Recent advancement on technical requirements for grid integration of wind power

The installation of wind energy has experienced rapid development during recent years.As a result,the operation of power system can be greatly affected.Therefore,the operators of different countries have formulated the grid codes which reinforce technical requirements for wind power plants.In this paper,recent grid codes published in different countries have been carefully reviewed.The basic requirements of active power control and reactive power compensation,both of which have particular influence on wind power plants operation,are focused on.Based on this review,it is understood that with the increasing integration of wind energy,there is a worldwide trend to regulate the performance of wind power plants so that they can contribute to the stability and reliability of power system.

An online maximum power point capturing technique for highefficiency power generation of solar photovoltaic systems

This paper proposes a novel high-efficiency generation technique for photovoltaic(PV) system,named maximum power point capturing(MPPC) technique. This is an aperiodic perturbation MPPC technique compared to the conventional periodic perturbation maximum power point tracking technique. Firstly, under a closed-loop circuit and an open-loop circuit,the complete I-V curves and P-V curves are defined. Secondly, the proposed MPPC technique is based on the complete I-V curves and a practical model of solar PV systems.The proposed method realizes that maximum power point(MPP) is captured online, and its control strategy is designed to set a steady operating area around MPP. The duty cycle keeps constant when the operating point is within the steady operating area, i.e., aperiodic perturbation, and when the operating point is outside the steady operating area, MPPC is triggered to capture a new MPP with an updated steady operating area. Simulation results demonstrate that no oscillations exist in steady-state;dynamic performances are improved;and only two perturbations are required to capture the new MPP. Using the proposed MPPC method,low voltage ride through and high voltage ride through can be prevented.

Sequential quadratic programming particle swarm optimization for wind power system operations considering emissions

In this paper,a computation framework for addressing combined economic and emission dispatch(CEED)problem with valve-point effects as well as stochastic wind power considering unit commitment(UC)using a hybrid approach connecting sequential quadratic programming(SQP)and particle swarm optimization(PSO)is proposed.The CEED problem aims to minimize the scheduling cost and greenhouse gases(GHGs)emission cost.Here the GHGs include carbon dioxide(CO_(2)),nitrogen dioxide(NO_(2)),and sulphur oxides(SO_(x)).A dispatch model including both thermal generators and wind farms is developed.The probability of stochastic wind power based on the Weibull distribution is included in the CEED model.The model is tested on a standard system involving six thermal units and two wind farms.A set of numerical case studies are reported.The performance of the hybrid computational method is validated by comparing with other solvers on the test system.

A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimates maximal controllable TCL capacities at each scheduling time interval by solving a optimization model;[ the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator;and ′the TCL aggregator schedules the ON/OFFcontrol actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution(HDDE)algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.

A low-carbon oriented probabilistic approach for transmission expansion planning

Following the deregulation of the power industry,transmission expansion planning(TEP)has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment.Also,the growing concern on global warming highlights the importance of considering carbon pricing policies during TEP.In this paper,a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index.The formulated dynamic programming problem is solved by a hybrid solution algorithm in an iterative process.The performance of our approach is demonstrated by case studies on a modified IEEE 14-bus system.Simulation results prove that our approach can provide network planners with comprehensive information regarding effects of uncertainties on TEP schemes,allowing them to adjust planning strategies based on their risk aversion levels or financial constraints.

Distributed Control of Thermostatically Controlled Loads in Distribution Network with High Penetration of Solar PV

High penetration of solar energy can result in voltage rise in midday,while growth in residential air conditioning is the main contributor of overloading and voltage drop issues during peak demand time.This paper provides a hierarchical control scheme to coordinate multiple groups of aggregated thermostatically controlled loads to regulate network loading and voltage in a distribution network.Considering the limited number of messages that can be exchanged in a realistic communication environment,an event-triggered distributed control strategy is proposed in this paper.Through intermittent on and off toggling of air conditioners,the required active power adjustment is shared among participating aggregators to solve the issue.A case study is conducted and simulation results are presented to demonstrate the performance of the proposed control scheme.

Multi-objective Distributed Wind Generation Planning in an Unbalanced Distribution System

In addition to increasing penetration of distributed generation(DG),the distribution system power flow may be significantly impacted by direction and magnitude.This paper proposes a method for optimal placement of wind DG considering the unbalanced operation of distribution systems.The objective function includes static voltage stability index,three-phase unbalance index,system reliability index,and DG investment cost.The untransposed distribution lines and unbalanced load are modelled,and corresponding static voltage stability index and system reliability considering DG penetrations are derived.The expected and stochastic daily distributed generation and demand profiles in four seasons are calculated to improve the accuracy.To solve this multi-objective optimization model,a fuzzy membership function is used to integrate the four individual objectives,and a sensitivity-based method is proposed to solve the model efficiently.Case study on IEEE 13-bus distribution 3-phase networks and 123-node test feeder successfully verifies the performance of the proposed approach.