SOLAR POWER FORECASTED AND PRIORITIZED RULE BASED ENERGY MANAGEMENT SYSTEM FOR HOSPITAL
In recent years, Solar Photovoltaic (PV) system has presented itself as one of the main solutions to the electricity, poverty, plaguing the majority of buildings in rural communities with solar energy potential. However, the stochasticity associated with solar PV power output owing to vagaries in we
2025-06-28 16:29:35 - Adil Khan
SOLAR POWER FORECASTED AND PRIORITIZED RULE BASED ENERGY MANAGEMENT SYSTEM FOR HOSPITAL
Project Area of Specialization Electrical/Electronic EngineeringProject SummaryIn recent years, Solar Photovoltaic (PV) system has presented itself as one of the main solutions to the electricity, poverty, plaguing the majority of buildings in rural communities with solar energy potential. However, the stochasticity associated with solar PV power output owing to vagaries in weather conditions is a major challenge in the deployment of the systems. This study will investigate the approach for maximizing the benefits of a Stand-Alone Photovoltaic-Battery (SAPVB) system via techniques that provide for optimum energy gleaning and management. A rule-based load management scheme will be developed on the basis of Battery management System and Solar Power forecasting, and will be tested for a hospital building.
This approach will allow load prioritizing, source prioritizing and shifting based on certain rules. To achieve this, the hospital load will be classified into Sensitive Loads (SLs), Important Loads (ILs) Critical Loads (CLs) and Uncritical Loads (ULs). The SLs are of extreme priority and is comprised of main sensitive load like ICU while the ILs will comprised of wards and Laboratory. The CLs will be given higher priority and therefore will be allowed to operate at their scheduled time while the ULs will be of less priority, hence can be shifted to a time where there is enough electric power generation from the PV arrays rather than the loads being operated at the time period set by the user.
The source prioritizing approach will select the best optimal source for the forecasted and actual load. This will allow to use the best optimal and cheap source. Four scenarios were created to give insight into the applicability of the proposed rule based load management scheme.
Project ObjectivesThe prime objectives of our project are listed below;
- Hospital Loads are very sensitive which needs Power at any cost for 24/7 services and our Hospitals relay on Utility Grid and Generators or PV system as a backup. Here in Pakistan we have energy scarcity where generator as a source is very expensive to meet while Solar Energy is wasted because of it’s inefficient use.
- This inefficient use of energy leads user to improper load management and for hospital, load management becomes very sensitive topic. So the hospital management choose to be on the safe zone of inefficient use of energy without any energy management.
- Forecasted Solar Power Output.
- Optimal scheduling of available energy resources.
- Optimized Load Classification and Categorization.
- Battery Charging Scheduling on the basis of forecasted Solar Power
- To develop EMS for generic MG model for both the grid connected and islanded modes of operation.
- Finding the optimal Unit Commitment (UC) and Economical Dispatch (ED) of the available Distributive Energy Resources units, to achieve load and power balance in the system, while minimizing the operation cost.
The aim of this work is to modify load profile in accordance to order of priority as determined by the user. Loads within the residential building has to be met by the SAPVB installation will be classified based on their priority to the quality of life of the user. The loads will be classified in order of priority as it will affects the quality of life of the user.
After load classification the load management will be done on the basis of two main factors Solar Power (predicted from the solar irradiance) and the state of battery. For the SAPVB system, the idea of load management employed is based on load peaking i.e. satisfy loads so as to maximize available energy from the PV arrays; unlike the conventional approach employed by utilities where loads are being shed to manage available generation [18]. This load management scheme aims at maximizing available output of the PV array, managing loads in a priority-based fashion as well as maintaining battery charge levels within desired limits.
We will test our model for four-4 scenarios and these scenarios will be decided on the solar power predicted on the basis of subsequent solar power, in first-1st scenario the performance of the SAPVB will be evaluated without the proposed rule based energy management scheme (the user’s load profile will be fixed). Both the CLs and ULs will be supplied by solar PV with battery backed up in the day time while both type of loads will be supplied with battery only during the night time.
In the second-2nd scenario, both the CLs and ULs will be supplied by solar PV with battery backed up in the day time while both will be supplied with the battery only during the night time (Scenario for predicted normal sunny day).
In the third-3rd scenario, PV with battery backup will be used to supply the CL while only PV is used to supply the UL during the day. However, during the night period, the CL will be supplied using the battery while the UL be left out without any supply (Scenario for predicted overcast conditions).
In this fourth-4th scenario, only PV supplies both the CLs and the ULs during the day time, during the night time, the battery is supplying the CLs while the ULs are left without any supply. (Scenario for predicted extremely bad weather conditions).
In this way the power line of the less critical loads will be de-energized and will only be energized at the time when there is sufficient solar irradiation. Owing to variation in solar irradiance characteristics from the site, module performance will also vary likewise. Thus, for optimum energy gleaning, an optimum module selection procedure using capacity factor estimation based on probabilistic approach in [3] will be employed to determine the optimum solar module.
Figure 1 SAPVB SYSTEM ARCHITECTURE
The load management approaches will be investigated and will be tested via simulation in Matlab environment.
Benefits of the ProjectBenefits of the Project are listed below;
- Optimum Energy Gleaning and Management model for Hospital.
- Optimal selection of Number of solar modules and battery size.
- To maximize savings in electricity bills by decreasing power drawn from the utility grid.
- To prolong Battery Life.
- To manage load while not compromising consumer comfort.
| Serial Number | Project Requirement | Source |
| 1 | MATLAB 2020a | MATHWORK |
| 2 | Load Profile Data Set | From a field hospital (Khyber teaching hospital Peshawar) |
| 3 | Solar Designing System | optimal designing and sizing of Solar System |
| 4 | EMS Model | GitHub |
| Elapsed time in (days or weeks or month or quarter) since start of the project | Milestone | Deliverable |
|---|---|---|
| Month 1 | Reseach Work | Literature Review |
| Month 2 | Write the Proposal | Handed over to supervisor |
| Month 3 | Designing the Algorithms | Completed the final optimal Algorithm |
| Month 4 | Software Development | Completed the software simulation |
| Month 5 | Load Profiling | Load Calculated and load forecasted |
| Month 6 | Solar Designing | Designed optimal solar system with the roof top available. |
| Month 7 | Testing | tested the model with the hospital specific load for different scenarios |
| Month 8 | Final Build | final Testing on the system |
| Month 9 | Thesis and Research Paper Writing | writing research paper and thesis work |