Generation Optimization and Planning To Boost
Affordable Electrification: A Case Study of Nias Island System as an Outcome of Power System Operation and Control Course at
Institut Teknologi Bandung
Ardylla Rommyonegge1,2, Kevin M. Banjar-Nahor1*, Nanang Hariyanto1
1 School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
2 PT. PLN (Persero), Indonesia
*Corresponding Author: [email protected]
Accepted: 1 April 2020 | Published: 15 April 2020
_________________________________________________________________________________________
Abstract: Electrification ratio of Nias Island in 2019 is 51.38 %, while around 281 villages are not yet electrified. The island has many potential resources for new renewable power plants. The government policy about development of electricity in isolated and small islands electric power systems requires that the operation use N-2 criteria in the generation, and fossil-based generation is still considered necessary to ensure reliable operation. Meanwhile, electrification and energy management considering economic and environmental aspects becomes a big issue in the electricity sector. This paper aims to respond to a part of such challenges by introducing a study of generation planning and optimization, using a method suitable with PLN business plan and regulations. The potential of organic waste from plantations, river topography, and utilization of solar power is considered alternatives for renewable energy. Other possible solutions include the development of transmission grids.
The N-2 criteria and the policy about reducing the consumption of fuel are taken into account. This study considers real data collected in January 2020 and uses AMPL. The methods and calculations used in this paper are taught in Power System and Control course, given for master level students at Institut Teknologi Bandung, Indonesia. As a number of students are employees of PT. PLN (Persero), the national electricity company of Indonesia, the course proves to be useful in practical settings. This paper aims to optimize generation operational cost and schedule. It has been shown that PLN is potentially able to secure cost efficiency of Rp 31,055,342,319 in one month and should maximize PLTG MPP Batam and other power plants according to the results of economic dispatch in order to obtain optimal economic operation.
Keywords: electrification, renewable energy, generation planning, generation optimization, lagrange multiplier, AMPL, economic dispatch, course
_________________________________________________________________________
1. Introduction
Nias is an archipelago located in the west of Sumatra Island with an area of 5,625 km2 consisting of four districts, one city and included in the province of North Sumatra. This area has a population of nearly 1,000,000 people with the main livelihoods being coconut farmers and fishermen. Nias Island is the largest island among the islands on the west coast of Sumatra, which has the potential as a tourist area that may equal the popular island of Bali and it has potential for plantations, such as rubber, cocoa, oil palm, coconut and other commodities, covering an area of 12,576.17 Ha.
Figure 1: Map of Nias Island
The Nias electricity system is isolated (not yet interconnected with the Sumatra Island grid) with a number of rural areas (950 villages). The system consists of two substations namely Teluk Dalam and Gunung Sitoli, 70 kV transmission system along 193.14 kms, and 20 kV distribution system consisting of 8,603.1 kms of lines, low voltage system of 1,413.77 kms of lines, and 1,152 transformer units (total of 54,757 kVA). The electricity demand is supplied from six power plants with a total capacity of 72.4 MW, with an average peak load of 24.5 MW.
The electrification ratio (ER) is percentage of ratio between number of household that electrified with number of total household.
∑
∑ (1)
ER of Nias Island is 51.38% (90,456 customers and 669 villages with electricity), about 70%
of the total villages on Nias Island enjoy electricity. The data shows that the electricity supply in Nias Island is still not evenly distributed. With an increase in population, the need for electrical energy will increase as well. On the other hand, the policy of development of electricity in isolated electric power systems and small islands, explains that the fossil based power plants still play an important role. Moreover, economic and environmental aspects are becoming big issues in electricity sector.
In PLN RUPTL (Electricity Supply Business Plan) 2019-2028, generation planning criteria on small grid or isolated area uses a deterministic method. It is based on the N-2 criteria, which states that the reserve margin must be more than the total capacity of the largest and second largest generation units (RUPTL, 2019). If those criteria are fulfilled, then generation economic optimization can be proposed.
Nowadays, there have been many discussions or studies on electricity economic operations and generation plans in isolated areas, but not specifically for Nias Island, which has many potential resources. Therefore, it needs a study regarding efficient operation of the power plant (low operating costs) and strategies to fulfill environmentally friendly electrification of Nias Island. This paper also supports the goal of the Mandatory Biodiesel Program (ESDM Minister Regulation No 41, 2018), which is to reduce the consumption and imports of fuel.
Moreover, it is supporting the RUKN (National Electricity General Plan) 2018-2037, which is the use of fuel in Diesel power plant and other oil-fired power plants must be strictly controlled and restricted.
The methods and calculations used in this paper were taught in Power system operation and Control course, given for master level students at Institut Teknologi Bandung, Indonesia. As a number of students are employees of PT. PLN (Persero), the national electricity company of Indonesia, this course proves to be useful in practical settings. The authors start with the data collection, the construction of of power-cost curves of the generators in the system from the real gathered data, and the optimization to obtain the optimum economic dispatch. The optimization of generation dispatch is performed in AMPL (A Mathematical Programming Language), a software program which allows the user to flexibly model an optimization problem, including the objective(s), the constraints. The power system operation and control course focuses on providing the students with the ability to translate any optimization problem in power systems into a mathematical model, and then model the objective(s) and constraints in a mathematical modeling program, with an intuitive script in AMPL language. In this study, the potential resources on Nias Island are also considered.
This paper aims to obtain the minimum operating costs, optimal generation operating schedules and an appropriate strategy or planning for electrification of Nias Island as a practical of Power System and Control course at ITB that suitable with PLN business plan and regulations.
2. Data and Literature Review
Nias Electricity System
The configuration of Nias electricity system is as follows.
Figure 2: Single Line Diagram of Nias Island system
Electricity loads on Nias Island are supplied from two gas power plants and four diesel power plants. However, all of them are fossil-based, as shown in detail as follows.
Table 1: Nias power plants
Power Plant Owner Capacity Resource Price (Rp/Liter) Grid
PLTD Moawo PLN 1x7,1 MW Fuel 7406 20 kV GI G Sitoli
PLTG MPP Batam IPP 1x25 MW Fuel 7406 20 kV GI G Sitoli
PLTD ASJ IPP 13x1 MW Fuel 7406 20 kV GI G Sitoli
PLTMG Nias PLN & IPP 5x6,9 MW Fuel 7406 20 kV GI G Sitoli
PLTD BGP IPP 14x400 KW Fuel 7406 20 kV GI G Sitoli
PLTD BGP IPP 13x1 MW Fuel 7406 20 kV GI T. Dalam
Table 2: Nias power plants limitation
Power Plant Code Minimum (MW) Maximum (MW)
PLTD Moawo 0,8 6
PLTG MPP Batam 1,25 25
PLTD ASJ 1 9,1
PLTMG Nias 6,9 25
GI GUNUNGSITOLI GI
TELUK DALAM
TD1 30 MVA
TD1 (30 MVA)
TD2 (30 MVA) TRANSMISI 70 KV
193,14 kms 402 tower
MPP Batam 1x25 MW
GSTLI4 1
GSTLI4 2
TDLAM4 1
TDLAM4 2
INC PLTG GB4 GB2 GB1 GB3 PS
OUT6 OUT5 OUT3 OUT2 OUT1 BUSSECTION KOPEL
KOPEL
BM4 BM3 BM2 BM1
PLTD BGP (3 MW)
PLTD ASJ (9.1MW)
EXPRES
KOTA
70 KV 70 KV
20 KV 20 KV
~
PLTD BGP (4.3 MW)
NS 5 NS4 NS3 NS2 NS1
PLTD MOAWO (7.1MW)
PLTMG NIAS5 x 5 MW
GT3 27.5 MVA
GT4 18.25 MVA
BLOCK ABLOCK B ~ ~~ ~
~~~~~
BUS SECTION
INC
INC INC
INC
PLTD BGP G Sitoli 0,4 3
PLTD BGP Teluk Dalam 1 4,3
Total 11,35 72,4
Daily load and generation schedule
The daily load pattern and schedule of all generation on Nias Island taken in January 2020 are as follows.
Table 3: Daily Load Pattern and generation operation schedule
Hour Operation (MW)
00.00 0 0 0 14,9 0 0
01.00 0 0 0 14,9 0 0
02.00 0 0 0 14,9 0 0
03.00 0 0 0 14,9 0 0
04.00 0 0 0 14,9 0 0
05.00 1,6 0 1,6 14,9 0 0
06.00 1,6 0 1,6 14,9 0 0
07.00 1,6 0 1,6 20,8 0 0
08.00 0 0 0 18,8 0 0
09.00 0 0 0 18,8 0 0
10.00 0 0 0 18,8 0 0
11.00 0 0 0 18,8 0 0
12.00 0 0 0 18,8 0 0
13.00 0 0 0 18,8 0 0
14.00 0 0 0 18,8 0 0
15.00 0 0 0 18,8 0 0
16.00 0 0 0 18,8 0 0
17.00 1,6 0 0 22,7 0 0
18.00 1,6 0 1,6 22,7 0 0
19.00 1,6 0 1,6 22,7 0 0
20.00 1,6 0 1,6 24,5 0 0
21.00 0 0 0 24,5 0 0
22.00 0 0 0 24,5 0 0
23.00 0 0 0 24,5 0 0
Subtotal 11,2 0 9,6 460,4 0 0
Total 481,2
Generation planning
For generation planning on isolated area or small grid, PLN as state-owned electric company, uses deterministic method or N-2 criteria as follows.
(2) (3)
Where RM = Reserve margin (minimum back up) G = Total generation capable power capacity
= 1st biggest generator capable power capacity
= 2nd biggest generator capable power capacity = Peak Load
Generation unit modelling
In power system, the economic dispatch requires data about input output characteristic of generation. The curve of input output characteristic approached with quadratic polynomial equation (Wood, Allen J & Bruce F Wollenberg, 1996).
(4) (5)
Where Hi = Input of Fuel consumption (Liter/hour or Mbtu/hour) Fi = Function Cost (Rp/hour)
P = Power output of generation (MW) = Constant function
Incremental Fuel Cost (IFC) reflects the changes in fuel costs that occur when there is a change in generated electric power. The lowest price of incremental cost is the cheapest generation unit (Delima & Syafii, 2016).
(6)
(7)
Figure 3: Input output characteristic of power plant
The input output characteristic of six power plants are as follows.
(a) (b)
Figure 4: (a) PLTD Moawo (b) PLTG MPP Batam characteristic
(a) (b)
Figure 5: (a) PLTD ASJ (b) PLTMG Nias characteristic
(a) (b)
Figure 6: (a) PLTD BGP Gunung Sitoli (b) PLTD BGP Teluk Dalam characteristic
Optimization
Generation optimization is to meet economical operation and optimum schedule which proper with any constraints or condition. The economic operation means process of sharing the total load to each generating unit, all generating units are controlled continuously in a certain time interval so that the optimal operation is achieved, thus power generation can be done in the most economical way (Marsudi ,2006).
Economic dispatch is the arrangement of generating systems that are committed to serving the load to minimize total production costs. Unit commitment is determining the schedule on / off the plant to be able to meet the needs of the load.
Figure 7: System with N generation; without transmission losses
Generators of each power plant unit should generate power not exceeding the maximum value and may not operate to below the minimum value. In addition, total load of generation must be equal with total power consumption without considering the transmission losses (small grid).
∑ (8) (9) Where = Total production cost
In order to solve non-linear optimization functions, especially on multivariable optimization, the Lagrange multiplier method is commonly used. Lagrange is a conventional method widely used for solving the problem of cost optimization or economic dispatch. The Lagrange function establishes the necessary conditions for finding an extrema of an objective function with constraints. Objective function ( ) and equality constraint ( ) in Lagrange method as follows (Wood, Allen J & Bruce F Wollenberg, 1996).
∑ ∑ (10) Where = Lagrange multiplier
Taking the first derivatives of the Lagrange function with respect to the independent variables allows us to find the extreme value when the derivatives are set to zero.
(11)
In addition to the cost function and the equality constraint, each generation unit must satisfy two inequalities: the power output must be greater than or equal to the minimum power permitted and the power output must be less than or equal to the maximum power permitted.
And necessary conditions (incremental cost of each generator) as follows.
(12)
(13)
(14) The flowchart of economic dispatch using Lagrange multiplier method (without transmission losses) is as follows.
START
Determine condition for an optimal dispatch:
dFi/dPi=λ Σ Pi=Pload Data input-output curves and
fuel cost to obtain Fuel cost function
Solving λ value and then each generator power value
Meet constraint ?
STOP YES
NO
1. Set generator to possibility maximum or minimum which out of constraint 2. Compute new λ (equal with incremental cost from only generator not at their limit)
3. Compute incremental cost of other generators and compared with new λ 4. If incremental cost less than new λ indicating that it is maximum
5. If incremental cost greater than new λ indicating that it is minimum
6. Rework Σ Pi=Pload, with generator that incremental cost equal to new λ
Figure 8: Flowchart of Lagrange multiplier method
When the transmission losses are taken into account, constraint equation is expanded as follows.
∑ (15)
Optimization is modeled and calculated in AMPL, a language for algebraic modeling and mathematical programming: a computer readable language for expressing optimization problems such as linear programming in algebraic notation based on Lagrange multiplier.
Some important details are shown below (Sarjiya, Galih Yudha Prawira, & Agus Yogianto, 2013).
Assumption:
Generation online in one month
Constant operation (no fault or outage)
Transmission losses is neglected Objective function:
Minimize = Constraints or subject to:
Power delivery : ∑
Limitation : 3. Methodology
In this paper, the procedure to boost affordable electrification on Nias Island as follows.
START
Generation Data collection and references : configuration, capacity, price, limitation, Fuel storage,
Fuel delivery, daily load, operation schedule
Meet up N-2 criteria on Island and rural area ?
Optimization
Economic and optimal schedule generation operation
Manual or Software calculation
Planning
Generation modelling : Function cost, assumption, objective,
constraints
Optimum than existing condition ?
Potential resources : Gas, Biomass, Photovoltaic, Mini
Hydro, Wind
Feasibility study on another potential resources : Gas, Biomass, Photovoltaic, Mini
Hydro, Wind
Another strategies for electrification :
PLTMG using gas again (not fuel), its need gas distributution planning
LTSHE (energy saving solar lights)
Rural electrification program (transmission development)
STOP
Feasible ?
YES NO
YES NO
NO
YES
Figure 9: Flowchart strategy or procedure on Nias Island electrification
4. Result and Discussion
At present, Nias Island electricity is supplied from six power plants with a capacity of 72,4 MW, and an average peak load of 24,5 MW. The amount of reserve margin is 47,9 MW. It is
bigger than first biggest generation capacity (PLTG MPP Batam 25 MW) and bigger than second biggest capacity (PLTMG Nias 25 MW).
Optimization result
Function cost equation (Fi) of each generation is obtained from fuel function (Hi) multiplied with the fuel cost.
Table 4: Generation function cost
Power Plant (Rp/hour)
PLTD Moawo
PLTG MPP Batam
PLTD ASJ
PLTMG Nias PLTD BGP G Sitoli PLTD BGP T. Dalam
From Table 3 and Table 4, the daily generation operation cost calculation are as follows (Achmad Faizal Tamin, Karnoto, & Mochammad Facta, 2018).
Table 5: Generation operation cost before optimization (daily)
Hour Daily Cost (Rp)
00.00 655431 1655315 251804 49023350 12961 407885
01.00 655431 1655315 251804 49023350 12961 407885
02.00 655431 1655315 251804 49023350 12961 407885
03.00 655431 1655315 251804 49023350 12961 407885
04.00 655431 1655315 251804 49023350 12961 407885
05.00 3210902 1655315 3219314 49023350 12961 407885
06.00 3210902 1655315 3219314 49023350 12961 407885
07.00 3210902 1655315 3219314 79705386 12961 407885
08.00 655431 1655315 251804 68576835 12961 407885
09.00 655431 1655315 251804 68576835 12961 407885
10.00 655431 1655315 251804 68576835 12961 407885
11.00 655431 1655315 251804 68576835 12961 407885
12.00 655431 1655315 251804 68576835 12961 407885
13.00 655431 1655315 251804 68576835 12961 407885
14.00 655431 1655315 251804 68576835 12961 407885
15.00 655431 1655315 251804 68576835 12961 407885
16.00 655431 1655315 251804 68576835 12961 407885
17.00 3210902 1655315 251804 90968979 12961 407885
18.00 3210902 1655315 3219314 90968979 12961 407885
19.00 3210902 1655315 3219314 90968979 12961 407885
20.00 3210902 1655315 3219314 102261233 12961 407885
21.00 655431 1655315 251804 102261233 12961 407885
22.00 655431 1655315 251804 102261233 12961 407885
23.00 655431 1655315 251804 102261233 12961 407885
Sub Total 33618638 39727561 23848353 1722012222 311052 9789251
Total 1.829.307.077
From table 5, it is seen that generation operation cost ( ) in one month is Rp 1.829.307.077 x 30 = Rp 54.879.212.319.
The model in AMPL is comprised of three parts of algorithms. They are modelling, data and running algorithm. The algorithm in AMPL is as follows.
Figure 10: Modelling algorithm
(a) (b)
Figure 11: (a) Data algorithm (b) Running algorithm
Optimization result use generated by AMPL is shown below.
Figure 12: AMPL calculation (398 iterations)
Figure 12 shows that generation operation cost ( ) in one month is Rp 794.129.000 x 30 = Rp 23.823.870.000. It has been shown that after the optimization, PLN is potentially able to save Rp 31.055.342.319 (54.879.212.319-23.823.870.000) in one month.
The optimal generation operation schedule is as follows.
Table 6: Daily Load Pattern and generation operation schedule (After optimization)
Hour Operation (MW)
00.00 0,8 2,2 1 6,9 3 1
01.00 0,8 2,2 1 6,9 3 1
02.00 0,8 2,2 1 6,9 3 1
03.00 0,8 2,2 1 6,9 3 1
04.00 0,8 2,2 1 6,9 3 1
05.00 0,8 4,08607 1 6,9 3 2,31393
06.00 0,8 4,08607 1 6,9 3 2,31393
07.00 1,21003 7,58997 1 6,9 3 4,3
08.00 0,8 4,47196 1 6,9 3 2,62804
09.00 0,8 4,47172 1 6,9 3 2,62828
10.00 0,8 4,46923 1 6,9 3 2,63077
11.00 0,8 4,47094 1 6,9 3 2,62906
12.00 0,8 4,4717 1 6,9 3 2,6283
13.00 0,8 4,47051 1 6,9 3 2,62949
14.00 0,8 4,47214 1 6,9 3 2,62786
15.00 0,8 4,472 1 6,9 3 2,628
16.00 0,8 4,46961 1 6,9 3 2,63039
17.00 1,35492 7,74508 1 6,9 3 4,3
18.00 2,14687 8,55313 1 6,9 3 4,3
19.00 2,16821 8,53179 1 6,9 3 4,3
20.00 2,88369 9,29338 1,32293 6,9 3 4,3
21.00 1,4573 7,8427 1 6,9 3 4,3
22.00 1,43321 7,86679 1 6,9 3 4,3
23.00 1,45614 7,84386 1 6,9 3 4,3
Subtotal 26,91037 124,67865 24,32293 165,6 72 67,68805
Total 481,2
Table 6 shows that (PLTMG Nias) is the cheapest generation. This operation reflects the recent condition. Otherwise, (PLTG MPP Batam) is the 2nd cheapest generation and PLN should also maximize the use of PLTG MPP Batam to reach the optimal economic operation.
Planning and strategies
Around 281 villages in Nias Island are not yet electrified. In order to speed up enhancement of electrification in isolated and rural area, it is need another generation planning and strategies. From flowchart in Figure 9, potential resources on Nias Island become a big asset to build renewable generation which is eco-friendly (Arif Febriansyah Juwito, Sasongko Pramono Hadi, & T. Haryono, 2012). Nias Island has potential in Biomass power plants that use organic waste material from plantations such as rubber or coconut. Nias has 35.067,8 ha rubber plant area with 26.476,99-ton rubber production and 44.243,1 ha coconut plant area with 34.411,23-ton coconut production (BPS-statictics of North Sumatera Provinces, 2019).
This utilization of organic waste materials not only helps the problem of electricity but also directly saves the environment damage caused by unused waste (Kiman Siregar, Rizal Alamsyah, Ichwana, Sholihati, & Saminuddin B.Tou, 2017). Biomass Power plant is able to serve until 25 kW. Indonesian government encourages the development of biomass power plants by issuing Minister of Energy and Mineral Resources Regulation No. 50, 2017. It still needs some coordination with the Regional Government to provide land and regulations regarding fuel prices long-term biomass. Topography of Nias Island has potential of micro hydro. Hydropower resource is also employed for irrigation. However, rivers and high waterfalls with good water discharge still exist in the region. The capacity of micro hydro power plant is less than 200 kW. In Figure 1, river topography is shown in blue line. Another planning (besides building new renewable energy generation) alternatives are also worth
consideration for electrifying Nias Island. Some of them are the utilization of LTSHE (Lampu Tenaga Surya Hemat Energi), rural electrification program (developing the transmission to villages not electrified from existing network). LTSHE is kind of photovoltaic, solar power is harvested by solar panel with 20 Watt peak capacity and converted into electric power and stored in a battery. The energy stored in battery is able to turn on the light. Government officially released the regulation (presidential decree No 47, 2017) about LTSHE provision for public in isolated area.
5. Conclusions
From the above case study, it is concluded that generation planning and optimization might be a major aspect in order to enhance the electrification (to boost affordable the electrification ratio of 100% from 51,38%) on Nias Island, offering efficiency of generation operational cost for PLN. This paper also has highlighted that wide area of plantations and massive production being a potential organic waste for biomass power plants. River topography on Nias Island shows that it has potential for micro hydro power plants. The utilization of solar power is also an alternative for LTSHE are introduced as well. Considering N-2 criteria, this paper proves the optimization generation operational cost and schedule using AMPL software (data taken in January 2020); PLN should be able to economize Rp 31.055.342.319 in one month and PLN should maximize PLTG MPP Batam and other power plants, to reach the optimal economic operation. The knowledge and tools taught in Power System Operation and Control course at Institut Teknologi Bandung proves to be useful in practical settings for the students having practical engineering background, and provides the students with good knowledge on power system operation, especially in small isolated areas where the power plants are still limited in number.
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