The Experts below are selected from a list of 2946 Experts worldwide ranked by ideXlab platform

Dipti Srinivasan - One of the best experts on this subject based on the ideXlab platform.

  • distributed model predictive real time optimal operation of a network of Smart Microgrids
    IEEE Transactions on Smart Grid, 2019
    Co-Authors: Kumar Utkarsh, Dipti Srinivasan, Anupam Trivedi, Wenjie Zhang, Thomas Reindl
    Abstract:

    In this paper, we study multiple interconnected Smart Microgrids, and develop an efficient strategy for their internal device scheduling and energy trading. This paper achieves the following objectives. First, each microgrid holistically manages its internal devices, such as local storage systems and reactive power compensation levels, and external active/reactive energy trading (with the external grid and other Microgrids) simultaneously for real-time optimization. Scenarios of social cooperation and game in interconnected Microgrids are formulated as distinct objectives of the Microgrids, which aim to optimize their own performance and gain benefits through energy trading. Second, Microgrids of different network topologies (radial and meshed) and nominal voltages are fully incorporated. Third, a fully distributed model-predictive and computational-intelligence-based algorithm is proposed, so that Microgrids’ devices operate autonomously with minimum communication exchange, obviating the need for a central controller. Convergence properties of the proposed distributed algorithm are analyzed and benchmarked with a state-of-the-art distributed algorithm, and numerical simulations for different scenarios are performed demonstrating that the proposed distributed strategy can be feasibly applied to real-world Microgrids.

  • Multiagent-based transactive energy framework for distribution systems with Smart Microgrids
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Dipti Srinivasan
    Abstract:

    The increasing population of Microgrids with various kinds of plug and play energy resources and rapidly varying demand in distribution systems are multiplying the complexity involved in overall system management. This paper proposes an agent-based transactive energy management framework with a comprehensive energy management system (CEMS) as a solution to address the aggregated complexity induced by Microgrids in distribution systems. In this framework, Microgrids sell or buy the energy in transactive market, which is an inter-microgrid auction based electricity market, to manage the excess supply or residual demand. CEMS follows a dual phase energy management strategy. In the first stage local auxiliary resources such as demand response and distributed energy storage systems of the Microgrids are optimally integrated into system operation to level off the forecasted energy imbalances in Microgrids. In the latter stage, the operating configuration of the local auxiliary resources is adjusted in real time along with transactive energy to address the imbalances leftover in the former phase and the forecast errors. The efficacy of the proposed framework and CEMS is verified on a IEEE distribution test feeder system with Microgrids.

  • multi agent based demand response management system for combined operation of Smart Microgrids
    Sustainable Energy Grids and Networks, 2016
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Suryanarayana Doolla, Amit Mohan Saklani, Anudeep Sesetti, Swathi Battula, Dipti Srinivasan
    Abstract:

    Abstract This paper presents an agent based market model for combined operation of the grid connected Smart Microgrids with price sensitive consumers by executing demand side management strategies. This model maintains a non-discriminative market environment among the consumers and generators of the Microgrids connected across the distribution system. The novelty of this agent model is in two fold. First, a novel incentive mechanism called priority banking is proposed to encourage the consumers by giving them a share in locally available generation. This mechanism also monitors how often the consumers are utilizing the incentives and thereby updates their priority. Second, after executing the contracts obtained from the market, the loss contribution of each trade to the overall network loss is calculated using a novel network loss allocation method. The applicability and effectiveness of the proposed agent based market model are exemplified using an IEEE 37 bus distribution feeder network with two grid connected Smart Microgrids simulated in Open DSS and the proposed multi-agent system is built on JADE framework.

  • A multi-agent system for energy management in Smart Microgrids with distributed energy storage and demand response
    2016 IEEE International Conference on Power Electronics Drives and Energy Systems (PEDES), 2016
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Dipti Srinivasan
    Abstract:

    This paper proposes a multi-agent system based microgrid energy management framework to balance the energy supply and demand by feasibly integrating the distributed energy storage and demand response (DR). The main contribution of this paper is an energy management system which schedules the operation of distributed energy storage systems (DESSs) and DR loads based on the day-ahead forecast data to minimise the energy mismatches in the system by taking the preferences set by the owners and life depletion costs of DESSs. The target schedule prepared based on the forecast information is adjusted in real-time to compromise the uncertainties and forecast errors. Besides scheduling the energy resources, the proposed management systems organises an energy spot market to settle the energy demand and supply quotes of end-users and distributed generators (DGs). The developed multi-agent systems is applied to a microgrid case study to verify its performance. The simulation results and their analysis suggest that the proposed microgrid energy management system is effective in managing the energy under uncertainties.

Tao Jiang - One of the best experts on this subject based on the ideXlab platform.

  • Real-Time Energy Management for Cloud Data Centers in Smart Microgrids
    IEEE Access, 2016
    Co-Authors: Liang Yu, Tao Jiang
    Abstract:

    Cloud service providers are typically faced with three significant problems when running their cloud data centers, i.e., rising electricity bills, growing carbon footprints, and unexpected power outages. To mitigate these issues, running cloud data centers in Smart Microgrids (SMGs) is a good choice, since SMGs can enhance the energy efficiency, sustainability, and reliability of electrical services. Thus, in this paper, we investigate the problem of energy management for cloud data centers in SMGs. To be specific, we would minimize the time average expected energy cost (including electricity bill, battery depreciation cost, the total generation cost of conventional generators, and revenue loss due to the unfinished workloads) with the consideration of three practical factors, i.e., the ramping constraints of backup generators, the charging and discharging efficiency parameters of batteries, and two kinds of data center workloads. A stochastic programming is formulated by integrating the constraints associated with workload allocation, electricity buying/selling, battery management, backup generators, and power balancing. To solve the stochastic programming problem, an online algorithm is designed, and the algorithmic performance is analyzed. Simulation results show the advantages of the designed algorithm over other baselines.

  • energy cost minimization for distributed internet data centers in Smart Microgrids considering power outages
    IEEE Transactions on Parallel and Distributed Systems, 2015
    Co-Authors: Tao Jiang, Yang Cao
    Abstract:

    In this paper, we investigate the problem of minimizing energy cost for distributed Internet data centers (IDCs) in Smart Microgrids while taking system dynamics into consideration. Specifically, IDC operators expect to minimize the long-term energy cost with the uncertainties in electricity price, workload, renewable energy generation, and power outage state. At first, we formulate the problem as a stochastic program that captures service request distribution, server provisioning, energy storage management, generator scheduling, power transactions between Smart Microgrids, and main grids. Second, we use the Lyapunov optimization technique to design an operation algorithm, which enables an explicit tradeoff between energy cost saving and battery investment cost. Finally, the effectiveness of the proposed algorithm is evaluated with practical data.

  • Carbon-Aware Energy Cost Minimization for Distributed Internet Data Centers in Smart Microgrids
    IEEE Internet of Things Journal, 2014
    Co-Authors: Liang Yu, Tao Jiang, Qi Qi
    Abstract:

    In this paper, we investigate the problem of minimizing carbon-aware energy cost for distributed Internet data centers (IDCs) in Smart Microgrids. Specifically, a socially responsible IDC operator intends to jointly minimize the long-term energy cost and carbon emission in IDC operations. Since the future system parameters (e.g., electricity price, workload, renewable energy generation, and carbon emission rate) are random, we formulate the above-mentioned problem as a stochastic program to minimize the time-averaged expectation of the weighted summation of energy cost and carbon emission with guaranteed quality of service for service requests. Then, we design an operation algorithm to solve the formulated problem based on Lyapunov optimization technique without requiring any knowledge about system statistics. Finally, evaluations based on real-life data show that the proposed operation algorithm can achieve lower energy cost and carbon emission simultaneously compared with the carbon-oblivious algorithm.

Paolo Mattavelli - One of the best experts on this subject based on the ideXlab platform.

  • distribution loss minimization by token ring control of power electronic interfaces in residential Microgrids
    IEEE Transactions on Industrial Electronics, 2012
    Co-Authors: Paolo Tenti, Paolo Mattavelli, Alessandro Costabeber, Daniela Trombetti
    Abstract:

    Smart Microgrids offer a new application domain for power electronics. In fact, every distributed energy resource includes an electronic power processor (EPP) to control the power exchange with the grid. If such distributed EPPs perform cooperatively, all the available energy sources and energy storage units can be fully exploited, resulting in reduced power consumption from the utility, high power quality, and increased hosting capability by the utility. This paper shows that, even in low-voltage meshed Microgrids, where the electrical distribution pattern is complex and sources and loads may vary during daytime, such cooperative operation can be achieved by a proper selection of the local control algorithms and by allowing narrow-band communication capability among neighbor EPPs. In particular, this paper describes a token ring control approach which allows full exploitation of the microgrid capabilities with marginal investment in the information and communication technology infrastructure.

  • accountability in Smart Microgrids based on conservative power theory
    IEEE Transactions on Instrumentation and Measurement, 2011
    Co-Authors: Paolo Tenti, Helmo Kelis Morales Paredes, Fernando Pinhabel Marafao, Paolo Mattavelli
    Abstract:

    Smart Microgrids offer a new challenging domain for power theories and metering techniques because they include a variety of intermittent power sources which positively impact on power flow and distribution losses but may cause voltage asymmetry and frequency variation. In Smart Microgrids, the voltage distortion and asymmetry in presence of poly-phase nonlinear loads can be also greater than in usual distribution lines fed by the utility, thus affecting measurement accuracy and possibly causing tripping of protections. In such a context, a reconsideration of power theories is required since they form the basis for supply and load characterization. A revision of revenue metering techniques is also suggested to ensure a correct penalization of the loads for their responsibility in generating reactive power, voltage asymmetry, and distortion. This paper shows that the conservative power theory provides a suitable background to cope with Smart grids characterization and metering needs. Simulation and experimental results show the properties of the proposed approach.

  • conservative power theory a framework to approach control and accountability issues in Smart Microgrids
    IEEE Transactions on Power Electronics, 2011
    Co-Authors: Paolo Tenti, Helmo Kelis Morales Paredes, Paolo Mattavelli
    Abstract:

    Smart Microgrids offer a new challenging domain for power theories and compensation techniques, because they include a variety of intermittent power sources, which can have dynamic impact on power flow, voltage regulation, and distribution losses. When operating in the islanded mode, low-voltage Smart Microgrids can also exhibit considerable variation of amplitude and frequency of the voltage supplied to the loads, thus affecting power quality and network stability. Due to limited power capability in Smart Microgrids, the voltage distortion can also get worse, affecting measurement accuracy, and possibly causing tripping of protections. In such context, a reconsideration of power theories is required, since they form the basis for supply and load characterization, and accountability. A revision of control techniques for harmonic and reactive compensators is also required, because they operate in a strongly interconnected environment and must perform cooperatively to face system dynamics, ensure power quality, and limit distribution losses. This paper shows that the conservative power theory provides a suitable background to cope with Smart Microgrids characterization needs, and a platform for the development of cooperative control techniques for distributed switching power processors and static reactive compensators.

Sandro Zampieri - One of the best experts on this subject based on the ideXlab platform.

  • a distributed control strategy for reactive power compensation in Smart Microgrids
    IEEE Transactions on Automatic Control, 2013
    Co-Authors: Saverio Bolognani, Sandro Zampieri
    Abstract:

    We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a Smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to a microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, leader-less, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance is achieved when we command cooperation among microgenerators that are neighbors in the electric topology. Numerical simulations are included to validate both the proposed model and the analytic results about the performance of the proposed algorithm.

  • distributed control for optimal reactive power compensation in Smart Microgrids
    Conference on Decision and Control, 2011
    Co-Authors: Saverio Bolognani, Sandro Zampieri
    Abstract:

    We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a Smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We also show how agents have a partial knowledge of the problem parameters and state via some local measurements. Then, we design a randomized, gossip-like optimization algorithm, providing conditions for convergence together with an analytical characterization of the convergence speed. The analysis shows that the best performance is achieved when we command cooperation among agents that are neighbors in the Smart microgrid topology.

  • distributed control for optimal reactive power compensation in Smart Microgrids
    2011
    Co-Authors: Saverio Bolognani, Sandro Zampieri
    Abstract:

    We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a Smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to the microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance can be achieved when we command cooperation among units that are neighbors in the electric topology. Numerical simulations are included to validate the proposed model and to confirm the analytic results about the performance of the proposed algorithm.

  • a distributed control strategy for reactive power compensation in Smart Microgrids
    arXiv: Optimization and Control, 2011
    Co-Authors: Saverio Bolognani, Sandro Zampieri
    Abstract:

    We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a Smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to the microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance can be achieved when we command cooperation among units that are neighbors in the electric topology. Numerical simulations are included to validate the proposed model and to confirm the analytic results about the performance of the proposed algorithm.

H. S. V. Sivanand Kumar Nunna - One of the best experts on this subject based on the ideXlab platform.

  • Multiagent-based transactive energy framework for distribution systems with Smart Microgrids
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Dipti Srinivasan
    Abstract:

    The increasing population of Microgrids with various kinds of plug and play energy resources and rapidly varying demand in distribution systems are multiplying the complexity involved in overall system management. This paper proposes an agent-based transactive energy management framework with a comprehensive energy management system (CEMS) as a solution to address the aggregated complexity induced by Microgrids in distribution systems. In this framework, Microgrids sell or buy the energy in transactive market, which is an inter-microgrid auction based electricity market, to manage the excess supply or residual demand. CEMS follows a dual phase energy management strategy. In the first stage local auxiliary resources such as demand response and distributed energy storage systems of the Microgrids are optimally integrated into system operation to level off the forecasted energy imbalances in Microgrids. In the latter stage, the operating configuration of the local auxiliary resources is adjusted in real time along with transactive energy to address the imbalances leftover in the former phase and the forecast errors. The efficacy of the proposed framework and CEMS is verified on a IEEE distribution test feeder system with Microgrids.

  • multi agent based demand response management system for combined operation of Smart Microgrids
    Sustainable Energy Grids and Networks, 2016
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Suryanarayana Doolla, Amit Mohan Saklani, Anudeep Sesetti, Swathi Battula, Dipti Srinivasan
    Abstract:

    Abstract This paper presents an agent based market model for combined operation of the grid connected Smart Microgrids with price sensitive consumers by executing demand side management strategies. This model maintains a non-discriminative market environment among the consumers and generators of the Microgrids connected across the distribution system. The novelty of this agent model is in two fold. First, a novel incentive mechanism called priority banking is proposed to encourage the consumers by giving them a share in locally available generation. This mechanism also monitors how often the consumers are utilizing the incentives and thereby updates their priority. Second, after executing the contracts obtained from the market, the loss contribution of each trade to the overall network loss is calculated using a novel network loss allocation method. The applicability and effectiveness of the proposed agent based market model are exemplified using an IEEE 37 bus distribution feeder network with two grid connected Smart Microgrids simulated in Open DSS and the proposed multi-agent system is built on JADE framework.

  • A multi-agent system for energy management in Smart Microgrids with distributed energy storage and demand response
    2016 IEEE International Conference on Power Electronics Drives and Energy Systems (PEDES), 2016
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Dipti Srinivasan
    Abstract:

    This paper proposes a multi-agent system based microgrid energy management framework to balance the energy supply and demand by feasibly integrating the distributed energy storage and demand response (DR). The main contribution of this paper is an energy management system which schedules the operation of distributed energy storage systems (DESSs) and DR loads based on the day-ahead forecast data to minimise the energy mismatches in the system by taking the preferences set by the owners and life depletion costs of DESSs. The target schedule prepared based on the forecast information is adjusted in real-time to compromise the uncertainties and forecast errors. Besides scheduling the energy resources, the proposed management systems organises an energy spot market to settle the energy demand and supply quotes of end-users and distributed generators (DGs). The developed multi-agent systems is applied to a microgrid case study to verify its performance. The simulation results and their analysis suggest that the proposed microgrid energy management system is effective in managing the energy under uncertainties.

  • Demand response in Smart Microgrids
    2011 IEEE PES International Conference on Innovative Smart Grid Technologies-India ISGT India 2011, 2011
    Co-Authors: H. S. V. Sivanand Kumar Nunna, Suryanarayana Doolla
    Abstract:

    The mismatch between supply and demand in Microgrids can be overcome by effectively utilizing distributed energy resources and/or encouraging demand side management. Demand response is one of the popular techniques to demand side management. In this paper an agent based architecture to simulate virtual markets enabling customers of the market to participate in demand response and trade power using intelligent trading strategy which makes the market more realistic and Microgrids Smarter is proposed. The proposed concept is verified on a system with two Microgrids. The proposed MAS is developed using Java Application Development (JADE) framework.