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This paper addresses the integrated volt-var control for distribution network operation via multiobjective optimization. This paper seeks to explore the problem of energy savings and peak demand relief through the voltage reduction procedure. Currently, due to the emergence of the distribution smart grids, these procedures are gaining renewed interest and attention. The proposal presented here is for the operation phase, with a strategy based on an hourly load forecast for the next day/week, taking into account the active power intake reduction, and the voltage deviation. Therefore, the result is a set of nondominated optimal solutions, and then one may decide when, where, and how to apply them to meet different goals. The obtained solutions, for two typical distribution networks, describe relevant economic and technical benefits. Index Terms-Distribution systems, integrated volt-var control, multiobjective optimization, voltage reduction. NOMENCLATURETotal energy savings.Voltage drop at the substation bus.Active load power at bus number .Active load power at the rated voltage and frequency at bus .Reactive load power at bus number .Reactive load power at the rated voltage and frequency at bus . andVoltage exponents of active and reactive load power.Voltage magnitude at bus number .Nominal voltage of the system. Voltage drop between buses and .Line resistance between buses and .Line impedance between buses and .

Optimal and simultaneous siting and sizing of distributed generators and capacitor banks in distribution systems have attracted a lot of attention from distribution companies. The placement and capacity of these devices have direct effects on the system's performance. This paper presents a model for the simultaneous allocation of capacitor banks and distributed generation, which takes into account the stochastic nature of distributed generation. To solve the model presented, we propose an efficient hybrid method based on Tabu search and genetic algorithms. The hybrid method is applied to a well-known system in literature. Index Terms-Capacitor bank (CB), distributed generation (DG), uncertainty, Tabu search (TB), Chu-Beasley genetic algorithm (CBGA). NOTATION Sets nb, nbc, nbg Sets of system buses, candidate buses for CB installation, and candidate buses for DG installation. nlo Set of load levels. nl Set of system lines. CB f , CB s Set of fixed and switched CBs available to be installed. DG Set of DG units available to be installed.

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