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Dynamic network pricing based on Smart reference networks
Abstract
Network pricing is a complex issue, considering the network size and other facets. For distribution networks, reference network aids in quick decision making, for network operation and pricing. There is a sustained interest for development of dynamic network pricing mechanisms to reflect network cost on a real time basis. Recent developments in smart grid technologies have offered opportunities to utilise these innovative technologies for real time network pricing. The paper proposes an integrated framework for providing dynamic network pricing for practical distribution networks. This framework introduces an integration of network reconfiguration algorithm in association with reference network formation algorithm. Considering the dynamic nature of networks, their reference network would also change with them. With real time inputs, it is possible to form a reference network for every eventuality in the system in real time, and carry out quick analyses based on these smart reference networks, and offer real time dynamic network pricing.
... Efforts were made to develop RN for DN in India, aimed at network pricing and SG initiatives [18], [47], [48]. The approach adopted involves the use of a "decision tree." ...
In recent decades, there has been an increasing penetration of new smart grids (SG) and distributed generations (DG) that are connected to the distribution network (DN). Thus, it is critical for utilities to analyze and assess their impact on the power system networks, which often necessitates major decisions about network operation and planning. Consequently, researchers are constantly developing new and improved methods of advanced control and operation to address these challenges. Unfortunately, there are a limited number of realistic DN models that are made publicly available by the utilities for the development, testing, and evaluation of such new methods. This is mainly caused by the utilities' concerns and reluctance to reveal the public's real and “sensitive” network information. Although international standard test systems such as IEEE and CIGRE are publicly available, these test network models are customized based on the US DN and are not representative of the other networks that operate under different network settings. This paper presents a brief literature survey of existing and prominent representative DNs with a special emphasis on identifying the general description, and application, as a comparison for future development of test network in Malaysia.
... In a SG environment, network cost component can be reflected as a component of smart network prices when actual network usage is known. Smart meters at different network levels can capture user's contributions to asset peak usage, and can be used to compute network usage charges [14]- [15]. ...
Impending Smart Grid environment can offer innovative solutions to alleviate network congestion through efficient network management. This paper proposes a coincident demand based Smart Long Run Incremental Cost (LRIC) pricing mechanism to provide efficient pricing signal to users for mitigating network congestion. Considering that future smart meters would measure user's coincident peak demand, the user is offered a coincident demand based Smart Pricing signal in a LRIC pricing framework. The proposed approach is applied on 22-bus practical Indian reference network. Users connected at the various nodes face network charges based on their coincident demand to each upstream asset. The results encourage users to modify their consumption pattern, and reduce their coincidence to network peak usage.
The intuition of the power distribution system is to supply good quality of power to the customers with cost-effectively and environment friendly. Renewable energy resources (RES) are integrated in the distribution system to meet out the variable load demand with the decarbonizing effect. With the inclusion of RES, the operation of Distribution Network (DN) has become more complex. This paper describes the state of art in various load flow methods used to analyze the parameters in DN. This paper emphasizes upon the various challenges of DN with the integration of RES. It reviews the various pricing methodologies for the delivered power in DN elaborately. The importance of Demand Side Management (DSM) and energy storage in DN are explored in this paper. The analysis of nodal voltages in the DN with Solar PV, Storage, PHEV and Diesel sources is demonstrated on IEEE four node test feeder.
The electricity sector is confronted by critical challenges viz. growing energy demand, high aggregated technical and commercial (AT&C) losses and quality of power supply. These challenges lead the development of smart grid technology which brings efficiency and sustainability in meeting the growing electricity demand with reliability and best of the quality. Energy demand in the world is increasing at a rapid rate. To meet the rise in demand as well as to provide an affordable, reliable and sustainable supply of electricity to the consumer, Smart Grid is the need of hour. The implementation of smart grid benefits both the utility and the consumer. This paper addresses the smart distribution grid scenario of different countries in detail. It also presents the survey about the advanced metering infrastructure, clustering of customer consumption and integration of renewable energy in the distribution sector of the smart grid.
Distribution system planning involves a set of complex analysis as the amount of data and associated parameters needed for the analysis are huge. Simplified reference network models (or a generic representative network) would help to reduce the amount of data to be handled, and thereby simplify the complexities of analysis. Depending on the parameters used, reference network models could be applied to assess the technical and economic performance of a network, such as, investment consequences against impact of customer end tariff pricing. The inherent idea is to develop a generic reference models that would help to visualize the impact of different planning parameters, such as adequacy, reliability, and quality against cost. These models have the potential capability for flexible usage on fast developing networks. This paper discusses an indigenous conceptual development of a reference network based on the Malaysian distribution system
Upcoming smart grid environment can offer innovative mechanisms for efficient network management, to relieve the network presently reeling under congestion. A smart network pricing mechanism has been proposed in this paper, to provide effective network pricing signal to the users for network congestion. Considering that future smart meters could measure user's coincident peak demand, the user is offered a coincidence factor (CF) based smart pricing signal, in a Long Run Incremental Cost (LRIC) pricing framework. The proposed approach is applied on 22-bus practical Indian reference network. Different category customers connected at the same node face different network charges, based on their coincident demand. The results encourage users to modify their consumption pattern, and reduce their coincidence to network peaks.
This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, load balancing among feeders, and is subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages, and radial optimal operation of networks. A specific approach of the generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages: the first one is the master problem and is formulated as a mixed integer nonlinear programming problem. This stage determines the radial topology of the distribution network. The second stage is the slave problem and is formulated as a nonlinear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in the general algebraic modeling system. The effectiveness of the proposal is demonstrated through three examples extracted from the literature.
Load flow method suitable for both radial and weakly-meshed network structures common to distribution systems is proposed in this paper. Here the concept duality of network has been exploited to obtain the solution. Unique data feeding technique and creation of single matrix [branch-voltage drop to node-current] based on dual nature of the electrical network are used in the procedural technique. A single informative forward path impedance [FPI] matrix is developed in the proposed method and it is found to be adequate for the analysis. The method first arranges constant input data and then proceeds further by collecting the information about forward path-impedances in matrix form. Then identify the dual of forward path-impedance matrix, which gives backward nodal-current injection information about the network. The solution is derived using forward path impedance and branch currents. This methodology is programmed for an IEEE 15-Node network using MATLAB Ver. 7.0. and it is demostrated that computational efficiency has been improved by the algorithm suggested. This paper also includes equations for two real-world issues like, when lines are modeled as Pi section and for network having tap changing transformer. The proposed method is flexible to extend for 3-phase networks also.
This paper presents the main features characterizing ANETO, a tool intended to automatically generate a theoretical distribution network connecting available transmission sources with customers at all levels (high, medium and low voltages). In addition to the main modules, design criteria and algorithms behind ANETO, illustrative results arising from its application to the Spanish system will be shown.
This paper presents a new approach for distribution system reconfiguration (DSR) based on optimum power flow (OPF) in which the branch statuses (open/close) are represented by continuous functions. In the proposed approach, all branches are initially considered closed, and from the OPF results, a heuristic technique is used to determine the next loop to be broken by opening one switch. Then the list of switches that are candidates to be opened is updated, and the above process is repeated until all loops are broken, making the distribution system radial. This paper includes results and comparisons on test systems utilized in three classical papers published in the technical literature, as well as in a previous paper by the authors. Results obtained on a real large-scale distribution system are also presented
Smart Grids are paving the way for innovative technologies and services. Reference networks aid in quick decision making relating to network operation and pricing. Linking the two concepts would enable many real time conclusions to be drawn from the existing network and aid in strategic decision making. An algorithm is proposed for the formation of a reference network for a practical distribution system. Considering the dynamic nature of Smart Grids, the reference network for such a grid would also need to change with the network. If real time inputs from a Smart Grid are available, it would be possible to form a reference network for every eventuality in the system in real time and carry out quick analyses based on these smart reference networks. Using these reference networks, the smart system control may be developed, making it possible for the system to be operated in the most optimal manner.
This paper presents an overview of demand response (DR) in electricity market. The definition and a classification of demand response will be presented. Different potential benefits as well as cost components of demand response will be presented. The most common indices used for demand response evaluation are highlighted. Moreover, some utilities experiences with different demand response programs will be presented.
The modernization of the US electric power infrastructure, especially in lieu of its aging, overstressed networks; shifts in social, energy and environmental policies, and also new vulnerabilities, is a national concern. Our system are required to be more adaptive and secure more than every before. Consumers are also demanding increased power quality and reliability of supply and delivery. As such, power industries, government and national laboratories and consortia have developed increased interest in what is now called the smart grid of the future. The paper outlines smart grid intelligent functions that advance interactions of agents such as telecommunication, control, and optimization to achieve adaptability, self-healing, efficiency and reliability of power systems. The author also presents a special case for the development of dynamic stochastic optimal power flow (DSOPF) technology as a tool needed in smart grid design. The integration of DSOPF to achieve the design goals with advanced DMS capabilities are discussed herein. This reference paper also outlines research focus for developing next generation of advance tools for efficient and flexible power systems operation and control.
Many believe the electric power system is undergoing a profound change driven by a number of needs. There's the need for environmental compliance and energy conservation. We need better grid reliability while dealing with an aging infrastructure. And we need improved operational effi ciencies and customer service. The changes that are happening are particularly signifi cant for the electricity distribution grid, where "blind" and manual operations, along with the electromechanical components, will need to be transformed into a "smart grid." This transformation will be necessary to meet environmental targets, to accommodate a greater emphasis on demand response (DR), and to support plug-in hybrid electric vehicles (PHEVs) as well as distributed generation and storage capabilities. It is safe to say that these needs and changes present the power industry with the biggest challenge it has ever faced. On one hand, the transition to a smart grid has to be evolutionary to keep the lights on; on the other hand, the issues surrounding the smart grid are signifi cant enough to demand major changes in power systems operating philosophy.
There has been much recent discussion on what distribution systems can and should look like in the future. Terms related to this discussion include smart grid, distribution system of the future, and others. Functionally, a smart grid should be able to provide new abilities such as self-healing, high reliability, energy management, and real-time pricing. From a design perspective, a smart grid will likely incorporate new technologies such as advanced metering, automation, communication, distributed generation, and distributed storage. This paper discussed the potential impact that issues related to smart grid will have on distribution system design.
Charging methodology is one important scheme in the deregulated environment in the way that it can be utilized to recover the investment cost from network users according to their different impact on the network. The long-run incremental cost (LRIC) pricing methodology developed by University of Bath in conjunction with Western Power Distribution (WPD, UK) and Ofgem (the office of gas and electricity markets, UK) has drawn lots of attention from industry and academic circles and found its application in practice. Compared with the existing long-run cost pricing methodologies, this charging model can produce forward-looking charges that reflect both the extent of the network needed to serve the generation/demand and the degree to which the network is utilized. This paper examines the practical issues concerning implementation of this charging model in order to assist its utilization in the future. Firstly, the calculation and selection of the parameters, load growth rate, contingency factor, asset costs, that would impact charge evaluation are discussed, followed by the focus on some particular issues concerning them. Thereafter, the technical problems which might appear while applying this charging model to large-scale practical systems are dressed and a few feasible solutions are provided. This charging model, at last, is demonstrated on a practical system taken from the U.K. network.
Demand response (DR) is becoming an integral part of power system and market operations. Smart grid technologies will further increase the use of DR in everyday operations. Once the volume of the DR reaches a certain threshold, the effect of the DR events on the distribution and transmission system operations will be hard to ignore. This paper proposes changing the business process of DR scheduling and implementation by integrating DR with distribution grid topology. Study cases using OATI webDistribute show the potential DR effect on distribution grid operations and the distribution grid changing the effectiveness of the DR. These examples illustrate the need of integrating demand response with the distribution grid.
The complexity in handling distribution networks for network pricing analysis can be reduced with the development of simplified reference network model of the actual network. These models provide a test system to assess the investment consequences of applying different tariff charging approaches and analyzing the impact of such approaches on customer use-of-system prices. This helps to foresee the requirement of future network investment. The inherent idea is to be able to visualize the impact of pricing models while working with a small number of networks that are able to represent a large number of actual feeders. As the thrust of power system restructuring is shifting towards developing countries, a relevant work for a large network has been undertaken.
In this article, we present the security, agility, and robustness/survivability of a large-scale power delivery infrastructure that faces new threats and unanticipated conditions. By way of background, we present a brief overview of the past work on the challenges faced in online parameter estimation and real-time adaptive control of a damaged F-15 aircraft. This work, in part, provided the inspiration and laid the foundation in the 1990s for the flight testing of a fast parameter estimation/modeling and reconfigurable aircraft control system that allowed the F-15 to become self-healing in the face of damaged equipment.
It is becoming very important to be able to demonstrate and quantify the necessity and benefit of particular investment and operational decisions in electricity distribution systems, particularly in the context of service quality. Consequently, network performance, traditionally considered mainly from the network owner's perspective, is now becoming customer driven, leading to the need to include an assessment of customers' worth of supply and the benefit they derive by system investment. This concept is at the heart of performance-based regulation. However, the development requires a framework to be created that would enable strategic decisions to be determined. In the UK, this centres on the Information and Incentive Project (IIP). This was set up to strengthen the incentives with respect to delivering the quality of output. As the IIP is based on financial penalties and rewards, the overall distribution revenue is a function not only of the operating and capital costs incurred by the network owner in providing the service, but also of the quality of customer service. These new performance-based developments in regulation, including the UK IIP activities, require a framework to be created that would enable strategic decisions to be determined. This necessitates an understanding of the relationship between certain input and output parameters involved in the decision-making process which in turn requires tools for quantifying the relationship between investment and operational decisions with system performance. Such a quantitative understanding would enable a strategy to be set, subsequent to which specific designs could be implemented. At UMIST, considerable work has been carried out on the development of alternative approaches, concepts and techniques to support and facilitate the strategic decision-making process related to distribution network operation and investment expenditure. These are discussed in this article.
Distribution systems are inherent monopolies and therefore they have generally been regulated to protect customers and to ensure cost-effective operation. In the UK this is one of the functions of the Office of Gas and Electricity Markets (OFGEM). Initially the regulation was based on the value of assets but there is now a trend towards performance-based regulation. To achieve this, a methodology is needed that enables the reliability performance associated with alternative investment strategies to be compared with the investment cost of these strategies. At present there is no accepted approach for such assessments. An approach based on the concept of reference networks is proposed. The essential idea is to analyse a small number of networks that represent the real feeders of the system being considered. The main stages are: to classify the real feeders into coherent clusters, to construct a representative network for each cluster, to assess the reliability of these representative networks and to re-aggregate the results to give those for the overall system. These representative networks are then analysed repetitively for different investment scenarios and the corresponding reference networks derived. The approach can be used to assess individual companies on an absolute basis or to compare the relative performance between companies. The approach, its implementation in conjunction with a number of distribution companies, and its effectiveness when approach using the underground part of a real system are described
The authors report a power-flow-minimum heuristic algorithm for
determining the minimum loss configuration of radial distribution
networks. The algorithm is based on the concept of optimum flow pattern
which is determined by solving the KVL and KCL (Kirchoff's voltage and
current laws) equations of the network. The optimum flow pattern of a
single loop formed by closing a normally open switch is found, and the
flow pattern is established in the radial network by opening a closed
switch. This process is repeated until the minimum loss configuration is
obtained. A simple, fast and approximate power flow method has also been
developed to assist the reconfiguration algorithm. The proposed
reconfiguration algorithm has been found to give better network
configuration than those obtained by some other methods
The network performance assessment model-Regulation with a reference network
- M. B-O Larsson
Transforming to a smart grid
- T F Weaver
Network benefits from introducing an economic methodology for distribution charging Study submitted by Dept
- F Li
- D Tolley
- N P Padhy
- Ji Wang