23,377 research outputs found
Stochastic approach for active and reactive power management in distribution networks
YesIn this paper, a stochastic method is proposed to assess the amount of active and reactive power that can be injected/absorbed to/from grid within a distribution market environment. Also, the impact of wind power penetration on the reactive and active distribution-locational marginal prices is investigated. Market-based active and reactive optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand. The uncertainties are modeled by Scenario-based approach. The proposed model is examined with 16-bus UK generic distribution system.Supported by the Higher Education Ministry of Iraqi government
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Distribution Network Operation with High Penetration of Renewable Energy Sources. Joint Active/Reactive Power Procurement: A Market-Based Approach for Operation of Distribution Network
Distributed generators (DGs) are proposed as a possible solution to supply
economic and reliable electricity to customers. It is adapted to overcome the
challenges that are characterized by centralized generation such as
transmission and distribution losses, high cost of fossil fuels and environmental
damage. This work presents the basic principles of integrating renewable DGs
in low voltage distribution networks and particularly focuses on the operation
of DG installations and their impacts on active and reactive power.
In this thesis, a novel technique that applies the stochastic approach for the
operation of distribution networks with considering active network
management (ANM) schemes and demand response (DR) within a joint active
and reactive distribution market environment is proposed. The projected model
is maximized based on social welfare (SW) using market-based joint active
and reactive optimal power flow (OPF). The intermittent behaviour of
renewable sources (such as solar irradiance and wind speed) and the load
demands are modelled through Scenario-Tree technique. The distributed
network frame is recast using mixed-integer linear programming (MILP) that is
solved by using the GAMS software and then the obtained results are being
analysed and discussed. In addition, the impact of wind and solar power
penetration on the active and reactive distribution locational prices (D-LMPs)
within the distribution market environment is explored in terms of the
maximization of SW considering the uncertainty related to solar irradiance,
wind speed and load demands. Finally, a realistic case study (16-bus UK
generic medium voltage distribution system) is used to demonstrate the
effectiveness of the proposed method. Results show that ANM schemes and
DR integration lead to an increase in the social welfare and total dispatched
active and reactive power and consequently decrease in active and reactive
D-LMPs.Ministry of Higher Education and Scientific Research - IraqThe selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright
Active network management for electrical distribution systems: problem formulation, benchmark, and approximate solution
With the increasing share of renewable and distributed generation in
electrical distribution systems, Active Network Management (ANM) becomes a
valuable option for a distribution system operator to operate his system in a
secure and cost-effective way without relying solely on network reinforcement.
ANM strategies are short-term policies that control the power injected by
generators and/or taken off by loads in order to avoid congestion or voltage
issues. Advanced ANM strategies imply that the system operator has to solve
large-scale optimal sequential decision-making problems under uncertainty. For
example, decisions taken at a given moment constrain the future decisions that
can be taken and uncertainty must be explicitly accounted for because neither
demand nor generation can be accurately forecasted. We first formulate the ANM
problem, which in addition to be sequential and uncertain, has a nonlinear
nature stemming from the power flow equations and a discrete nature arising
from the activation of power modulation signals. This ANM problem is then cast
as a stochastic mixed-integer nonlinear program, as well as second-order cone
and linear counterparts, for which we provide quantitative results using state
of the art solvers and perform a sensitivity analysis over the size of the
system, the amount of available flexibility, and the number of scenarios
considered in the deterministic equivalent of the stochastic program. To foster
further research on this problem, we make available at
http://www.montefiore.ulg.ac.be/~anm/ three test beds based on distribution
networks of 5, 33, and 77 buses. These test beds contain a simulator of the
distribution system, with stochastic models for the generation and consumption
devices, and callbacks to implement and test various ANM strategies
Stochastic optimisation-based valuation of smart grid options under firm DG contracts
Under the current EU legislation, Distribution Network Operators (DNOs) are expected to provide firm connections to new DG, whose penetration is set to increase worldwide creating the need for significant investments to enhance network capacity. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to accurately determine in advance where network violations may occur. Hence, conventional network reinforcements run the risk of asset stranding, leading to increased integration costs. A novel stochastic planning model is proposed that includes generalized formulations for investment in conventional and smart grid assets such as Demand-Side Response (DSR), Coordinated Voltage Control (CVC) and Soft Open Point (SOP) allowing the quantification of their option value. We also show that deterministic planning approaches may underestimate or completely ignore smart technologies
Optimizing Service Restoration in Distribution Systems with Uncertain Repair Time and Demand
This paper proposes a novel method to co-optimize distribution system
operation and repair crew routing for outage restoration after extreme weather
events. A two-stage stochastic mixed integer linear program is developed. The
first stage is to dispatch the repair crews to the damaged components. The
second stage is distribution system restoration using distributed generators,
and reconfiguration. We consider demand uncertainty in terms of a truncated
normal forecast error distribution, and model the uncertainty of the repair
time using a lognormal distribution. A new decomposition approach, combined
with the Progressive Hedging algorithm, is developed for solving large-scale
outage management problems in an effective and timely manner. The proposed
method is validated on modified IEEE 34- and 8500-bus distribution test
systems.Comment: Under review in IEEE Transactions on Power System
Review of trends and targets of complex systems for power system optimization
Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107
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