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For past recent years, electric power companies are shifting towards the major restructuring process and deregulated market scenario. Competition has been introduced in the power system all over the world with the aim of increasing the efficiency of the industrial sector and reducing the cost of electricity to the customers. In the competitive electricity markets, the power producers are required...
This paper reports on future electricity generation scenarios modelled using NEMO, a model that applies a genetic algorithm to optimise a mix of simulated generators to meet hourly demand profiles, to the required reliability standard, at lowest overall industry cost. The modelling examined the least and near least cost technology portfolios for a scenario that limited emissions to approximately one...
This paper presents a novel methodology based on Fuzzy Adaptive Particle Swarm Optimization (FAPSO) for the preparation of optimal bidding strategies by power suppliers in a competitive electricity market. The gaming by participants in a competitive electricity market causes electricity market more an oligopoly than a competitive market. In general, Competition implies the opportunities for Generation...
In this paper, particle swarm optimization method is proposed to determine the optimal bidding strategy in competitive electricity market. The market includes Generating companies (Genco's), large consumers who participate in demand side bidding, and small consumers whose demand is present in aggregate form. The effectiveness of the proposed method is tested with IEEE-30 bus system in which six generators...
This paper presents an artificial neural network (ANN) based controller for multi-area Automatic Generation Control (AGC) scheme in a deregulated electricity market. A three layer feed forward neural network (NN) is proposed for controller design and trained with Back propagation algorithm (BPA). The ANN controller has been developed for multi-area system having Poolco, bilateral and mixed transactions...
Electricity market price may not always be a reference to determine the existence of market power. This paper discusses why electricity price in a day-ahead electricity market may exhibit peaks without representing market manipulation by any of the players. We use genetic algorithms to simulate the trading behavior of artificial agents in the spot market. Two case studies are reported and the results...
Market power is one of the main concerns in the Italian electricity market. Transmission constraints and highly concentrated ownership structure in the market have been allowing firms to exercise market power and raise electricity prices above marginal cost. This paper presents a supply function equilibrium (SFE) model for analyzing the exercise of potential market power in the Italian electricity...
Load shedding is the last-resort tool for use in an extreme situation arising due to generating power deficiency and the consequent drop in power system frequency, which lead to a system collapse. Load shedding becomes a common practice for electric utilities around the world. To be effective, load shedding should be simple, rapid, and decisive. This paper deals with the problem of using optimal load...
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