The Experts below are selected from a list of 2406 Experts worldwide ranked by ideXlab platform

Pierluigi Siano - One of the best experts on this subject based on the ideXlab platform.

  • incorporating price responsive customers in day ahead scheduling of smart Distribution Networks
    Energy Conversion and Management, 2016
    Co-Authors: Mohammadreza Mazidi, Hassan Monsef, Pierluigi Siano
    Abstract:

    Abstract Demand response and real-time pricing of electricity are key factors in a smart grid as they can increase economic efficiency and technical performances of power grids. This paper focuses on incorporating price-responsive customers in day-ahead scheduling of smart Distribution Networks under a dynamic pricing environment. A novel method is proposed and formulated as a tractable mixed integer linear programming optimization problem whose objective is to find hourly sale prices offered to customers, transactions (purchase/sale) with the wholesale market, commitment of Distribution generation units, dispatch of battery energy storage systems and planning of interruptible loads in a way that the profit of the Distribution Network Operator is maximized while customers’ benefit is guaranteed. To hedge Distribution Network Operator against financial risk arising from uncertainty of wholesale market prices, a risk management model based on a bi-level information-gap decision theory is proposed. The proposed bi-level problem is solved by recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. Performance of the proposed model is verified by applying it to a modified version of the IEEE 33-bus Distribution test Network. Numerical results demonstrate the effectiveness and efficiency of the proposed method.

  • optimal dr and ess scheduling for Distribution losses payments minimization under electricity price uncertainty
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Alireza Soroudi, Pierluigi Siano, Andrew Keane
    Abstract:

    The Distribution Network Operator is usually responsible for increasing the efficiency and reliability of Network operation. The target of active loss minimization is in line with efficiency improvement. However, this approach may not be the best way to decrease the losses payments in an unbundled market environment. This paper investigates the differences between loss minimization and loss payment minimization strategies. It proposes an effective approach for decreasing the losses payment considering the uncertainties of electricity prices in a day ahead energy market using energy storage systems and demand response. In order to quantify the benefits of the proposed method, the evaluation of the proposed technique is carried out by applying it on a 33-bus Distribution Network.

  • A Model for Wind Turbines Placement Within a Distribution Network Acquisition Market
    IEEE Transactions on Industrial Informatics, 2015
    Co-Authors: Pietro Lamaina, Pierluigi Siano, Debora Sarno, Alireza Zakariazadeh, Roberto Romano
    Abstract:

    This paper proposes an innovative exhaustive search method for the optimal placement of wind turbines (WTs) in electrical Distribution systems taking into account wind speed and load demand uncertainty, and the variability of electrical energy prices within a Distribution Network Operator (DNO) acquisition market environment. The method combines Monte Carlo simulation (MCS) and market-based optimal power flow (OPF) to maximize the net present value (NPV) related to the investment made by WTs' developers over a planning horizon. In particular, the MCS data feed the market-based OPF problem with inter-temporal constraints in order to find the most convenient WTs allocation and priority on the Network, based on Distribution-locational marginal prices (D-LMPs) in a competitive electricity market. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4-kV radial Distribution system.

  • Strategic placement of Distribution Network Operator owned wind turbines by using market-based optimal power flow
    IET Generation Transmission & Distribution, 2014
    Co-Authors: Geev Mokryani, Pierluigi Siano
    Abstract:

    In this study, a new methodology to optimally allocate wind turbines (WTs) in Distribution Networks is proposed. A market-based optimal power flow is used to determine the optimal numbers and capacities of WTs in a way that maximises the social welfare. The method is conceived for Distribution Network Operators to strategically allocate WTs in Distribution Networks. The proposed method by yielding location-specific WTs capacity settlement both in terms of cost reduction and consumers' benefits is consistent with Distribution Network topology and constraints. The method is solved by using step-controlled primal dual interior point method considering Network constraints. The effectiveness of the proposed method is demonstrated with two radial Distribution systems including an 84-bus 11.4 kV and a 69-bus 11 kV Network.

Tsuyoshi Funaki - One of the best experts on this subject based on the ideXlab platform.

  • economic and efficient voltage management using customer owned energy storage systems in a Distribution Network with high penetration of photovoltaic systems
    IEEE Transactions on Power Systems, 2013
    Co-Authors: Hideharu Sugihara, K Yokoyama, Osamu Saeki, Kiichiro Tsuji, Tsuyoshi Funaki
    Abstract:

    The widespread installation of distributed generation systems is crucial for making optimal use of renewable energy. However, local Distribution Networks face voltage fluctuation problems if numerous photovoltaic (PV) systems are connected. Recently, energy storage systems that can be installed at commercial customers have been developed. This paper proposes a concept that solves the voltage fluctuation problem in Distribution Networks with high penetration of PV systems by using customer-side energy storage systems. The Distribution Network Operator (DNO) is allowed to control the output of the energy storage systems of customers during a specific time period in exchange for a subsidy covering a portion of the initial cost of the storage system. The cost effectiveness of the cooperative operation for both customer and DNO is discussed by numerical simulations based on minute-by-minute solar irradiation data. Our results have clarified the possibilities of making voltage management more economical in Distribution Networks.

Roberto Romano - One of the best experts on this subject based on the ideXlab platform.

  • A Model for Wind Turbines Placement Within a Distribution Network Acquisition Market
    IEEE Transactions on Industrial Informatics, 2015
    Co-Authors: Pietro Lamaina, Pierluigi Siano, Debora Sarno, Alireza Zakariazadeh, Roberto Romano
    Abstract:

    This paper proposes an innovative exhaustive search method for the optimal placement of wind turbines (WTs) in electrical Distribution systems taking into account wind speed and load demand uncertainty, and the variability of electrical energy prices within a Distribution Network Operator (DNO) acquisition market environment. The method combines Monte Carlo simulation (MCS) and market-based optimal power flow (OPF) to maximize the net present value (NPV) related to the investment made by WTs' developers over a planning horizon. In particular, the MCS data feed the market-based OPF problem with inter-temporal constraints in order to find the most convenient WTs allocation and priority on the Network, based on Distribution-locational marginal prices (D-LMPs) in a competitive electricity market. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4-kV radial Distribution system.

Mohammad E. Khodayar - One of the best experts on this subject based on the ideXlab platform.

  • A Hierarchical Electricity Market Structure for the Smart Grid Paradigm
    IEEE Transactions on Smart Grid, 2016
    Co-Authors: Saeed D. Manshadi, Mohammad E. Khodayar
    Abstract:

    This paper proposed a hierarchical structure for the electricity market to facilitate the coordination of energy markets in Distribution and transmission Networks. The proposed market structure enables the integration of microgrids, which provide energy and ancillary services in Distribution Networks. In the proposed hierarchical structure, microgrids participate in the energy market at the Distribution Networks settled by the Distribution Network Operator (DNO), and load aggregators (LAs) interact with microgrids and generation companies (GENCOs) to import/export energy to/from the Distribution Network electricity markets from/to the wholesale electricity market. The proposed approach addressed the synergy of energy markets by introducing dynamic game with complete information for GENCOs, microgrids, and LAs. The proposed hierarchical competition is composed of bi-level optimization problems in which the respective upper-level problems maximize the individual market participants’ payoff, and the lower-level problems represent the market settlement accomplished by the DNO or the independent system Operator. The bi-level problems are solved by developing sensitivity functions for market participants’ payoff with respect to their bidding strategies. A case study is employed to illustrate the effectiveness of the proposed approach.

Qiang Yang - One of the best experts on this subject based on the ideXlab platform.

  • Coordinated Investment Planning of Distributed Multi-Type Stochastic Generation and Battery Storage in Active Distribution Networks
    IEEE Transactions on Sustainable Energy, 2019
    Co-Authors: Ali Ehsan, Qiang Yang
    Abstract:

    This paper presents a scenario-based stochastic active Distribution Network planning (ADNP) model considering the multi-type distributed generation and battery energy storage (BES). The proposed solution aims to identify the optimal mix, siting, and sizing of wind turbine (WT), photovoltaic (PV), and BES units to maximize the net present value of Distribution Network Operator (DNO) while fully exploiting the BES arbitrage benefit. First, a heuristic moment matching based uncertainty matrix comprising of representative scenarios is generated to effectively capture the stochastic characteristics and correlation among historical WT generation, PV generation, and load demand. Then, the uncertainty matrix is incorporated to formulate the stochastic ADNP problem. The proposed solution minimizes the costs and maximizes the revenues of the DNO. The effectiveness and scalability of the proposed model are evaluated through case studies in the 53-bus and IEEE 123-bus Distribution systems. Finally, the performance of the proposed model is compared against the deterministic planning model, and a sensitivity analysis is performed to assess the impact of various planning factors on the proposed solution.