Forecasting based Optimal Scheduling in Micro Grid

Project Title

Forecasting based Optimal Scheduling in Micro Grid

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

Microgrid management is a multi-objective problem that involves purchasing and selling energy, time-variant renewable generation, and maintenance costs. The microgrid can operate freely on an island or through mode connected with the main grid. An optimization model for the management of an isolated microgrid allows the automatic grid connection to provide supportive services to the main grid, such as selling the excess renewable generation and purchasing electricity to charge the battery bank. This however, imposes a challenging task as this switching can cause frequency disturbances. Therefore, we are currently focusing on the grid-connected mode of operation only. The proposed project predicts the future load and generation using past 3-year real generation capacity data, i.e., Distributed generations (DGs), Independent Power Producers (IPPs) & Utility, and load data (electricity demand) of FEIDMC Grid station Faisalabad. Therefore, the optimal condition from the future perspective to balance supply and demand can be considered by utility. The main objective is to achieve the optimum DGs combination by analyzing the expected generation capacity and expected electricity demand to avoid any power shortage. The preference will be given to all renewable energy resources present in the system to make the model environment friendly. Artificial Neural Network will be used for the decision making. This project aims to solve multi-objective problems involving all stakeholders. It will help the national grid operators to supply continuous and economical electricity. Whereas it will also be helpful for the industries of Faisalabad city who are facing electricity shortage from last two decades. In addition, this project is helpful in achieving green and sustainable energy too by reducing dependency on fossil fuels for generation purposes

Project Objectives

This project aims to fill the gap in the literature concerning the MG management with weather data forecasted by ANN, considering the grid connection and disconnection. The optimization model allows an MG to operate in the island mode and eventually in the grid-connected mode to offer energy sale services to the main grid when there is a surplus of renewable energy. This project also proposes a new model of a battery bank that takes into account the connection and disconnection of an MG with the main grid. The other objective of the project is to study the possible use of forecasting technique for power system loads, and estimating the annually load demand.

Project Implementation Method

The previous power loadings of FEIDMC Grid station is obtained from Wapda. The power loads are measured in MWh for each available electric substation. The power load readings are based active power consumed per electric substation. The load data are collected for each month from the year of 2017 to 2019 and these data are taken as the reference data for the entire forecasting works. This project intents to forecast the load connected to FEIDMC grid station  for the following year of 2021 and 2022.

The work is performed using EXCEL software to derive an equation based on the existing data. EXCEL curve fitting tool known in the insert and layout has the ability to generate various types of equations. The next step is to use MATLAB to derive an ANN approach by training the neurons in the specific layers. These layers consist’s of single input layer, one or more hidden layers and single output layer. The input layer contains of a number of neurons equals to the number of input variables in the training network by an iterative process. The weights are adjusted using some learning algorithms. For the purpose of forecasting in this project, ANN will be used in dynamic load forecasting after the static load forecasting is conducted. The forecasting work is conducted by substituting the variable parameters into each equation. EXCEL will be utilized to plot column graphs and line graphs for all data.

Benefits of the Project

Load forecasting problem is receiving great and growing attention as being an important and primary tool in power system planning and operation. Microgrid management is a multi-objective problem that involves purchasing and selling energy, time-variant renewable generation Importance of load forecasting becomes more significant in developing countries with high growth rate. In recent years the electrical energy consumption is increased. A noticeable increase of electric energy consumption in all over Pakistan and especially from last decade observed a significant increase in energy consumption due to developments that has recently made. Since this development will be accompanied by increasing demand for energy, so it is necessary to perform the forecasting study to estimate the increase of energy demand that meet the needs of the future development plans, and helps the authority to take the right decisions regarding the investment and future plans.  

Technical Details of Final Deliverable

Energy loss reduction: Taking advantage of the proximity between micro sources and loads, microgrids can significantly reduce the energy losses in electricity and heat transmission distribution and improve the utilization of renewable energy.

Reliability improvement: Since a microgrid can operate in an islanded mode if there is a fault in the main grid, the negative impact of the outages in transmission and distribution systems can be reduced, and thus, system reliability can be improved.

Enhancement of energy management: With the micro sources and loads in a microgrid being `managed in a coordinated way, the electric and/or heat power can be better shared among the local customers.

Benefits to the main grid: Via efficient energy management of microgrids, the energy import from the main grid can be reduced, which relieves power transmission/distribution line congestions. Moreover, microgrids can be used to provide additional services (such as frequency regulation) to the main grid, which potentially improves the reliability of the main grid.

Final Deliverable of the Project HW/SW integrated systemCore Industry Energy Other IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Affordable and Clean Energy, Industry, Innovation and Infrastructure, Sustainable Cities and CommunitiesRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	45500
Arduino	Equipment	5	700	3500
Relay	Equipment	5	900	4500
Displays	Equipment	5	200	1000
Motor	Equipment	3	6000	18000
Connecting Wire coil	Miscellaneous	1	500	500
Hardware design	Miscellaneous	1	8000	8000
Battery	Equipment	2	5000	10000