**3.2 Framework of smart dispatch**

The objective of this section is to reveal the proposed framework of Smart Dispatch. The framework outlines the basic core SD functions for RTOs/ISOs operating in the smart grid environment. Some of the functional highlights and differentiations from classical dispatch are:


One major core functions of Smart Dispatch is called Generation Control Application (GCA) which aims at enhancing operators' decision making process under changing system conditions (load, generation, interchanges, transmission constraints, etc.) in near real-time. GCA is composed of several distinct elements (Figure 4):


perspective. For example, effective presentation of multi-dimensional data to help system operators better visualize the system is very important. Beside a forward-looking view for system operators, SD should also allow after-the-fact analysis. System analysts should be able to analyze historical data systematically and efficiently, establish dispatch performance measures, perform root-cause analysis and evaluate corrective actions, if necessary. SD will become an evolving platform to allow RTOs/ISOs to make sound dispatch decisions.

The objective of this section is to reveal the proposed framework of Smart Dispatch. The framework outlines the basic core SD functions for RTOs/ISOs operating in the smart grid environment. Some of the functional highlights and differentiations from classical dispatch

One major core functions of Smart Dispatch is called Generation Control Application (GCA) which aims at enhancing operators' decision making process under changing system conditions (load, generation, interchanges, transmission constraints, etc.) in near real-time.

Fig. 3. Time and Scenario Dimensions in Smart Dispatch

GCA is composed of several distinct elements (Figure 4): Multi-stage Resource Scheduling Process (SKED 1,2&3)

Comprehensive Operating Plan (COP)

Adaptive Model Management

Extension for price-based, distributed, less predictable resources

 Congestion management with security constrained optimization Continuum from forward scheduling to real-time dispatch

 Extension for dynamic, multi-island operation in emergency & restoration After-the-fact analysis for root-cause impacts and process re-engineering

**3.2 Framework of smart dispatch** 

 Active, dynamic demand Modeling parameter adaptation

are:

The multi-stage resource scheduling (SKED) process is security constrained unit commitment and economic dispatch sequences with different look-ahead periods (e.g. 6 hours, 2 hours and 20 minutes) updating resource schedules at different cycle frequencies (e.g. 5min, 15min or hourly). The results of each stage form progressively refined regions that guide the dispatching decision space of the subsequent stages. Various SKED cycles are coordinated through the so-called Comprehensive Operating Plan (COP).

Fig. 4. Smart Dispatch Framework

COP is a central repository of various kinds of scheduling data to and from a certain class of power system applications. COP presents a comprehensive, synchronized and more harmonized view of scheduling data to various applications related to power system operations. The class of scheduling data of interest includes the followings:


COP also contains comprehensive summary information. Summary information could be rollups from a raw data at a lower level (e.g. resource level) according to some pre-defined system structures.

Adaptive Model Management as shown in Figure 4 consists of two parts: Advanced Constraint Modeling (ACM) and Adaptive Generator Modeling (AGM). ACM will use intelligent methods to preprocess transmission constraints based on historical and current network conditions, load forecasts, and other key parameters. It should also have ability to achieve smoother transmission constraint binding in time. AGM will provide other GCA components with information related to specific generator operational characteristics and performances. The resource "profiles" may contain parameters such as ramp rate, operating bands, predicted response per MW of requested change, high and low operating limits, etc. Another major core functions of Smart Dispatch is After-the Fact Analysis (AFA). AFA aims


One special use case of AFA is the so-called "Perfect Dispatch" (PD). The idea of PD was originated by PJM (Gisin et al., 2010). PD calculates the hypothetical least bid production cost commitment and dispatch, achievable only if all system conditions were known and controllable. PD could then be used to establish an objective measure of RTO/TSO's performance (mean of % savings, variance of % savings) in dispatching the system in the most efficient manner possible by evaluating the potential production cost saving derived from the PD solutions.

Demand forecast is a very crucial input to GCA. The accuracy of it very much impacts market efficiency and system reliability. The following is devoted to discuss some recent advances in techniques of demand forecasting.
