Jignesh Solanki

A Multi-Agent Solution to Distribution Systems Restoration

The goal to provide faster and faster restoration after a fault is pushing the technical envelope related to new algorithms. While many approaches use centralized strategies, the concept of multi-agent systems (MAS) is creating a new option related to distributed analyses for restoration. This paper provides details on a MAS that restores a power system after a fault. The development of agents and behaviors of the agents are described, including communication of agents. The MAS is tested on two test systems and facilitates both full and partial restoration, including load prioritization and shedding.

Development of Three-Phase Unbalanced Power Flow Using PV and PQ Models for Distributed Generation and Study of the Impact of DG Models

With the increased installations of distributed generators (DGs) within power systems, load flow analysis of distribution systems needs special models and algorithms to handle multiple sources. In this paper, the development of an unbalanced three-phase load flow algorithm that can handle multiple sources is described. This software is capable of switching the DG mode of operation from constant voltage to constant power factor. The algorithm to achieve this in the presence of multiple DGs is proposed. Shipboard power systems (SPS) have other special characteristics apart from multiple sources, which make the load flow difficult to converge. The developed software is verified for a distribution system without DG using the Radial Distribution Analysis Package (RDAP). The developed software analyzes an IEEE test case and an icebreaker ship system. System studies for the IEEE 37-node feeder without the regulator show the effect of different models and varying DG penetration related to the increase in loading. System losses and voltage deviations are compared.

Optimized Restoration of Unbalanced Distribution Systems

A novel formulation for service restoration algorithm for unbalanced three phase distribution systems is described. This problem is a constrained multiobjective optimization formulated as a mixed integer non-linear programming problem. A comparison of the solutions with and without switch pairs has been made. The formulation was first validated using already developed three-phase unbalanced power flow software. The three-phase unbalanced power flow equations were embedded in the formulation, and hence separate calculations were not needed. Simulation results are presented for modified IEEE 13-node and IEEE 37-node test cases

Coordinated Predictive Control of a Wind/Battery Microgrid System

This paper presents the operation and controller design of a microgrid consisting of a direct drive wind generator and a battery storage system. A model predictive control strategy for the ac-dc-ac converter of wind system is derived and implemented to capture the maximum wind energy as well as provide desired reactive power. A novel supervisory controller is presented and employed to coordinate the operation of wind farm and battery system in the microgrid for grid-connected and islanded operations. The proposed coordinated controller can mitigate both active and reactive power disturbances that are caused by the intermittency of wind speed and load change. Moreover, the control strategy ensures the maximum power extraction capability of wind turbine while regulating the point of common coupling bus voltage within acceptable range in both grid-connected and islanded operations. The designed concept is verified through various simulation studies in EMTDC/PSCAD, and the results are presented and discussed.

Using intelligent multi-agent systems for shipboard power systems reconfiguration

Many approaches have been taken on the reconfiguration of power systems, but most of these approaches use a centralized method. While these methods can be acceptable for terrestrial power system applications, doing reconfiguration on shipboard power systems has a different set of issues involved. For naval ships, that may experience damage during battle, a centralized reconfiguration method provides a limitation. Based on these constraints researchers are investigating decentralized control strategies that allow for reconfiguration using localized information. One newer technology that is showing promise in this area is intelligent multi-agent (IMA) systems. This paper discusses efforts underway at Mississippi State University to use IMA systems for reconfiguration of the power system. Agents are being implemented in multiple formats including Matlab and JADE to investigate the issues related to data sharing, communications and reconfiguration strategies

Demand response using multi-agent system

Smart grid has been a significant development trend of power system. Within smart grid, microgrids share the burden of traditional grids and reduce energy consumption cost. In a microgrid, consumers are the integral part with varying demand throughout a day. Furthermore, the penetration of Plug-in-Hybrid Vehicles (PHEVs) is overloading the existing residential network and calls for dynamic strategy. This paper proposes a dynamic Demand Response (DR) approach in the context of isolated smart microgrid for a residential community. A multi-agent system is proposed for optimizing the demand response by updating the grid generation resources and controlling the customer load. The multi-agent system can switch customer load and controls the charging of PHEVs depending on their Battery State of Charge (BSOC) to reduce cost and avoid overload during peak hours. Simulation and numerical results show the effectiveness of using multi-agent system on reducing the energy consumption cost of the residential customers and also allowing electric vehicles charging during the peak hours.

Demand response model and its effects on voltage profile of a distribution system

This paper develops a model for Demand Response (DR) by utilizing consumer behavior modeling considering different scenarios and levels of consumer rationality. Consumer behavior modeling has been done by developing extensive demand-price elasticity matrices for different types of consumers. These Price Elasticity Matrices (PEMs) are utilized to calculate the level of demand response for a given consumer. DR thus obtained is applied to a real world distribution network considering a day-ahead real time pricing scenario to study the effects of demand reduction on system voltage. Results show considerable boost in system voltage that paves way for further demand curtailment through demand side management techniques like Volt/Var Control (VVC).

Market optimization for microgrid with Demand Response model

This paper develops a market optimization model for a microgrid with Demand Side Bidding (DSB) and Demand Response (DR) by residential consumers. Demand Response (DR) models have been developed by utilizing consumer behavior modeling by Price Elasticity Matrices (PEMs) considering different scenarios and levels of consumer rationality. These PEMs are utilized to calculate the levels of demand response for different consumer types and utilized in the bidding mechanism for the double sided microgrid market. The proposed method is tested for different scenarios on a microgrid system with Independent Power Producers (IPPs) and Load Serving Entities (LSEs) for optimized generation and demand response levels so as to minimize cost.

Steady state analysis of high penetration PV on utility distribution feeder

The current deregulation trend in the electric power industry has led to the utilities trying to adapt Distributed Generation (DG) into their existing infrastructure. In this paper, 12.47 kV distribution feeders of American Electric Power (AEP) are modeled in OpenDSS to investigate the impacts of PV integration. With increasing PV penetration reverse power may flow on the grid which is associated with voltage rise that may lead to violation of integration standards. The impact on voltage profiles and losses depends upon the size and location of the PV system. Voltages of the feeder, voltage regulation and feeder losses under various locations and levels of PV penetration are analyzed for the utility feeder utilizing unbalanced power flow solution.

Multi-agent-based reconfiguration for restoration of distribution systems with distributed generators

Restoration involves supplying the loads that lose power in the process of fault isolation. This process entails the development of a plan consisting of opening or closing of switches, the process called reconfiguration. Existing methods, based on centralized restoration schemes, which require a powerful central computer, may lead to a single point of failure. This paper proposes a decentralized scheme based on agents. The large-scale introduction of Distributed Generation (DG) in distribution systems has made it increasingly necessary to develop restoration schemes that consider DG. When a portion of the system isolated from the utility is fed by DGs, an island occurs. Load shedding may be the only option to maintain the island when conditions are so severe they require correction by restoration schemes. In this paper, a fast and efficient service restoration with load shedding method has been designed for land-based and ship systems, considering priority of customers. The load-shedding algorithm with the service restoration algorithm performs load shedding and restores the loads for systems with and without DG.