This paper presents the use of proposed Smart Grid Distribution Management System (SGDMS) for Singapore contestable and non-contestable consumers. The SGDMS is a distributed management system proposed using Multi-Agent System (MAS) technology. This system can optimise the distribution of renewable energy while minimizing electricity bills for consumers. The entire system was developed using Java with the extension of JADE which is an IEEE FIPA compliant multi-agent system platform. This decentralised platform allows agents to interact and communicate using energy sources from different sectors and control them intelligently to minimise the cost of electricity for the consumers. Simulation studies were carried out on the proposed system to show its potential for providing solutions through intelligent distribution techniques and how it influences the cost of electricity.
Power grid system is one of the main factors which control the distribution of the electricity to various grids. Tradition power grid is usually dispatchable and relatively inexpensive, however, it will cause significant pollution to the environment. As such, renewable energy has been extensively researched due to the generation of clean power sources. However, the generation of power cannot be accurately predicted. Hence, smart grid system is more favourable compared to traditional power grid [
In order to achieve a low carbon energy environment, power grids and renewable energy integration developments are currently carried out. However, the increasing research on such technology would incur a high cost which requires the support of the government [
The world renewable energy has been contributing 19% to the current electricity usage. Hydroelectric energy had been producing 16%, thus making wind and PV energy production modest, but it means that many initiatives can improve these renewable energies [
Renewable energy systems (RES) are not able to replace existing electrical grids as it has been established and used for ages due to its reliability. Although RES technology is not able to cope with the demand of electricity consumption these days, integrating it with the existing power grid has shown that it is able to change the system towards certain extent [
RES involves certain criteria to be practical. The criteria are reliability, efficiency, development of algorithms for advanced control, and monitoring. Therefore, availability of equipment or tools would be crucial for the research of such technology [
Ng, C. H., et al. [
W. Li., et al. [
The proposed Smart Grid Distribution Management System (SGDMS) allows smart grid to be equipped with better distribution techniques to optimise electricity costs. Additionally, the proposed system includes MAS as its communication channel that increases the reliability and efficiency of data transmission.
The remaining paper is organised as follows: Section 2 shares the information used for the proposed system. Section 3 shows the proposed SGDMS. Section 4 provides simulation results. Finally, the paper is concluded in Section 5.
Singapore power grid was distributed to 3 main sub-grids which are the industrial, commercial, and residential grids. Transport-related and others grids contain a smaller distribution of electricity. Singapore is exploring the options of alternative power resources using renewable energy to create a smart nation concept of a green country.
Singapore power grid has one of the most reliable electricity networks in the world. The grid had already deployed advanced Supervisory Control and Data Acquisition (SCADA) systems which were able to read electricity supply data to bring its power grid capabilities even further.
In Singapore, the Energy Market Authority (EMA) was set up to liberalise the electricity markets to promote reliable, secure, and effective electric supply. Energy Market Company (EMC) was established to connect the electricity makers and buyers in order to give alternative from regulated tariffs from SP Services [
The electricity prices were separated into contestable and non-contestable due to different pricing in electricity purchase. Contestable consumers are able to purchase from the electricity market using wholesale pricing run by Energy Market Company while non-contestable consumers use the regulated tariff prices from SP Services.
P day = P year / 365 (1)
P period = P day / 365 (2)
where, P year represents the total power consumption in a year, P day in a day, and P period in a period.
The average power consumption is scaled down to year, day, and period using the formula 1 and 2. Due to different periods having different prices, it can be used to calculate how much the consumers were paying per period.
The mathematic equation for renewable energy in Singapore was defined as follow:
P SG Wind/year = P Wind / 39 (3)
P SG Tidal/year = P SG Tidal/Period ∗ 365 ∗ 24 (4)
Renewable Energy | Power per annum for Singapore (MWh) |
---|---|
Wind | 0.26 |
Tidal | 8.76 |
Solar | 4800 |
Total | 4809.02 |
Year 2014 | Contestable (GWh) | Non-Contestable Consumers (GWh) | Total Singapore electricity demand (GWh) |
---|---|---|---|
Industrial | 18,528.20 | 1260.30 | 19,788.50 |
Commercial | 12,163.50 | 4790.80 | 16,954.30 |
Transport | 2,284.00 | 155.4 | 2439.40 |
Residential | 0 | 6935.80 | 6935.80 |
Others | 28.5 | 256.4 | 284.90 |
Overall | 33,004.20 | 13,398.70 | 46,402.90 |
Year 2014 | Contestable Consumer | Non-Contestable Consumers | ||||
---|---|---|---|---|---|---|
Per year (GWh) | Per day (GWh) | Per period (GWh) | Per year (GWh) | Per day (GWh) | Per period (GWh) | |
Industrial | 18,528.20 | 50.76 | 1.06 | 1260.30 | 3.45 | 0.07 |
Commercial | 12,163.50 | 33.32 | 0.69 | 4790.80 | 13.13 | 0.27 |
Transport | 2284.00 | 6.26 | 0.13 | 155.40 | 0.43 | 0.01 |
Residential | 0.00 | 0.00 | 0.00 | 6935.80 | 19.00 | 0.40 |
Others | 28.50 | 0.08 | 0.00 | 256.40 | 0.70 | 0.01 |
Overall | 33,004.20 | 90.42 | 1.88 | 13,398.70 | 36.71 | 0.76 |
where P Wind represents the total wind power generated for the region for the year, P SG Wind/year represents the wind power generated for a year in Singapore. P SG Tidal/Period represents the tidal power generated for a period in Singapore, P SG Tidal/year represents the tidal power generated for a year in Singapore.
In Singapore, the government agencies JTC Corp and the Housing Board are looking into the use of wind turbines. Small and medium-sized enterprises (SMEs) like CygnusPower and Daily Life Renewable Energy (DLRE) are exploring the usage of wind turbines to have better efficiency. Daily Life Renewable Energy (DLRE) had already built a 10 MW commercial wind farm in Sri Lanka to serve 39 countries in the Asia-Pacific region [
There had been a study that Singapore environment can extract 250 MW peak with a tidal barrage [
Time | Period | WEP ($/MWh) | Time | Period | WEP ($/MWh) |
---|---|---|---|---|---|
00:00-00:30 | 1 | 77.78 | 12:00-12:30 | 25 | 64.45 |
00:30-01:00 | 2 | 73.95 | 12:30-13:00 | 26 | 66.39 |
01:00-01:30 | 3 | 67.14 | 13:00-13:30 | 27 | 71.31 |
01:30-02:00 | 4 | 68.26 | 13:30-14:00 | 28 | 77.6 |
02:00-02:30 | 5 | 66.54 | 14:00-14:30 | 29 | 77.73 |
02:30-03:00 | 6 | 73.85 | 14:30-15:00 | 30 | 85.31 |
03:00-03:30 | 7 | 69.11 | 15:00-15:30 | 31 | 85.24 |
03:30-04:00 | 8 | 67.44 | 15:30-16:00 | 32 | 73.11 |
04:00-04:30 | 9 | 66.06 | 16:00-16:30 | 33 | 67.09 |
04:30-05:00 | 10 | 60.81 | 16:30-17:00 | 34 | 66.28 |
05:00-05:30 | 11 | 55.66 | 17:00-17:30 | 35 | 64.35 |
05:30-06:00 | 12 | 67.75 | 17:30-18:00 | 36 | 60.83 |
06:00-06:30 | 13 | 68.65 | 18:00-18:30 | 37 | 59.85 |
06:30-07:00 | 14 | 66.98 | 18:30-19:00 | 38 | 61.1 |
07:00-07:30 | 15 | 53.95 | 19:00-19:30 | 39 | 65.36 |
07:30-08:00 | 16 | 56.69 | 19:30-20:00 | 40 | 66.49 |
08:00-08:30 | 17 | 59.87 | 20:00-20:30 | 41 | 66.91 |
08:30-09:00 | 18 | 61.41 | 20:30-21:00 | 42 | 61.16 |
09:00-09:30 | 19 | 61.12 | 21:00-21:30 | 43 | 63.52 |
09:30-10:00 | 20 | 64.94 | 21:30-22:00 | 44 | 61.19 |
10:00-10:30 | 21 | 66.55 | 22:00-22:30 | 45 | 58.09 |
10:30-11:00 | 22 | 66.71 | 22:30-23:00 | 46 | 56.34 |
11:00-11:30 | 23 | 66.69 | 23:00-23:30 | 47 | 54.3 |
11:30-12:00 | 24 | 64.59 | 23:30-00:00 | 48 | 53.01 |
(NTU) designed and built 2 turbines which will extract up to a thousand watts of energy per hour combined. This test project shows the Singapore government support of tidal energy usage [
Singapore total generations of electricity by PV systems (Solar energy) were estimated to be 4.8 GWh electric energy per annum [
The mathematical formulas of the cost are defined as follows:
M cont/yr = ( ∑ i = 1 48 P cont/period ∗ P P cont ( i ) ) ∗ 365 (5)
M non-cont/yr = P non-cont/year ∗ P P non-cont (6)
M Total/yr = M cont/year + M non-cont/year (7)
where P P cont ( i ) represents the price in different period for contestable, P P non-cont for non-contestable. M cont/yr represents the total amount of electricity cost in a year for contestable, M non-cont/yr for non-contestable, and M Total/yr for the total amount of electricity cost. P non-cont/year represents the total power for non-contestable in a year, P cont/period for contestable in a period.
The equations calculate the consumer cost dependent on how the electricity is being distributed in the grid. These equations are widely used in Singapore to calculate the electricity cost for consumers.
consumption if no renewable energy is connected.
For this research,
which are the Renewable Energy System (RES) and Grid System (GS). RES was then further categorised into three parts which are the PhotoVoltaics (PV) system, Tidal Energy, and Wind Energy. GS was then further categorised into three parts which are the Industrial Grid (IG), Commercial Grid (CG), and Residential Grid (RG).
The functionality of the RES collects and calculates the data that is available to the SGDMS. GS calculates the amount of electricity that is needed for them. SGDMS will then decide how much power will be distributed to which grid. The messages set are “REQUEST”, “SUBSCRIBE”, “CONFIRM” “, “INFORM” and “CFP”. Each message sent would provide different kinds of information when it is required during the process of algorithm calculations.
Simulation studies were carried out on the following types of the distribution system which are given in
Representative | Description |
---|---|
No RES | Power Grid with no RES supply |
RES | Power Grid with evenly distributed RES supply |
RES1 | Power Grid with RES supply distributed to contestable only |
RES2 | Power Grid with RES supply distributed to non-contestable only |
Description | No RES | RES | RES1 | RES2 |
---|---|---|---|---|
Amount of RES power distribution (MWh) | ||||
Contestable | 0 | 2404.51 | 4809.02 | 0 |
Non-Contestable | 0 | 2404.51 | 0 | 4809.02 |
Total Power after RES power distribution (GWh) | ||||
Contestable | 33,004.20 | 33,001.80 | 32,999.39 | 33,004.20 |
Non-Contestable | 13,398.70 | 13,396.30 | 13,398.70 | 13,393.89 |
Average electricity usage (MWh) | ||||
Contestable for 1 period | 1883.80 | 1883.66 | 1883.53 | 1883.80 |
Average electricity price (SGD$) | ||||
Contestable for 1 day | 5,951,889.27 | 5,951,455.64 | 5,951,022.021 | 5,951,889.27 |
Contestable for 1 year | 2,172,439,582 | 2,172,281,310 | 2,172,123,038 | 2,172,439,582 |
Non-Contestable for 1 year | 2,726,635,450 | 2,726,146,133 | 2,726,635,450 | 2,725,656,815 |
Cost (SGD$) | ||||
Total for 1 year | 4,899,075,032 | 4,898,427,442 | 4,898,758,488 | 4,898,096,397 |
Savings compared to no RES | 0 | 647,589.66 | 316,544.49 | 978,634.84 |
savings by using the integrated power grid when comparing RES with the traditional power grid.
These results were understood by the amount of money saved when more renewable energy was distributed to the contestable or non-contestable electricity source with the same total electricity consumption. The simulation result shows when more power was distributed to the non-contestable electricity demand, the overall electricity pricing would be cheaper compared to the contestable electricity demand.
The results shown in
These simulations show the effects of economic impacts on the distribution of renewable energy to different sectors.
In this paper, it was shown how the use of renewable energy sources makes differences in Singapore power grid. The proposed algorithm optimises the electricity cost of consumers while maximizing the use of renewable energy sources. These simulation studies show that the proposed Smart Grid Distribution Management System (SGDMS) achieves the maximum use of
power distribution, minimises the cost of electricity bills and lowers greenhouse effects by the existing power grid.
In the view of the smart grid, this research demonstrates various types of power grid distribution and the impact on the prices based on the current electricity market. These lead to a smart nation concept which would be beneficial to the future of Singapore.
Enhancements of the SGDMS would require an increase in reliability and further improvements for optimization in order to get better efficiency of the grid. With the help of increased renewable energy sources, overloading of generators will be greatly reduced. Ultimately, this approach will step towards a more environmentally friendly and cost-effective grid system for Singapore.
The authors declare no conflicts of interest regarding the publication of this paper.
Li, W.X., Ng, C.H., Logenthiran, T., Phan, V.-T. and Woo, W.L. (2018) Smart Grid Distribution Management System (SGDMS) for Optimised Electricity Bills. Journal of Power and Energy Engineering, 6, 49-62. https://doi.org/10.4236/jpee.2018.68003