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In smart grid, the demand side management (DSM) techniques need to be designed to process a large number of controllable loads of several types. In this paper, we proposed a framework to study the demand side management in smart grid which contains a variety of loads in two service areas, one with multiple residential households, and one bus with commercial customers. Specifically, each household may have renewable generation as well as interruptible and uninterruptible appliances to make individual scheduling to optimize the electric energy cost by making the best time of the electricity usage according to the day ahead forecast of electricity prices. A high load bus represents a commercial area employed to demonstrate the impact of high load at any bus on voltage profile, power loss, and load flow condition, and to show the performance of the proposed DSM for large number of appliance. Using the developed simulation model, we examine the performance of the proposed DSM and study their impact on the distribution network operation and renewable generation, overall voltage deviation, real power loss, and possible problems such as reverse power flows, voltage rise have examined and compared, these problems can easily be seen at the commercial load bus.

In the past extensive researches have been conducted on demand side management (DSM) program which aims at reducing peak loads and saving electricity cost. In this paper, we propose a framework to study decentralized household demand side management in a residential distribution network which consists of multiple smart homes with schedulable electrical appliances and some rooftop photovoltaic generation units. Each smart home makes individual appliance scheduling to optimize the electric energy cost according to the day-ahead forecast of electricity prices and its willingness for convenience sacrifice. Using the developed simulation model, we examine the performance of decentralized household DSM and study their impacts on the distribution network operation and renewable integration, in terms of utilization efficiency of rooftop PV generation, overall voltage deviation, real power loss, and possible reverse power flows., Comment: 5 pages, 7 figures, ISGT 2018 conference

Nowadays common practice in deploying photovoltaic distributed generations (PVDGs) is customer-based installation in the distribution network. Increasing level of PVDG applications and expedite approval by utilities have raised concern about the negative impacts of PVDG installations on the distribution network operations such as reverse power flows and undesirable voltage fluctuations. One potential solutions is to optimize the siting and sizing of these distributed renewable generation resources. This paper presents a comparative study on both optimal and randomized installation of PVDGs with the latter modeling real life customer-based renewable integration. The proposed models examine and compare the impacts of PVDG installation on distribution network operation. Numerical simulations have been performed on a local distribution network model with realistic load profiles, GIS information, local solar insolation, and feeder and voltage settings. It is found that when the distribution system has a medium penetration ratio optimal PVDG installations may introduce essential improvements in terms of voltage deviation and energy loss reduction than randomized installation. However, if the penetration ratio is very low or extremely high there will be not significant difference between the two., Comment: 5 pages, 7 figures, conference

Vehicle-to-grid (V2G) technology has drawn great interest in the recent years and its efficiency depends on scheduling of charging process of plug-in electric vehicles (PEVs) as small portable power plants in smart parking lots. On the other hand, active shift from centralized to decentralized power generation and environmental concerns have caused an increase in the utilization of combined heat and power (CHP) units in power systems. The goal of this study is to develop and simulate a novel approach for combined heat and power unit commitment with PEVs for cost reduction in electric power system. A schedule for charging and discharging processes of PEVs with respect to load curve variations is proposed in this paper. A modified test system consisting of conventional TG (thermal power generating) units, CHP units, and PEVs is employed to investigate the impacts of PEVs on generation scheduling. For the modified test system, results obtained are encouraging and indicate both the feasibility of the proposed technique and its effectiveness on generation scheduling.

Demand Side Management (DSM) strategies are of-ten associated with the objectives of smoothing the load curve and reducing peak load. Although the future of demand side manage-ment is technically dependent on remote and automatic control of residential loads, the end-users play a significant role by shifting the use of appliances to the off-peak hours when they are exposed to Day-ahead market price. This paper proposes an optimum so-lution to the problem of scheduling of household demand side management in the presence of PV generation under a set of tech-nical constraints such as dynamic electricity pricing and voltage deviation. The proposed solution is implemented based on the Clonal Selection Algorithm (CSA). This solution is evaluated through a set of scenarios and simulation results show that the proposed approach results in the reduction of electricity bills and the import of energy from the grid.

Remarkable penetration of renewable energy in electric networks, despite its valuable opportunities, such as power loss reduction and loadability improvements, has raised concerns for system operators. Such huge penetration can lead to a violation of the grid requirements, such as voltage and current limits and reverse power flow. Optimal placement and sizing of Distributed Generation (DG) are one of the best ways to strengthen the efficiency of the power systems. This paper builds a simulation model for the local distribution network based on obtained load profiles, GIS information, solar insolation, feeder and voltage settings, and define the optimization problem of solar PVDG installation to determine the optimal siting and sizing for different penetration levels with different objective functions. The objective functions include voltage profile improvement and energy loss minimization and the considered constraints include the physical distribution network constraints (AC power flow), the PV capacity constraint, and the voltage and reverse power flow constraints., Comment: To be published (Accepted) in: Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference (ISGT), Washington D.C., USA, 2017