The aim of the smart grid is to achieve more efficient, distributed and secure supply of energy over the traditional power grid by using a bidirectional information flow between the grid agents (e.g. generator node, customer). One of the key optimization problems in smart grid is to produce power among generator nodes with a minimum cost while meeting the customer demand, known as Economic Disp...

The geographically spatial and controlled distribution of fossil fuel resources, catastrophic global warming, depletion resources have forced us to integrate zero- or low-emissions energy such as wind solar, in the generation mix. These renewable are unexhausted, available around globe, free cost. advancement solar technologies has caused an appreciable decrease installed levelized costs electr...

Solving the problem of energy dispatch in a heterogeneous complex system is not a trivial task. The problem becomes even more complex considering uncertainties in demands and energy prices. This paper discusses the development of several Economic Model Predictive Control (EMPC) based strategies for solving an energy dispatch problem in a smart micro-grid. The smart grid components are described...

Since renewable energies have been and will be massively integrated, electrical power grids require more refined generation dispatch modes and smarter communication methods. In this paper, the real-time generation dispatch and communication architecture of smart grid with renewable energy are studied. Firstly, the technical characteristics and application background of smart grid communication ...

A power system operation at minimum cost is no longer the only criterion for electrical power dispatch. Combined economic emission dispatch problem is obtained by considering both the economy and emission objectives with required constraints. This problem can be solving optimization techniques. Many optimization techniques are slow for such complex optimization tasks and are not suitable for on...

Economic load dispatch (ELD) and economic emission dispatch (CEED) have been applied to obtain optimal fuel cost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. This biobjective CEED problem is converted into a single objective function using a price penalty factor app...

This paper presents a demonstration of solving combined economic and emission dispatch problems by using one of swarm intelligences, called particle swarm optimization. The objective of the combined problem can be expressed by taking both the total production cost and total emission into account with required constraints. Among potential intelligent search methods, particle swarm optimization i...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

In this paper, Hopfield Neural Network (HNN) and Lagrange Multiplier (LM) solutions to economic dispatch (ED), NOx emission dispatch (EmD), and economic-emission dispatch (EED) of a sample system consisting of six thermal generators are presented. Transmission losses are included. The results of HNN are compared with the results of LM.