Oguzhan Ceylan

Distribution System Voltage Regulation by Distributed Energy Resources

This paper proposes a control method to regulate voltages in 3 phase unbalanced electrical distribution systems. A constrained optimization problem to minimize voltage deviations and maximize distributed energy resource (DER) active power output is solved by harmony search algorithm. IEEE 13 Bus Distribution Test System was modified to test three different cases: a) only voltage regulator controlled system b) only DER controlled system and c) both voltage regulator and DER controlled system. The simulation results show that systems with both voltage regulators and DER control provide better voltage profile.

Advanced Energy Storage Management in Distribution Network

With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. The proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. The optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. The proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.

Optimal voltage regulation for unbalanced distribution networks considering distributed energy resources

With increasing penetration of distributed generation in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative quadratic constrained quadratic programming model to minimize voltage deviations and maximize distributed energy resource (DER) active power output in a three phase unbalanced distribution system is developed. The optimization model is based on the linearized sensitivity coefficients between controlled variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DERs). To avoid the oscillation of solution when it is close to the optimum, a golden search method is introduced to control the step size. Numerical simulations on modified IEEE 13 nodes test feeders show the efficiency of the proposed model. Compared to the results solved by heuristic search (harmony algorithm), the proposed model converges quickly to the global optimum.

Harmonic elimination of multilevel inverters by moth-flame optimization algorithm

This paper solves harmonic elimination problem, and minimizes total harmonic distortion by a recently developed heuristics: moth-flame optimization method. 5th and 7th order harmonics are eliminated for a seven level cascaded multilevel inverter, and 5th, 7th, 11th and 13th order harmonics are eliminated for an eleven level cascaded multilevel inverter. Simulation results of a seven level cascaded multilevel inverter and an eleven level cascaded multilevel inverter are provided for different levels of modulation indexes. The simulation results show that moth-flame optimization model solves the harmonic elimination problem, total harmonic distortion minimization problem efficiently.

Parallel harmony search based distributed energy resource optimization

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123-bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

Optimal reactive power allocation for photovoltaic inverters to limit transformer tap changes

This paper combines an iterative approach based voltage control algorithm for allocating the reactive power outputs of distributed energy sources (DERs) with an Augmented Lagrangian voltage deviation optimization model that takes tap positions into consideration. The approach is applied to a modified IEEE 123 bus distribution test system with several PVs of varying output. Voltage variations due to the intermittent nature of the PVs in the distribution system are constrained by scheduling reactive power injections from the inverters. Allocating reactive power outputs of PVs and changing transformer tap positions allows the proposed approach to be used as an alternative to traditional distribution voltage control approaches. Simulation results show that the proposed method is able to keep voltage magnitudes in the normal voltage magnitude range with few tap operations.

A robust load shedding strategy for microgrid islanding transition

A microgrid is a group of interconnected loads and distributed energy resources. It can operate in either gridconnected mode to exchange energy with the main grid or run autonomously as an island in emergency mode. However, the transition of microgrid from grid-connected mode to islanded mode is usually associated with excessive load (or generation), which should be shed (or spilled). Under this condition, this paper proposes an robust load shedding strategy for microgrid islanding transition, which takes into account the uncertainties of renewable generation in the microgrid and guarantees the balance between load and generation after islanding. A robust optimization model is formulated to minimize the total operation cost, including fuel cost and penalty for load shedding. The proposed robust load shedding strategy works as a backup plan and updates at a prescribed interval. It assures a feasible operating point after islanding given the uncertainty of renewable generation. The proposed algorithm is demonstrated on a simulated microgrid consisting of a wind turbine, a PV panel, a battery, two distributed generators (DGs), a critical load and a interruptible load. Numerical simulation results validate the proposed algorithm.

A regression based hourly day ahead solar irradiance forecasting model by labview using cloud cover data

This paper applies a regression based numerical method for photovoltaic power output hourly forecast. The method uses a historical data composed of irradiance, azimuth, zenith angle and time of day information. In every run of the forecast program, publicly available cloud cover forecast data for the following day is obtained, and by using a numerical regression based method a function is fit. Then by using the publicly available temperature forecast data, forecasted irradiance data, and computed solar position (zenith, azimuth) data, both power output and temperature module output of PV array is computed. Numerical forecast results show that, they are in accordance with the actual data.

Optimal DG allocation and sizing in radial distribution networks by Cuckoo search algorithm

Modern smart grid implementations bring several advantages in terms of operational controls. Distributed generation and storage facilities near the load centers are probably the most important concepts that are used to improve the quality and the reliability of the consumed energy. Siting and sizing of DG generations in distribution systems may create several problems in traditional radial power systems, which were originally designed for unidirectional power flows. This paper presents an optimal DG allocation and sizing approach in a traditional distribution network where the whole year load variation is taken into account. Optimization aims to minimize both the total voltage variation, TVV, in a day and daily percentage energy losses along the feeder branches. The two objectives are first formulated as singular optimization problems and then combined in a multi-optimization problem. Meta-heuristic Cuckoo search algorithm is used to solve the resulting constrained optimization problem. The proposed formulation is applied to a 12-bus radial distribution system and the MATLAB simulations are performed to validate the performance of the approach.

A daily multiobjective optimization model in smart grids

This paper solves a daily multiobjective optimization model for efficient operation of power distribution systems. The model aims to minimize the voltage deviations, minimize power losses and minimize the energy costs of the distributed generators. The model is implemented on a modified 33 bus distribution system by including: two voltage regulators and four distributed generators. Three different simulation sets are performed: the first one includes only voltage regulators and the second one includes only distributed generators and the third one includes both voltage regulators and distributed generators. When the simulation results are compared, results show that better voltage profiles with less power losses and costs might be obtained by using both voltage regulators and distributed generators.