Green Campus Load Optimization

Project Title

Green Campus Load Optimization

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

The energy demand is extremely growing as time passes. This develops the need for alternate sources of energy.  Nowadays, renewable source helps in reducing carbon emissions and brings down negative effects on the climate. Demand on the grid for energy production is reduces by using renewable source. It also reduces the fossil fuel consumption. Solar energy is based on renewable source which plays an important role in the future of energy production. Producing energy with solar panels has massive advantage over fossil fuels and found cost-effective Grid interactive PV system feeds power into the grid and also generates power from the PV modules to meet their own needs. Educational institutes face energy crisis because of load shedding in the grid. This paper presents the optimal design and economical aspects of grid interactive PV system configuration for an educational campus also a comparative study is carried out for an on-grid PV system and off-grid PV-DG (Diesel generator) system. To purpose the green energy design for campus (Hybrid Optimization of Multiple Electric Renewable) software tool is used.

 The energy request is very developing step by step. This calls for substitute wellsprings of energy. Sustainable power is one among the best arrangements in gathering the expanding energy interest. It helps in decreasing worldwide carbon emanations and along these lines brings down negative effects on the climate. It additionally diminishes the weight on the framework and interest for petroleum products. Sunlight based energy is a creating fragment of our energy age blend, and it will assume a significant function later on for energy creation. Creating energy with solar boards has gigantic favorable position over petroleum products and discovered practical Grid intuitive PV framework takes care of intensity into the matrix and furthermore creates power from the PV modules to address their own issues. Instructive establishments face energy emergency in view of burden shedding in the framework. This paper presents the ideal plan and practical parts of lattice intelligent PV framework design for an instructive ground likewise a near report is completed for an on-matrix PV framework and off-network PV-DG (Diesel generator) framework. For the proposed ideal plan of the PV framework HOMER (Hybrid Optimization of Multiple Electric Renewable) programming apparatus is utilized.

Project Objectives

The main objectives of this project is to reduce energy consumption cost for campus. Other aims are as follow 
Monitoring and analyzing of campus energy consumption patterns to identifying wastage of energy under specific conditions.
To optimize load management using different techniques.
To provides the cost analysis for hybrid energy system and also, associate the benefits from the analysis.
To calculate the reduced CO2 emission.

Project Implementation Method

Step 1 First utilize the real-time load measurements, obtained from load analysis of campus, to build a power consumption model. This model can be used to approximate the power consumption of each energy consumption building.
Step 2 Then, we start with developing the Electric wiring diagram using AutoCAD which includes the use of different symbols depending on the type, but the components remain the same. Diagrams will show receptacles, lighting, interconnecting wire routes, and electrical services within a home. This includes circuit breaker boxes and any alarms that are wired into the system. 
Step 3 In this step will apply the optimization techniques to reduce energy consumption by using different sensors. For instance we can use motion sensors to control office lights or LDR sensors to control outdoor lights.
Step 4 This step involves the optimizing the acquired data by HOMER. This software will provide the best suggestion for renewable source for given condition, to maximize the power obtained from renewable source, for green campus.
Step 5 This step involves adoption of such techniques where we can minimize the unit consumed when the consumption of energy increase during peak hours and during off peak hours when demand is low respectively returning the excessive power to grid to minimize the annual capital cost.
Step 6 The final step is to check whether the entire operation was successful in bringing change in the atmosphere means reduction of the pollutants such as carbon emission. 

Benefits of the Project

The energy policy of every nation has been changed significantly to allow high penetration of renewable energy in the power grid and especially in the distribution network for sustainable development. Whereas, the use of a single renewable resource is associated with power quality and stability issues so the hybrid renewable energy system can be seen as a possible solution. A hybrid optimization model is purposed for campus, which gives idea about commercial load profile. The hybrid model consist of solar-PV and biomass as non-conventional energy resources and the HOMER software is used in this study for simulation of the hybrid model for optimization and sensitivity analysis. The numbers of configurations are simulated in the HOMER and most cost-effective configuration is determined.

Because of the advancement of current data innovation, the rise of the fog processing upgrades gear computational force and gives new answers for conventional mechanical applications. For the most part, it is difficult to set up a quantitative energy-mindful model with a smart meter for load adjusting and booking improvement in small scale factories. With the emphasis on complex energy utilization issues of assembling bunches, this paper proposes an energy-mindful load adjusting and booking (ELBS) technique dependent on fog figuring. Simply, an energy utilization model identified with the outstanding load is set up on the node of fog, and an improvement work focusing on the cluster adjusting of assembling group is detailed. At that point, the improved molecule swarm enhancement (PSO) calculation is utilized to acquire an ideal arrangement, and the need for accomplishing assignments is worked towards the assembling bunch. At long last, a multi-specialist system is acquainted with accomplish the appropriated planning of assembling clusters.

In this research three different scenarios for load characteristic model based on demand response and the load optimization control method are studied. Firstly, by decoupling rigid load and flexible load, according to different degree that flexible load participates in demand response, considering the influence of different control variables, three types of load characteristics models of electricity price load, direct control load and interruptible load are constructed. Secondly, based on the established the load characteristic model proposes a reasonable load control strategy optimization control method under the condition of different practical power supply gap constraints. Finally, through three cases of scenarios, we find the control variables are direct control load and interruptible load control, the objective function is when there is a small gap between the deviating actual load reduction amount and the power supply and the demand response contract is considered in the constraint condition. 

Technical Details of Final Deliverable

The demand side management methods need to be designed to deal a countless number of controllable loads of several types in smart grid, this outcomes in expanded network supportability, as well as minimize the working cost. In this research, a purposed system is used to study decentralized demand side management in a distributed network which contains a variety of loads of two demand types. In particular, each of commercial and residential load has local non-conventional generation such as rooftop PV and by making an optimum individual scheduling will decrease the power bill with a sensible penance of client’s accommodation and comfort with respect to time-of-using (TOU) prices. In simulation model commercial load bus on bus seventeenth, with twenty-nine households employed to demonstrate the performance of the proposed DSM for large number of appliances. The efficiency of decentralized DSM and impact on the distribution network operation is examined by referring to developed simulation model. Also, in renewable generation, the examination and comparison of real power loss, overall voltage deviation, and possible problems such as reverse power flows, voltage rise are done.
In this research, a short-term load forecasting method based on combinatorial optimization of Gradient Boosting Decision Tree (GBDT) is proposed. Based on the single model, the optimal combination is established, and a GBDT load forecasting model is established. The above method is used to predict a total of 96-point loads in a certain area in southern China with 15 minutes as time interval. The effectiveness of the method is proved by comparing the Autoregressive Integrated Moving Average Model (ARIMA), Support Vector Machine (SVM) and Back Propagation Neural Network (BPNN) methods.

Today, due to the economic and political conditions of the modern world there is a rapid development of higher education system in Scotland. This develops the need for smart developments within Universities due to the high level of energy use and for low level campus facility maintenance. Purpose of this project is to suggest green energy solutions for the Campus. Different non-conventional power generating systems, solar, wind and CHP (configuration of hybrid power) systems, will be analyzed in detail and sensitivity analysis of sun intensity at specific region, wind speed, CHP size, and fuel prize of the proposed building area will be carried out using HOMER software to produce the final optimal results. By comparing optimization results in detail and taking into consideration of parameters such as cost of energy (COE) and lowest total net present cost (NPC), this report will propose suitable hybrid sustainable solutions for the campus.

Final Deliverable of the Project Hardware SystemCore Industry Energy Other Industries Health Core Technology Shared EconomyOther Technologies Wearables and ImplantablesSustainable Development Goals Affordable and Clean Energy, Industry, Innovation and Infrastructure, Climate ActionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	57100
Photo voltic module	Equipment	1	10400	10400
Ir sensors	Miscellaneous	15	100	1500
Light emitting diodes	Miscellaneous	20	10	200
Balsa wood	Equipment	75	600	45000