Might the large-scale PV power generation be reached in

China? A grid parity combined with techno-economic analysis

Hongyang Zou, Huibin Du*, Marilyn A. Brown

College of Management and Economics, Tianjin University, Tianjin

300072, China

School of Public Policy, Georgia Institute of Technology, Atlanta, GA

30332, USA

I. Introduction

II. Construction and parameter description

Outline

III. Techno-economic evaluation

IV. Grid parity estimation based on learning curve

V. Conclusions and policy implications

I. Introduction

• Pressure of carbon reduction: The electricity generated from renewable

energy will be reached at 9% in 2020 in the energy planning of National

Energy Administration of China; But in 2013, this percentage was only 2.8%.

• The new-added installed capacity of PV solar in China: up to 10.6 GW in

2014, which accounted for about 20% of total new-added installed capacity

in the world.

• The PV power generation: only 9, 000 GWh in 2013 accounting for 0.166%

of the electricity generation of China. plans to be reached at 150,000GWh

in 2020.

• Might this target be reached in 2020? When and What type of PV power

generation (grid-connected or off-grid) can be applied in large scale?

Where is more suitable to use PV power generation in China?

1. Grid-connected and off-grid PV power generation system

AC DC

PV Module

Battery

Primary Load

Converter

Grid

AC DC

PV Module

Battery

Primary Load

Converter

Diesel Generator

The structure of grid-connected PV system The structure of off-grid PV system

>2200

1800-2200

1400-1800

1000-1400<1000

kWh/m2/year

Tianjin

Xigaze

Xining

ChongqingHangzhou

2. PV systems in five cities

Solar radiation (five regions):

• More solar radiation than other countries

with a similar latitude;

• distributed unevenly;

The distribution of China’s solar radiation under the optimal slope

II. System construction and parameter description

● HOMER (Hybrid Optimization of Multiple Energy Resources), a micro-grid

software developed by the HOMER Energy LLC;

● Three main functions: simulation, optimization & sensitivity analysis.

II. System construction and parameter description (cont'd)

3. Data and Parameter description

Components Capital Replacement O&M Lifetime

PV module (1kW) 3640 3640 36.4 20 years

Converter (1kW) 800 800 0 15 years

Battery 600 600 0 10 years

Diesel generator(1kW)

1300 1300 0 15000 h

2.5

2.0

1.5

1.0

0.5

0Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Max

Daily high

Daily low

Mean

Min

3.0 (kW)

The synthesized data of load profile of residential houses

The cost of each component in PV system2.39 kW

Collected from: Annual Review and Outlook for China Solar PV industry, 2013; www.solarzoom.com; www.1688.com The picture resource comes from the HOMER software

III. Techno-economic evaluation

CitiesPV capacity

(kW)

Battery

(quantity)

Converter

capacity (kW)

Generator capacity

(kW)

Grid-

connectedAll five cities 3 1 1 /

Off-grid

Chongqing 10 30 3 5

Hangzhou 7 35 3 5

Tianjin 5 35 3 5

Xining 5 30 3 5

Xigaze 5 25 3 5

1. Technical feasibility analysis

Objective function: 𝑚𝑖𝑛 NPC (Net Present Cost)

s.t.

the electricity generated from each component in a PV system ≥ the electricity demand

The optimal system configurations of grid-connected and off-grid PV systems in five cities

III. Techno-economic evaluation (cont'd)

1. Technical feasibility analysis

Grid-connected:

PV production: more than 50%;

Xigaze: PV 5913 kWh (72.7%);

Chongqing: PV 2771 kWh (51%).

Off-grid:

The same electricity consumption: 4113

kWh/year;

The excess electricity of Tianjin is the

lowest; (the most cost-effective)

51

.0%

58

.1%

66

.4%

68

.4%

72

.7%

49

.0%

41

.9%

33

.6%

31

.6%

27

.3%

0

1

2

3

4

5

6

7

8

9

Chongqing Hangzhou Tianjin Xining Xigaze

PV production Grid purchases

42

.9%

48

.4%

51

.6%

48

.7%

41

.9%

46

.0%

38

.8%

34

.8%

38

.7%

47

.6%

0123456789

1011

Chongqing Hangzhou Tianjin Xining Xigaze

AC consumption Excess electricity Losses

The electricity generation of grid-connected PV systems

The electricity generation of off-grid PV systems

10000

12500

15000

17500

20000

22500

25000

27500

30000

32500

35000

37500

0

0.2

0.4

0.6

0.8

Chongqing Hangzhou Tianjin Xining Xigaze

NP

C (

RM

B Y

uan

)

LCO

E a

nd

reta

il ele

ctri

city

pri

ce(R

MB

Yu

an

/kW

h)

LCOE Retail price NPC

III. Techno-economic evaluation (cont'd)

0

20000

40000

60000

80000

100000

0.00

0.40

0.80

1.20

1.60

2.00

2.40

Chongqing Hangzhou Tianjin Xining Xigaze

NP

C (

RM

B Y

uan

)

LCO

E a

nd

reta

il ele

ctri

city

pri

ce(R

MB

Yu

an

/kW

h)

2. Cost-effectiveness analysis

Grid-connected:

● LCOE: 0.469-0.622 RMB Yuan/kWh;

● Xigaze: the only region, LCOE<retail price;

Off-grid:

● LCOE: 1.34-2.03 RMB Yuan/kWh;

● NPC: much more than grid-connected systems

(more energy storage batteries).

𝐿𝐶𝑂𝐸 =𝐶ann𝐸served

the total annualized cost of the system

the total electrical load served

𝐶ann = 𝐶𝑅𝐹 𝑖, 𝑁 ∗ 𝐶NPCthe total net presented cost of the PV system

capital recovery factor

The electricity generation (MWh) of grid-connected PV systems

The electricity consumption (MWh) of off-grid PV system

Levelized cost of energy

III. Techno-economic evaluation (cont'd)

3. Environmental performance

438

659737

1057

1297

29

203 202

325384

0

300

600

900

1200

1500

Xigaze Xining Tianjin Hangzhou Chongqing

CO2 emission of grid-connected PV systems (kg/year)

CO2 emission of off-grid PV systems (kg/year)

The CO2 emissions produced by grid-connected and off-grid systems in five cities

𝑀𝑖 = 𝐸𝑝 ∗ 𝐸𝐹𝑖

𝑀𝑖 : the emissions of pollutant i (kg)

𝐸𝑝: the net grid purchases (kWh) or the consumption of fuel p (kg)

𝐸𝐹𝑖 : the emissions factor of pollutant i

◆ CO2, SO2, NOX , CO and particulate matter

◆ Grid-connected > off-grid

IV. Grid parity estimation based on learning curve

Cities Learning curve Learning rate (LR)

Xigze UCt = 8.5791∗Cumt−0.193 0.1252

Xining UCt = 9.3612∗Cumt−0.191 0.1240

Tianjin UCt = 9.7109∗Cumt−0.191 0.1240

Hangzhou UCt =11.342∗Cumt−0.190 0.1234

Chongqing UCt =12.239∗Cumt−0.184 0.1197

1. The learning curve in five cities

2. Grid parity in five cities

Grid parity in future 30 years;

Xigaze: the first region (2027-2031).

The learning curve of PV power generation in five cities

𝑈𝐶𝑡 = 𝑈𝐶0 × 𝐶𝑢𝑚𝛼

𝐿𝑅 = 1 − 2𝛼

Model Formula

One-factor 𝑆𝐶 = 𝑎 × (𝐶𝐶−𝑏)

Two-factor 𝑆𝐶 = 𝑎 × (𝐶𝐶−𝑏) × (𝐾𝑆−𝑐)

Three-factor 𝑆𝐶𝑖𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛 = 𝑎 × (𝐶𝐶−𝑏) × (𝐾𝑆−𝑐)𝑄𝑑

Four-factor

𝑆𝐶

= 𝑎 × (𝐶𝐶−𝑏) × (𝐾𝑆−𝑐)𝑄𝑑(

𝑖=1

𝑛

𝑝𝑖𝑒𝑖)

Learning rate

the cost of PV power generation in time period t

the initial unit cost of PV power generation

Learning Index

Conclusions and policy implications

Xigaze has the best solar radiation and the

earliest grid parity (2027-2031).

Tianjin has the high retail electricity price and

the average solar radiation.

2. Market deployment of PV power

generation will vary across regions

(1) Remote areas in Tibei —— off-grid PV system;

(2) North China —— grid-connected PV system.

1. The diversified development of the user

market

(1) Courtyard house and single houses;

(2) High-tech industrial parks.

The LCOE of grid-connected PV systems is close

to the retail electricity price (RMB Yuan/kWh).

3. The subsidy-change strategy of PV

power generation

China’s benchmark price is reducing to 0.80, 0.88

& 0.98 RMB Yuan/kWh in 2017.

The LCOE of off-grid PV systems will drop to be

0.536 -0.870 RMB Yuan/kWh in 2050.

Grid parity will be reached in the future 30 years.

Chongqing Hangzhou Tianjin Xining Xigaze

LCOE 0.622 0.588 0.511 0.469 0.472

Retail

price0.520 0.540 0.489 0.420 0.500

Huibin Du： duhuibin@tju.edu.cn