Abstract:
In most instances, consumers have very little influence on the design of electricity market. Most electricity markets do not treat consumers as a genuine demand side capable of making rational decisions but simply as a load that need to be served under all conditions. If the demand side is allow for participating in the market then it would make electricity market more efficient and more competitive.
With keeping this in mind, a market model has been proposed and analyzed in which both generators and consumers are participants; with energy and reserve are jointly dispatched. A simultaneous market for reserve considers spinning reserve from generators and interruptible loads. It is all about encouraging flexibility in the use of electricity by demand-side.
Traditional formulation of the scheduling problem is not valid when load reduction is available. So, a composite model for optimal generation and load shedding scheduling is developed here. The market structure considered as a competitive power pool which accepts bids from both the generators and the consumers for energy and reserve and these form the objective function of the scheduling problem. This is minimized subject to several operating constraints. This formulation results into a mixed-integer nonlinear optimization problem which is solved using a new approach based on Hybrid Particle Swarm Optimization (HPSO) method. For handling the system constraints in HPSO, a method based on preserving feasibility of solution is applied.
An approach based on the combination of Artificial Neural Network (ANN) and PSO is proposed to solve the scheduling problem. The extra scheduling introduced by demand side bidding in the reserve offers significant gains in economic efficiency.
