This research presents new algorithms for subtransmission simultaneous substation and network expansion planning. Given an existing system model, the projected load growth in a target year and various system expansion options, the algorithms find the optimal mix of sys More
This research presents new algorithms for subtransmission simultaneous substation and network expansion planning. Given an existing system model, the projected load growth in a target year and various system expansion options, the algorithms find the optimal mix of system expansion options to minimize the cost function subject to various system constraints and single contingencies on lines and transformers.
The system expansion options considered include building new subtransmission lines/substations, the capacity to be upgraded and the service area of HV/MV substations. In this research, Genetic Algorithm (GA) with new coding, Ant Colony algorithm (AC) and hybrid Ant Colony and Genetic Algorithm (AC&GA) methods are employed. The optimization results are compared with successive elimination method to demonstrate the performance improvement.
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A hybrid genetic algorithm (GA)–simulated annealing (SA) approach, incorporating Differential Evolution (DE), fencing method (FM) as well as implicit enumeration method (IEM) is proposed in this paper for transmission expansion planning (TEP) of a grid, involving both H More
A hybrid genetic algorithm (GA)–simulated annealing (SA) approach, incorporating Differential Evolution (DE), fencing method (FM) as well as implicit enumeration method (IEM) is proposed in this paper for transmission expansion planning (TEP) of a grid, involving both HVAC and HVDC links. The use of these algorithms makes a robust proposed approach by which for a hybrid HVAC-HVDC network, TEP may be performed fast and accurately. The proposed approach is assessed and evaluated for three test systems.
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In this paper, a model is presented for the optimal power flow of an HVAC/HVDC transmission network. OPF is a fundamental tool in power system operation and planning. The model proposed for optimal power flow includes network control parameters settings and HVDC links p More
In this paper, a model is presented for the optimal power flow of an HVAC/HVDC transmission network. OPF is a fundamental tool in power system operation and planning. The model proposed for optimal power flow includes network control parameters settings and HVDC links parameters tunings. Also, excessive equipment installation for appropriate operation of the network is minimized, while the network security margin is maximized. To solve the proposed model, a hybrid evolutionary algorithm by combining Particle Swarm Optimization (PSO) and Differential Evolution (DE) is proposed. The methodology is tested on IEEE-30 test system and compared with the results from other OPF techniques. Also the impact of HVDC links on OPF studies is illustrated by numerical examples.
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ts cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of More
ts cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of power system planning studies. In literature, different methods are investigated to achieve good solutions for TEP. This paper uses Mixed Integer Linear Programming (MILP) and Mixed Integer Nonlinear Programming (MINLP) methods to study TEP. It also presents a new NLP model in which the integer variables are omitted. Moreover, the models are properly modified so that contingency conditions are also observed. Different combinations of cost functions such as the expansion cost, the operation cost and the cost of the losses are considered and compared. To reach a global optimum solution, BARON solver is applied. The proposed algorithm is applied on Garver 6-bus and IEEE-118 bus test systems. It is shown that modeling the problem by MINLP and NLP methods, in combination with a proper solver, can result in a quick optimum solution.
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The growing need of energy sources especially in industrial countries and the shortage of the fossil resources cause a great concern in many countries. Considering that in some periods of the day the energy price is increased, Demand side management is one of the soluti More
The growing need of energy sources especially in industrial countries and the shortage of the fossil resources cause a great concern in many countries. Considering that in some periods of the day the energy price is increased, Demand side management is one of the solutions that is implemented. The major change in demand side management is consideration of consumers' response to energy price variations. This paper investigates the effect of demand response implementation on cost reduction in stochastic security constraint unit commitment. Uncertainties in power system such as transmission lines and power plants outage is considered in the paper Considering that the simultaneous implementation of stochastic security constraint unit commitment and demand response is a complex and nonlinear problem that contain Continuous and discrete variables, the mixed integer programming is being used. Proposed method is simulated in simple 3 bud system and IEEE RTS 24 bus system and the results analyzed in the paper.
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