Energy system is undergoing remarkable changes due to many factors including increase use of renewables, environmental consideration and technological advancements. This demands for new tools and methods for its efficient and smooth operation. This work proposes distributed demand response application using Multi-Agent System (MAS) for improving voltage in distribution network at port city. Contract-Net-Protocol (CNP) based scheme was used for communication and coordination between agents. A co-simulation framework including power system simulator and agent environment was used to evaluate the proposed MAS based approach. A test network including variable and intermittent renewable generation sources (wind, pv), flexible loads (reefers), non-flexible loads was used to investigate the MAS based approach. Results show that MAS based approach is quite effective for demand response application.

@en

This paper presents novel separate methods for finding optimal locations, sizes of multiple distributed generators (DGs) simultaneously and operational power factor in order to minimize power loss and improve the voltage profile in the distribution system. A load concentration factor (LCF) is introduced to select the optimal location(s) for DG placement. Exact loss formula based analytical expressions are derived for calculating the optimal sizes of any number of DGs simultaneously. Since neither optimizing the location nor optimizing the size is done iteratively, like existing methods do, the simulation time is reduced considerably. The exhaustive method is used to find the operational power factor, and it is shown with the results that the losses are further reduced and voltage profile is improved by operating the DGs at operational power factor. Results for power loss reduction and voltage profile improvement in IEEE 37 and 119 node radial distribution systems are presented and compared with the the loss sensitivity factor (LSF) method, improved analytical (IA) and exhaustive load flow method (ELF). The comparison for operational power factor and other power factors is also presented.@en

With increasing photovoltaic (PV) penetration in low voltage networks (LVNs), voltage regulation is a challenge. Active power curtailment (APC) is one possible solution for mitigating over voltages resulting from active power injection in LVNs. There is an inherent unfairness in the APC scheme. When generation is high and consumption is low, the voltages at the end of the feeder tend to be the highest. This results in high curtailment of active power output of the inverters located at the end of the feeder and low or even no curtailment for the inverts located closer to the transformer. A secondary voltage controller has been implemented to mitigate this unfairness in APC based voltage support schemes. The focus of this work is to quantify this unfairness and develop methods that enable residential PV owners serviced by the same feeder to participate equally in voltage regulation in the LVN.@en

The increasing growth in power demand and the penetration of renewable distributed generations in competitive electricity market demands large and flexible capacity from the transmission grid to reduce transmission bottlenecks. The bottlenecks cause transmission congestion, reliability problems, restrict competition, and limit the maximum dispatch of low cost generations in the network. The electricity system requires efficient utilization of the current
transmission capability to improve the Available Transfer Capability (ATC). To improve the ATC, power flow among the lines can be managed by using Flexible AC Transmission System (FACTS) devices as power flow controllers, which alter the parameters of power lines. It is important to place FACTS devices on suitable lines to vary the reactance for improving Total Transmission Capacity
(TTC) of the network and provide flexibility in the power flow. In this paper a transmission network is analyzed based on line parameters variation to improve TTC of the interconnected system. Lines are selected for placing FACTS devices based on real power flow Performance Index (PI) sensitivity factors. TTC is computed using the Repeated Power Flow (RPF) method using the constraints of lines thermal limits, bus voltage limits and generator limits. The reactance of
suitable lines, selected on the basis of PI sensitivity factors are changed to divert the power flow to other lines with enough transfer capacity available. The improvement of TTC using line reactance variation is demonstrated with three IEEE test systems with multi-area networks. The results show the variation of the selected lines’ reactance in improving TTC for all the test networks with defined contingency cases.
@en

The potential of demand side as a frequency reserve proposes interesting opportunity in handling imbalances due to intermittent renewable energy sources. This paper proposes a novel approach for computing the parameters of a stochastic battery model representing the aggregation of Thermostatically Controlled Loads (TCLs). A hysteresis based non-disruptive control is used using priority stack algorithm to track the reference regulation signal. The parameters of admissible ramp-rate and the charge limits of the battery are dynamically calculated using the information from TCLs that is the status (on/off), availability and relative temperature distance till the switching boundary. The approach builds on and improves on the existing research work by providing a straight-forward mechanism for calculation of stochastic parameters of equivalent battery model. The effectiveness of proposed approach is demonstrated by a test case having a large number of residential TCLs tracking a scaled down real frequency regulation signal.@en

The rise in the intermittent power generation from renewables shall increase the secondary frequency reserve requirements in the future power system. Complimenting the support from the generators in providing frequency reserve, the active demand response can result in a cost effective contribution to this resource. Among demand response resources, the thermostatically controlled loads (TCLs) connected to the medium voltage networks poses an interesting potential. This work develops a co-simulation environment for the TCLs based demand side management scheme that can be used to assess the network impacts of using this service. An equivalent battery model with dynamic charging rate limits models the TCL aggregation and tracks a realistic frequency regulation signal. The co-simulation platform is tested for the IEEE 119 node distribution test feeder.@en

A method of reducing active power losses in distribution networks by simultaneous placement of optimally sized DGs is presented in this paper. Optimal DG sizes are calculated using analytical expressions in Python environment. IEEE 37 node test system, developed in DigSILENT PowerFactory, is used for the simulations. Three different use cases are presented in this work for validation and comparison. The active power loss reduction is compared with the base case (without any DGs). Different DG types, based on active and reactive power output, are considered during this work. The analytical expressions for simultaneous sizing proved their usefulness for loss minimization in radial networks. The complete study is done for the cases of three and four DGs placement in the system. To highlight the expanded capabilities of proposed method, it is applied to both the static and time varying load conditions.@en

The ongoing transformation of the traditional power system into a more intelligent Smart Grid has many benefits. However, it also brings numerous challenges. The system is becoming more complex, making the existing domain specific tools less relevant. This paper presents a flexible co-simulation framework that supports multiple simulators, including multiagent platform, for a detailed evaluation of the impact and inter-dependencies between the cyber and physical components of the system. Two case studies have been evaluated with different Smart Grid applications, modeled and simulated with different simulators and coupled into the developed co-simulation framework. The results show the flexibility and useability of the proposed co-simulation framework.@en

Integration of distributed generation in power system challenges operation and management of power distribution network. This paper presents Modified Bat Algorithm for Optimal Reactive Power Dispatch (OPRF) of distributed generation for voltage support in distribution network. An objective function with constraints of voltage, DG reactive power, thermal limits of lines is presented. A modified IEEE 37 node test feeder with variable generation was used to validate the proposed algorithm. A co-simulation setup was used in which electric grid was developed in Power system tool (DigSILENT PowerFactory) and Modified Bat Algorithm was developed in Python. Results showed that Modified Bat Algorithm is quite effective for voltage profile improvement and loss minimization.@en