DETERMINATION OF THE BEST FITTING ENERGY MIX AND DEMAND SIDE MANAGEMENT OPTIONS FOR DEPARTMENT OF MECHANICAL ENGINEERING AS A CASE STUDY WITHIN  UNIVERSITY OF MORATUWA

Considered energy options and their characteristics

Energy sources such as Diesel, Coal, Wind, Solar, LNG (Liquid Natural Gas), CEB Power and Municipal Solid waste can be considered in proposing future energy mix of Department. Some of the energy sources mentioned above are not considered in the analysis due to some reasons mentioned below.

The main problem with establishing a power plant in university premises is the lack of spare land and health issues. Therefore establishment of a coal plant is not considered as the large land area requirement and high environmental impacts.

MSW (Municipal Solid Waste) power generation is still struggling to find its place in Sri Lanka. Also there are some problems combined with it when it comes to Sri Lankan context, such as poor waste segregation measures and low LHV (Lower Heating value) due to high humidity content. Therefore the testing of viability of producing energy with MSW to meet the energy demand of University is beyond the scope of this research.

Wind speed of Colombo city area falls in range from 3.0ms-1 to 4.5ms-1 according to the wind map produced by NREL (National Renewable Energy Laboratory) America. This value range was confirmed with the air speed readings in wind turbine which is in operation in the Department of Mechanical Engineering and wind map that is created by SLSEA. This wind speed is not effectively sufficient in producing high power ratings. Therefore wind energy harnessing is also not studied further.

Biomass, Solar, Diesel (for emergency power) and CEB power are the four energy sources that are considered in energy mix proposal. Solar energy have very low greenhouse gas emissions and are adopted all over the world in various extents due to that reason. Diesel is considered only as a backup power source in this study, therefore implementation of new Diesel plants are not considered; because the available Diesel generators have the capability to fulfil the power requirement of University in an emergency situation. Energy mix and the dispatch rule are proposed in order to minimise emissions and operation costs.

Energy mix planning

For energy mix optimization, HOMER energy analysis tool was used. It follows an analytical method to carry out the optimization. It has certain limitations as inability to capture opportunity costs of renewable energy fluctuations over usage of a battery bank. This could have been eliminated with a Generic Algorithm. But in this particular optimization scenario carried out in this project, use of Net-metering is considered and therefore above mentioned limitation of HOMER is not affecting.

Biomass, Solar energy are identified as best energy resources to be considered due to their low emissions and relatively low fuel prices. Municipal solid waste and Coal were not considered due to the process complexity, high land area and emission factors. HFO and Diesel were not taken into account as their cost and emission levels are high. Wind potential of Colombo area is not significant according to NREL wind potential map. Utilization  of  the  selected  energy  resources  for  the  best  fitting  energy  mix  for electrical load of department is analyzed with HOMER based on net percent cost.

Optimization results

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Optimization results using Homer software

 

Options are ranked based on their Net Present Cost.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 Optimization results

 

Current energy mix, Grid only option that is highlighted in green colour is ranked seventh. Therefore with the results it could clearly  be  seen  that  the  options  set  in  yellow  colour has  lower  Operating cost, NPC and COE (cost of expenditure)  values compared to existing option.

Option 1 to 6 has less unit price cost and less dependency on grid. Less dependency on grid is important to improve the energy security of the system as there are issues that CEB is trying to deal at present with increasing energy demand.

The major benefit of option 8 is the less initial cost. But it should also be noticed that option 8 does not change significantly from Grid only option when look into the capacities used. Therefore when selecting best fitting energy mix must be consider only options above to option 7. Although Homer suggest best option as option 1 by considering the different cost values when considering other constraint another option above to the option 7 might be a best fitting energy mix with the constraint. Therefore options above to option 7 should be analyse further. 

Option 3 and 4 are having lower initial cost. But all other cost are higher than the option1. Therefore those options are also can not consider as good options. When consider about option 1 and 2, option 2 need two biomass generators to full fill the energy demand. Therefore option2 is having higher operating cost, NPC and COE compared to option1.

When consider about the best option that have been suggested by Homer has lower cost component except initial cost compared to other all options. Although initial cost is comparably higher than other options other cost components will cause to benefited longtermely. It is further explaining by Homer in detail in the final simulation results. Those results can be shown below to have a proper idea about the optimized result for the best fitting energy mix.

Option1 has the highest renewable fraction also. That mean 77% of the total electrical energy requirement is supplied by PV panels and Biomass generator which is consider as a renewable energy resources and remaining 23% is supplied by the Grid.

 

Cost summary of the optimised energy mix

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cost summery of the optimized result

  

                                                

Cash flow diagram of the optimized energy mix

 

 

 

 

 

 

 

 

 

 

 

 

Cash flow of the optimized result

 

Homer gives the monthly average electric production of the best fitting Energy mix with the details of electric production of each component, energy consumption and some other details related to Electrical production. This is important to have proper idea about the electrical production of best fitting energy mix. Interface for this that shown in Homer can be shown as below.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 Monthly average electric production                     

Graphical representation of the hourly distribution of AC primary load, PV Power, Biogas Generator power, Grid purchase and Grid sales is shown in figure

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hourly electrical energy distribution