Description The Market Surveillance Panel (MSP), in all of its periodic reports, noted that the one-hour ahead pre-dispatch demand is persistently higher than the real-time peak demand. In its latest report, the MSP has further noted that this upward bias in demand forecasting is most prevalent in certain key hours, namely hours 23 and 24. The MSP has identified this persistent over-forecast of...

Well-designed interfaces use procedural and sensory cues to increase the salience of appropriate actions and intentions. However, empirical studies suggest that cognitive load can influence the strength of procedural and sensory cues. We formalise the relationship between salience and cognitive load revealed by empirical data. We add these rules to our abstract cognitive architecture developed ...

The economic load dispatch (ELD) is one of the most important optimization problems from the view point of power system to derive optimal economy. Classically, it is to Identify the optimal combination of generation level of all generating units which minimizes the total fuel cost while satisfying the load. This classical ELD formulation has been solved by various methods like Lagrange method, ...

This paper proposes a simple enhanced augmented Hopfield Lagrange neural network (EALH) for solving economic dispatch (ED) problem with piecewise quadratic cost functions. The EALH is an augmented Lagrange Hopfield neural network (ALH), which is a combination of continuous Hopfield neural network and augmented Lagrangian relaxation function as its energy function, enhanced by a heuristic search...

Load forecasting is an important component for power system energy management system. Precise load forecasting helps the electric utility to make unit commitment decisions, reduce spinning reserve capacity and schedule device maintenance plan properly and it also reduces the generation cost and increases reliability of power systems. In this work, a fuzzy logic approach for short term load fore...

This paper presents the optimal operation of a building energy management system (BEMS), with combined heat and power (CHP) generation, thermal storage (TES), battery (BES), subject to load demand uncertainty. The main objective is reduce total operating cost (TOC) CO2 emission (TCOE). First, we develop two models forecasting, one for weekday other weekend, using artificial neural networks, lon...

Particle swarm optimization (PSO ) is an effective & reliable evolutionary based approach .Due to its higher quality solution including mathematical simplicity, fast convergence & robustness it has become popular for many optimization problems. There are various field of power system in which PSO is successfully applied. Economic Load Dispatch(ELD) is one of important tasks which provide an eco...

In this paper, we continue to analyze optimal dispatch of generation and transmission topology to meet load as a mixed integer program (MIP) with binary variables representing the state of the transmission element (line or transformer). Previous research showed a 25% savings by dispatching the IEEE 118-bus test case. This paper is an extension of that work. It presents how changing the topology...