In recent years, utilities around the world are developing varying levels of expertise and knowledge on how to operate power grids with increasing amounts of power generation from wind and other renewable sources. Advanced decision support tools are important to manage grids with large amounts of energy from wind and other variable energy resources. Increased uncertainty and variability in grid operations would require new decision support systems designed with Intelligent User Interfaces, in order to improve the communication between the operator and the computerized tools used in control rooms. MiDS2™ - is a web based enterprise application catering to the needs of operator with entire gamut of services to manage resources.
MiDS2™ aggregates wind power schedules and load forecast information, present and future conventional generation schedules, reserves and ramping capability into a single operator dashboard.
The solution architecture of MiDS2™ follows MVC design pattern and thus consists of three components: a presentation layer, business logic layer and a data access layer (DBMS). Being written in Java and Java based frameworks, MiDS2™ is a platform independent web based enterprise application.
The presentation layer provides a user friendly responsive interface for rich user experience and efficient user interaction. The business layer constitutes the core logic for features like schedule combination & aggregation, user management, schedule configuration management etc., whereas the data access layer completely deals with the interaction of the application with database. MiDS2™ can be coupled with any RDBMS or NoSQL. databases.
The processing algorithms in MiDS2™ include: Schedule Optimization, Short term Load Forecast, Unit Commitment, and Energy Calculations according to local grid codes.
This feature prepares the zero schedule or final schedule based on the schedules received from various energy resources and the forecasted demand. This takes into account the unit commitment process during scheduling process for any deficit or surplus of power observed.
This module takes the historical data and SCADA data on continuous basis to forecast the short term load based on the weather data supplied. The short term load forecast results will be considered as input to day-ahead demand requirements and current day generation revisions.
Based on the inputs from renewable generation schedules (wind, solar etc.), short term load forecast and conventional generation schedules (thermal, hydro, etc.), UC module will provide the revised schedules for conventional units using priority list method.
The MiDS2™ addresses the power system management problems in a manner that ensures long term as well as the short term operations, to maximize the net benefits of power production to the utility.