
A.
Shalaby
, “
Application of the crow search algorithm for economic environmental dispatch
,”
in
2017 nineteenth international Middle East power systems conference (MEPCON)
(
IEEE
,
2017
) pp.
78
83
.
15.
S.
Zaoui
and
A.
Belmadani
, “
Solving engineering optimization problems without penalty
,”
International Journal of Computational Methods
18
,
2150007
(
2021
).
16.
C. Edwin Selva
Rex
,
M. Marsaline
Beno
, and
J.
Annrose
, “
A solution for combined economic and emission dispatch problem using hybrid optimization techniques
,”
Journal of Electrical Engineering & Technology
,
1
10
(
2019
).
17.
X.-S.
Yang
, “
Flower pollination algorithm for global optimization
,”
in
International conference on unconventional computing and natural computation
(
Springer
,
2012
) pp.
240
249
.
18.
M.
Kheshti
,
X.
Kang
,
J.
Li
,
P.
Regulski
, and
V.
Terzija
, “
Lightning flash algorithm for solving non-convex combined emission economic dispatch with generator constraints
,”
IET Generation, Transmission & Distribution
12
,
104
116
(
2018
).
19.
S.
Akram
and
Q. U.
Ann
, “
Newton raphson method
,”
International Journal of Scientific & Engineering Research
6
,
1748
1752
(
2015
).
20.
H. R.
Bouchekara
,
A.
Chaib
,
M. A.
Abido
, and
R. A.
El-Sehiemy
, “
Optimal power flow using an improved colliding bodies optimization algorithm
,”
Applied Soft Computing
42
,
119
131
(
2016
).
21.
A.
Askarzadeh
, “
A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm
,”
Computers & structures
169
,
1
12
(
2016
).
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