(2010). A multistage model for distribution expansion planning with distributed generation in a deregulated electricity market. Iranian Journal of Science and Technology Transactions of Electrical Engineering, 34(3), 275-287. doi: 10.22099/ijste.2010.823
. "A multistage model for distribution expansion planning with distributed generation in a deregulated electricity market". Iranian Journal of Science and Technology Transactions of Electrical Engineering, 34, 3, 2010, 275-287. doi: 10.22099/ijste.2010.823
(2010). 'A multistage model for distribution expansion planning with distributed generation in a deregulated electricity market', Iranian Journal of Science and Technology Transactions of Electrical Engineering, 34(3), pp. 275-287. doi: 10.22099/ijste.2010.823
A multistage model for distribution expansion planning with distributed generation in a deregulated electricity market. Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2010; 34(3): 275-287. doi: 10.22099/ijste.2010.823
A multistage model for distribution expansion planning with distributed generation in a deregulated electricity market
Distribution systems management is becoming an increasingly complicated issue due to the introduction of new technologies, new energy trading strategies and a new deregulated environment. In the new deregulated energy market and considering the incentives coming from the technical and economic fields, it is reasonable to consider Distributed Generation (DG) as a viable option for systems reinforcement in competition with voltage regulator devices, to solve the lacking electric power supply problem and meet the load growth requirements with a reasonable price as well as the system power quality problems. The problem of optimal placement and size is formulated in two stages; minimization of the total costs to find optimal sizing and mounting of DG with different payback time, and maximization of the social welfare to find optimal payback time. In this framework, the object function is investment costs, which are evaluated as the annualized total investment cost, plus total running cost as well as cost of Energy Not Supply (ENS) and losses. Different system conditions are assumed to indicate the effect of the system conditions on planning decision as well as the effect of DG placement on improvement of system conditions. An optimal placement, size and investment payback time is identified. The proposed two-stage model aspects of system operation and economic aspects of market operation act as good indicators for the placement of Microturbine as a common type of DG, especially in a market environment. A software package is developed for this reason, which runs each type of planning problem very fast. The proposed methodology is tested in the IEEE 30-bus test system.
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