Voltage Control Ancillary Service Through Grid-Connected Microgrid, Its Pricing by Optimized Active Power and Reactive Power Management Using IEHO-TOPSIS Approach

Abstract

At the distribution level, the traditional approach of pricing for voltage control ancillary service shows certain disadvantages as it considers only production costs. For the optimized procurement and pricing of active power and reactive power provision from reactive power compensating devices (RPCDs) such as APFCs, D-STATCOM and converter-controlled distributed generators (CCDGs), its location, availability, as well as its capability, are of utmost importance. For better pricing signals, the pricing structure for active power and reactive power compensation service needs to consider all major cost components like depreciation cost, cost of losses, capital cost, and balance of system cost. In this work, an attempt has been made to address the procurement and pricing issues at distribution level, by proposing optimized active power and reactive power management (OARPM) and developing ‘Extended Nodal Pricing Function' (‘ENPF’) for its pricing. This is specially developed for pricing the optimized active power and reactive power provision cost through RPCDs and CCDGs installed in grid-connected microgrid at distribution level achieving system performance improvement and bring economic savings. To test the impact of proposed OARPM and ENPF, five different cases are analyzed using Indian real-time distribution system data. The impact of proposed methodology is observed on 5 aspects of system performance that are dispatch of active power and reactive power, power losses minimization, objective function cost minimization, active power and reactive power DLMP and voltage control. The methodology is generic to implemented for pricing in any electricity market.

Appendices

Appendix 1

General data
The period of analysis (T)	24 h
Time step (t)	1 h
Life of plant ($ls$)	25 years
Rate of interest (rin)in %	0.12
PV module
Type	Monocrystalline
Peak power rating	250 Wp
Area per unit (A)	1.1 m2
Rated module efficiency (${\eta }_{\rm{PV}})$	15%
Temperature coefficient of efficiency (β)	0.0045
Normal operating cell temperature (NOCT)	55 °C
Temperature at rated efficiency	25 °C
Solar radiance at NOCT	800 W/m2
Capital cost per unit	0.70 $/W
Operation and maintenance cost	0.04 $/W
Balance of system cost	0.8 $/W
Depreciation cost	0.004 $/h
Lifespan	25 years
Number of PV modules (${N}_{PV})$	17
Wind energy conversion system
Make	SUZLON
Rated power	600 kW
Cut in speed ${(W}_{cin})$	4 m/s
Cut out speed ${(W}_{CO})$	20 m/s
Rated speed ${(W}_{Nor}$)	13 m/s
Hub height	90 m
Rotor diameter	20 m
Hellman coefficient used	0.35
Calculated WECS efficiency (${\eta }_{ws}$)	30%
Capital cost per unit	0.67 $/W
Operation and  maintenance cost	0.04 $/W
Lifespan ($ls$)	25 Years
Number of wind turbines (${N}_{ws}$)	6
D-STATCOM
Rated reactive power capacity (${Q}_{\rm{DSt}})$	1.5 MVAr
Coefficients of loss curve whose values ($\alpha$)	0.0067 (MW/MVAr2)
Coefficients of loss curve in $(\beta$)	0.0018 (MW)
HEP (wholesale energy Price)	100 $/MW
Automatic Power Factor Controllers (APFCs)
Number of Capacitors	6
Make	Havells
Rating of each capacitor	250 kVAr
Supply Frequency	50 Hz ± 3%
Switching	Thyristorised (automated)
Voltage	415 V

Appendix 2

Real-Time Indian 31 Bus Radial Distribution System (RDS):

Bus data			Branch data
Bus no.	Pd (kW)	Qd (kVAr)	Branch no.	From bus	To bus	R (Ω)	X (Ω)
1	0.000	0.000	1	1	2	0.089	0.026
2	25.000	0.000	2	2	3	0.080	0.077
3	48.000	8.000	3	3	4	0.089	0.047
4	80.000	47.000	4	4	5	0.081	0.052
5	0.000	44.000	5	5	6	0.090	0.014
6	15.000	153.000	6	6	7	0.080	0.021
7	25.000	109.000	7	7	8	0.080	0.047
			8	7	10	0.029	0.029
8	1772.000	374.000	9	8	9	0.011	0.086
9	90.000	44.000
10	225.000	109.000	10	10	11	0.091	0.100
			11	10	13	0.099	0.080
11	225.000	109.000	12	11	12	0.091	0.093
12	90.000	44.000
13	90.000	44.000	13	13	14	0.099	0.045
			14	13	15	0.091	0.030
14	1537.000	745.000
15	90.000	44.000	15	15	16	0.090	0.192
16	450.000	218.000	16	16	17	0.029	0.190
			17	16	20	0.090	0.140
17	495.000	240.000	18	17	18	0.021	0.915
18	90.000	44.000	19	18	19	0.020	0.770
19	90.000	44.000
20	225.000	159.000	20	20	21	0.076	0.011
21	225.000	159.000	21	21	22	0.018	0.005
			22	21	25	0.029	0.014
22	1874.000	907.000	23	22	23	0.015	0.013
23	180.000	157.000	24	23	24	0.039	0.050
24	274.000	139.000
25	225.000	109.000	25	25	26	0.071	0.038
			26	25	27	0.076	0.040
26	405.000	216.000
27	225.000	119.000	27	27	28	0.028	0.025
28	315.000	163.000	28	28	29	0.029	0.026
29	225.000	109.000	29	29	30	0.025	0.020
30	90.000	44.000	30	30	31	0.027	0.016
31	90.000	44.000