Congestion Management

Smart hybrid heat pumps have the capability to perform smart switching between electricity and gas by employing a fully-optimized control technology with predictive demand-side management to automatically use the most costeffective heating mode across time. This enables a mechanism for delivering flexible demand-side response in a domestic setting. This paper conducts a comprehensive analysis of the fine-grained data collected during the world's first sizable field trial of smart hybrid heat pumps to present the benefits of the smart control technology. More specifically, a novel flexibility quantification framework is proposed to estimate the capability of heat pump demand shifting based on preheating. Within the proposed framework, accurate estimation of baseline heat demand during the days with interventions is fundamentally critical for understanding the effectiveness of smart control. Furthermore, diversity of heat pump demand is quantified across different numbers of households as an important input into electricity distribution network planning. Finally, the observed values of the Coefficient of Performance (COP) have been analyzed to demonstrate that the smart control can optimize the heat pump operation while taking into account a variety of parameters including the heat pump output water temperature, therefore delivering higher average COP values by maximizing the operating efficiency of the heat pump. Finally, the results of the wholesystem assessment of smart hybrid heat pumps demonstrate that the system value of smart control is between 2.1 and 5.3£bn/year.

With deregulation and open access of the electricity supply industry occurring internationally, there is an increasing need to develop power market oriented optimal power flow (OPF) algorithm for power systems of developing countries. A genetic algorithm based OPF is proposed for this purpose, which inherits both the real and reactive power constraints with loss expressions involving B-coefficients for active power and C-coefficients for reactive power. The significance of the paper is the development of a flexible OPF methodology using both real and reactive power constraints, which can address a very important issue like determination of the spot price for each participant generator in the economic operation of restructured power systems in the developing countries. The proposed methodology has been tested in a 203 buses 267 lines 23 machines real power system of eastern part of India and the simulation results have established that the proposed method is promising for large scale optimizations under deregulated environments.

In a restructured electricity market environment, the competition in the production and consumption of electric energy leads to the transmission network operating at or beyond one or more transfer limits. Then the system gets congested, resulting in an increase in the cost of electricity and the system security as well as reliability are said to be in danger. The selection of generators to reschedule their output for effective management of congestion is a crucial task for the system operator. This paper presents a differential evolution algorithm based on power flow tracing approach for selection and rescheduling of active power output. The proposed method is demonstrated on IEEE 30 bus and Indian utility 62 bus systems.

Power losses in transmission systems are most of the time seen as a small amount (2-5%) from the total power carried over the network. However, transmission loss allocation may play a crucial role in the congestion management of balancing markets. Several loss allocation and loss cost allocation methods have been proposed and implemented in different markets. Most of these methods are intended to be used post market. This paper presents a novel near real-time loss allocation method suitable to be applied in real-time markets as envisioned in the smart grid context. The proposed method allocates the total system losses fairly to all the demand and generator buses, by taking into account the dynamical changes of the power network states, which are provided by an accurate state estimation. The power flows required to determine the allocated losses are executed after an economic dispatch procedure that ignores losses, making the choice of the slack bus an independent factor. The proposed method can be used as an accurate real-time pricing for network usage while the resolving of transmission congestion can be more reliable.

In this paper, a Flower Pollination Algorithm (FPA) has been proposed for relieving congestion in the deregulated power electricity industry. Congestion in the power market is one the contemplative challenges to be overcome in the era of deregulation. The primary cause of congestion is due to the loss of the transmission line, an increase in load, or loss of generator(s). Hence, managing congestion is one of the issues which have to be tackled in the present scenario. There are several techniques to relieve congestion. It is quite well-known that the thermal limits of transmission lines in a power system are fixed. One of the methods to abate congestion is to reschedule the real power of the generators. The purpose of the present work is to benefit the Independent System Operator (ISO) in reliving congestion. (1) In order to meet this objective effectively, a FPA algorithm has been proposed for relieving congestion and is simulated on a modified IEEE 30-bus system initially. (2) Con...

This paper proposes a congestion cost allocation method for pool market structure. The congestion cost presented here is the cost of congestion relief. This paper begins with the discussion on the basic concept of pool market. Then congestion cost allocation methods for pool market; uniform pricing and nodal pricing are discussed. The weaknesses of the existing methods are highlighted. As a result, a proposed congestion cost allocation strategy for a pure-pool based electricity market is presented. Case studies using a simple 3-buses and IEEE-14 bus system are presented to test the proposed method. The old uniform pricing in the old England & Wales (E&W) pool market and nodal pricing are used to compare the proposed method.

This paper proposes a congestion cost allocation method for pool market structure. The congestion cost presented here is the cost of congestion relief. This paper begins with the discussion on the basic concept of pool market. Then congestion cost allocation methods for pool market; uniform pricing and nodal pricing are discussed. The weaknesses of the existing methods are highlighted. As a result, a proposed congestion cost allocation strategy for a pure-pool based electricity market is presented. Case studies using a simple 3-buses and IEEE-14 bus system are presented to test the proposed method. The old uniform pricing in the old England & Wales (E&W) pool market and nodal pricing are used to compare the proposed method.

The solution of power system constraints is an important issue that has to be addressed to achieve a fair operation of a competitive electricity market. In the Spanish electricity market, the System Operator (SO) is in charge of determining the technical feasibility of the generation dispatch provided by the Market Operator (MO). An optimal solution method of power system constraints in the Spanish market must take into account the connection of off-line units to solve both branch overloads and voltage constraints, the adjustment of voltage control resources, the solution of the postulated n-1 and n-2 contingencies with a preventive criteria and the coupling of the solution in the 24 hourly scenarios due to the start-up cost of nonconnected units. This paper details the management of power system constraints in the Spanish market, and contains a comprehensive review of solution methods of power system constraints. In addition, the paper proposes a novel approach to solve Spanish power system constraints that overcomes the limitations of existing methods, by decoupling the solution of branch overloads and voltage constraints.

EU power market design has been focused on facilitating trading between countries and for this has defined interfaces for market participants and TSOs between countries. The operation of power systems and markets within countries was not the focus of these developments. This may have contributed to difficulties of defining or implementing a common perspective in particular on intraday and balancing approaches. This motivated us to pursue an in depth review of six European power markets to contribute to a better understanding of the common elements, differences and the physical and institutional reasons for these. With this paper we aim to present the main insights emerging from the reviews and to identify where there is a need for alignment of operational aspects and shortterm trading arrangements, taking into account system requirements individual member states face in operating their power system.

The paper introduces a framework for information exchange and coordination of security assessment suitable for distributed multi-area control in large interconnections operated by a team of transmission system operators. The basic idea of the proposed framework consists of exchanging just enough information so that each operator can evaluate the impact in his control area of contingencies both internal and external to his area. The framework has been thought out with the European perspective in mind where it is presently not possible to set up a transnational security coordinator that would have authority to handle security control over the whole or part of the European interconnection. Nevertheless, it can also be considered as an approach to handle security control in North-American Mega-RTOs, where it could help to circumvent problems of scalability of algorithms and maintainability of data by distributing them over the TSOs under the authority of the RTO.

This work focuses on congestion-driven placement of standard cells into rows in the fixed-die context. We summarize the stateof-the-art after two decades of research in recursive bisection placement and implement a new placer, called Capo, to empirically study the achievable limits of the approach. From among recently proposed improvements to recursive bisection, Capo incorporates a leading-edge multilevel min-cut partitioner [7], techniques for partitioning with small tolerance [8], optimal min-cut partitioners and end-case min-wirelength placers [5], previously unpublished partitioning tolerance computations, and block splitting heuristics. On the other hand, our "good enough" implementation does not use "overlapping" [17], multi-way partitioners [17, 20], analytical placement, or congestion estimation [24, 35]. In order to run on recent industrial placement instances, Capo must take into account fixed macros, power stripes and rows with different allowed cell orientations. Capo reads industry-standard LEF/DEF, as well as formats of the GSRC bookshelf for VLSI CAD algorithms [6], to enable comparisons on available placement instances in the fixed-die regime. Capo clearly demonstrates that despite a potential mismatch of objectives, improved mincut bisection can still lead to improved placement wirelength and congestion. Our experiments on recent industrial benchmarks fail to give a clear answer to the question in the title of this paper. However, they validate a series of improvements to recursive bisection and point out a need for transparent congestion management techniques that do not worsen the wirelength of already routable placements. Our experimental flow, which validates fixed-die placement results by violation-free detailed auto-routability, provides a new norm for comparison of VLSI placement implementations.

Growth in load demand may lead to changes in generation sources and sizes along with all the uncertainty of transactions will further strain existing power systems, and may lead to the transmission systems to work closer to their operating limits or even beyond its transfer capacity and cause congestion. Applications of newly emerging technologies are able to provide solutions for electricity markets to maintain the stability and reliability of power systems while handling large volumes of transactions. FACTS allows flexible operation of AC transmission systems whereby the changes can be accommodated very easily without stressing the system. In this paper the proposed methods are illustrated with a IEEE 30-bus system to improve the congestion management and to reduce the operating cost of the system using STATCOM controller. The optimal location as well as optimal rating of the device is found out for optimal system using Power World Simulator Software 12.0.

Abstract: Weaknesses in several recently proposed ideas about congestion control and avoidance in high-speed netwroks are identified. Both sides of the debate concerning prior reservation of resources versus walk-in service, open-loop control versus feedback control, rate control versus window control, and router-based control versus source-based control are presented. The circumstances under which backpressure is useful or not are discussed, and it is argued that a single congestion scheme is not sufficient, but that a combination of ...

Power systems may not capable of utilizing full transmission capacity. Restructuring of electricity industry produces some management criteria to improve technical as well as economical efficiency. The process of reregulation causes more challenges with regards to technical and trading issues. Under the new scheme of power markets, congestion management is a crucial problem that needed to be considered. Congestion relief can be handled using FACTS devices, where transmissions capability will be improved. In this paper, real genetic algorithm (RGA) is used for optimization process while analytical hierarchy process (AHP) with fuzzy sets is implemented to evaluate RGA fitness function. The effectiveness of the proposed methodology is shown through a modified IEEE 5-bus system.

Congestion management is one amongst the most difficult issues within the power world, not only in India however additionally all told over the world. This paper initially reviews the requirements of the advanced FACTS applications for future power systems, and then discusses general principles of congestion management, that depend upon market models, market policy and electricity network conditions. This paper reviews completely different strategies that are projected to see optimal location and best setting of FACTS devices for the aim of congestion management. Seeking the simplest place is performed using hybrid PSO, serial quadratic programming & genetic algorithmic rule. Further completely different strategies of congestion management by voltage stability & injecting active/reactive power within the system using particle swarm improvement, nonlinear Programming (NLP) & GA are discussed during this paper. IndexTerms EPS, GWO, FACTS, TCSC, active power loss and reactive power los...

Inclusion of renewable energy in power grid at micro and macro level has imposed numerous challenges in the recent years. Occurrence and managing congestion in the power transmission line due to unpredictable and stochastic nature of Renewable Energy Source (RES) integration has become a challenging task to the grid operators. Transmission lines operate at bottlenecks during a congestion episode adding to the extra congestion cost and risk in grid stability which becomes burden to the generation as well as end users. Different methodologies are applied to detect and manage the congestion to eliminate the congestion cost factor and maintain grid stability. The presented analysis compares conventional methodology Linear Sensitivity Factors (LSF) and Heuristic methodology Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) methods for congestion management in power transmission lines with integrated RES (wind and solar) system. For comparative analysis, a modified standard IEEE 30 Bus system is chosen which is integrated with real time RES generation. Optimal locations of RES generation with minimized congestion cost and percentage of RES curtailment are chosen as objective function for comparison of the methodologies.

Congestion management (CM) is one of the most important and challenging tasks of the Independent System Operator (ISO) in the deregulated environment. Recently, Sen Transformer (ST) has emerged as an important power flow control device which has the capability of power flow control over a wide range like UPFC. This device with a conventional transformer and tap changers has the capability of bidirectional control of active and reactive power and can play a very important role in future markets for mitigating the congestion problems. In this paper, the capability of ST has been utilized to manage transmission line congestion for hybrid based electricity market model. The main contribution of the paper is: (i) to develop an optimal rescheduling of generators strategy for real time congestion management and impact of ST for congestion management, (ii) the comparison of ST with unified power flow controller (UPFC) for congestion management, (iii) the secure bilateral transactions determination in a hybrid market model and congestion management with both power flow controllers in combined pool and bilateral market model. The optimal location of ST and UPFC has been obtained solving mixed integer non-linear programming model of congestion management. The proposed model has been applied for results on IEEE 24-bus RTS test system.

This review study explores the complex topic of traffic congestion caused by two-wheeler usage, comparing the situation in India to that of other countries across the world. The research endeavours to conduct a thorough analysis of the obstacles that two-wheelers present in their role as contributors to traffic congestion, as well as the various approaches that have been utilized worldwide to address this widespread problem. The method includes a careful examination of the patterns and root causes of the traffic congestion caused by twowheelers in Indian cities, as well as a comparative analysis with a subset of other nations. The study analyses the effectiveness of several mitigation strategies on a worldwide scale, taking into consideration local differences in the infrastructure, cultural norms, and economic circumstances that affect traffic patterns. Population density, urbanization developments, transportation infrastructure, and cultural factors that contribute to the particular difficulties brought on by two-wheeler traffic congestion are some of the important factors that are being studied. The current research seeks to look at innovative and successful approaches that have been implemented globally, including technology breakthroughs, interventions in urban design, public transit systems, and governmental measures. By synthesizing data from India and diverse global context, this review aspires to provide valuable insights for policymakers, urban planners, and transportation authorities. The findings aim to contribute to a nuanced understanding of effective traffic management strategies, facilitating the development of tailored solutions for mitigating two-wheeler induced congestion in Indian cities. This review paper conducts a comprehensive comparative analysis of traffic congestion in India and several other countries, exploring the diverse factors contributing to this urban challenge and scrutinizing the array of solutions implemented globally.

In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control system where the upper level controller directly controls the lower level subordinated nodes, this study aims to integrate two common indirect control methods:market-based control and price-based control into the hierarchical electric vehicles management system. Specifically, on the lower level of the hierarchy, the FOs coordinate the charging behaviors of their EV users using a price-based control method. A parametric utility model is used on the lower level to characterize price elasticity of electric vehicles and thus used by the FO to coordinate the individual EV charging. On the upper level of the hierarchy, the distribution system operator uses the market-based control strategy to coordinate the limited power capacity of power transformer with fleet operators. To facilitate the application of the two indirect control methods into the system, a model describing decision tasks in control is used to specify the essential functions that are needed in the control system. The simulations illustrate the effectiveness of the proposed solutions.

Secure and continuous power flow in the transmission line is one of the critical issues that must be rectified. In fact, rescheduling based congestion management is considered to be one of the promising solutions for this aspect. Still, the model faces issues onthe basis of rescheduling costs. More research works have been addressed so far to solve the problems of congestion management.  Optimization algorithms also play a vital role in solving this problem. Under this scenario, this paper introduces a new rescheduling based congestion management model that incorporates a new algorithm; Refractor Update based ROA (RU-ROA) that optimizes the generating power of added generators with the bus system. The proposed RU-ROA algorithm is the hybridization of two algorithms, namely Rider Optimization Algorithm (ROA) and Water Wave Optimization (WWO), that aims to manage the congestion with the reduced cost of rescheduling. Further, the proposed model compares its performance over other conventional models like Particle Swarm Optimization (PSO), FireFly (FF), Grey Wolf Optimization (GWO), traditional ROA and traditional WWO based rescheduling strategy with respect to cost analysis and convergence analysis, and proves the efficiency of proposed work over others.

Keywords:Congestion Management; Cost Function; Optimization Algorithm; ROA; Rescheduling strategy

High-performance cell-based communications networks including ATM have been conceived to carry asynchronous traftlc sources and support a continuum of transport rates ranging from low bit-rate to high bit-rate traffic. When a number of bursty traffic sources add cells, tbe network is inevitably subject to congestion. Traditional approaches to congestion management include admission control algorithms, smoothing functions, and the use of finite-sized butYers with queue management techniques. Most queue management schemes, reported in the literature, utilize "fixed" thresholds, i.e., either binary or a limited number of predetermined values based on the cell priorities, to determine when to permit or refuse entry of cells into the buffer. The aim is to achieve a desired tradeoff between the number of cells carried through the network, propagation delays of the cells, and the number of discarded cells. While binary thresholds are excessively restrictive, the rationale underlying the use of a large number of priorities appears to be ad hoe, unnatural, and unclear. This paper introduces, perhaps for the first time, the notion of cell-blocking, wherein a fuzzy thresholding function, based on Zadeh's fuzzy set theory, is utilized to deliberately refuse entry to a fraction of incoming cells from other switches. The blocked cells must be rerouted by the sending switch to other switches and, in the process, they may incur delays. Tbe fraction of blocked cells is a continuous function of the current buffer occupancy level unlike the abrupt, discrete thresholds in the traditional approaches. The fuzzy cell-blocking scheme is simulated on a computer and the simulation results for a given, realistic traffic stimulus, characterized by Poisson arrivals and exponentially distributed departure% are contrasted against those from the traditional approach. A comparative analysis reveals that fuzzy queue management adapts superbly to sharp changes in cell arrival rates and maximum burstiness of bu rsty traffic sources, yielding lower cell discard rates, high throughput of cells through the network, and lower cellbloeking rates. 1. 1NTi70tM-Jc710N A SYNCHRONOUS transfer mode (ATM) networks [I] refer to high performance communications networks that utilize the asynchronous transfer mode as the information Manuscnp[

Network congestion is one of the biggest problems facing HPC systems today, affecting system throughput, performance, user experience, and reproducibility. Congestion manifests as run-to-run variability due to contention for shared resources (e.g., filesystems) or routes between compute endpoints. Despite its significance, current network benchmarks fail to proxy the real-world network utilization seen on congested systems. We propose a new open-source benchmark suite called the Global Performance and Congestion Network Tests (GPCNeT) to advance the state of the practice in this area. The guiding principles used in designing GPCNeT are described and the methodology employed to maximize its utility is presented. The capabilities of GPCNeT are evaluated by analyzing results from several world's largest HPC systems, including an evaluation of congestion management on a next-generation network. The results show that systems of all technologies and scales are susceptible to congestion and this work motivates the need for congestion control in next-generation networks.

Data Envelopment Analysis (DEA) is a nonparametric tool for discriminating the best performers from a number of homogenous Decision Making Units (DMU). Cost oriented DEA models identify those best DMUs which run cost efficient process. This paper validates the outcome derived from the Ideal Frontier (mentioned in Sarkar. S (2014)) derived from non-central Principal Component Analysis and a slack based optimization model to identify the cost efficient DMUs. Instead of offering real cost of each resource, the proposed model minimizes the projection of inputs along the direction of first Eigenvector of specific covariance matrix from each allocated outputs. These essential directions vectors represent various "combined consumption (cost)" for the production of outputs. A Multi-Objective Fuzzy Goal Programming model is applied here to solve this multi-objective problem. Superiority is judged on the basis of higher value of a cost oriented performance ratio. A case study of six schools is incorporated here to identify the superior cost efficient school and also to visualize gaps in their performances.

Express buses operating on freeways and arterials are an important part ofmany metropolitan area transit services. Aregional express bus system plan for the San Francisco, California, Bay Area Is presented; network, st. ..tion and stop, operations, and user Issues are addressed. Previous work had focused on high-occupancy vehicles on freeways; the cnrrent work expands the vision of the system to address the door-to-door trip and ser vice on arterials. Gaps in the high•occupancy-vehicle network, priority treatment strategies, access modes and connections, station and stop design, park•and-ride lots, and public and private access services were analyzed, and other user and operator concerns were addressed. The plan was developed through a partnership that included the state transporta tion agency, the metropolitan planning organization, local transportation sales tax and congestion management agencies, and transit operators, with university researchers providing technical support and facilitation of meetings. On•board surveys and consumer focus groups were con ducted along with stakeholder interviews, field studIes, design evalua tions, and simulation modeling. The plan not only produced valuable information for future improvements but also helped develop a high level of cooperation and consensus among the participating agencies. Both methods used and lessons learned from the Bay Area experience should be useful to other metropolitan areas and transit operators. Express bus services are an important element in strategies for improving urban mobility. Express buses offer customers a fast tide by offeling limited-stop service to intermodal transfer points, work centers, and other major destinations and by making use of priority treatments to speed travel, including reserved lanes and ramps, signal preemption, ramp meter bypass, and fast ticketing options. In the San Francisco, California, Bay Area, numerous express buses operate on the region's freeways and arterials, and the Califor nill Department ofTransportation (Caltrans), the Metropolitan Trans pOl'tation Commission (MTC), transpOltation tax agencies, and the region's transit operators work together to deliver these services. Caltrans owns and operates high-occupancy-vehicle (HOV) lanes on many of the region's freeways, as well as many of the park and ride lots served by express buses. Caltrans also owns several of the major

Congestion management is one of the technical challenges in Power system deregulation. In deregulated electricity market transmission congestion occurs when there is insufficient transmission capacity to simultaneously accommodate all constraints for transmission of a line. Flexible Alternative Current Transmission System (FACTS) devices can be an alternative to reduce the flows in heavily loaded lines, resulting in an increased loadability, low system loss, improved stability of the network, reduced cost of production and fulfilled contractual requirement by controlling the power flow in the network. A method to determine the optimal location of FACTS has been suggested based on real power Performance Index and reduction of total system VAR power losses. The simulation results were successfully tested on IEEE 14 bus system.

Multicriteria Selection of Optimal Location of TCSC in a Competitive Energy MarketThe paper investigates selection of the best location of thyristor-controlled series compensator (TCSC) in a transmission system from many candidate locations in a competitive energy market such that the TCSC causes a net valuable impact on congestion management outcome, transmission utilization, transmission losses, voltage stability, degree of fulfillment of spot market contracts, and system security. The problem is treated as a multicriteria decision-making process such that the candidate locations of TCSC are the alternatives and the conflicting objectives are the outcomes of the dispatch process, which may have different importance weights. The paper proposes some performance indices that the dispatch decision-making entity can use to measure market dispatch outcomes of each alternative. Based on agreed-upon preferences, the measures presented may help the decision maker compare and rank dispatch ...

In this paper, a weighted Pratibha distribution introduced to modelling life time data using the weighted transformation technique in Pratibha distribution. Its statistical properties including survival function, hazard function, reverse hazard function, mean residual life function stochastic ordering, moments related measures such as moments about origin, moments about mean, coefficient of variation, skewness, kurtosis, index of dispersion have been studied. Parameters are estimated by method of maximum likelihood estimation. A simulation study has been carried out to test the consistency of the parameters obtained through the maximum likelihood method. The goodness of fit of the distribution has been presented with a real lifetime dataset and the goodness of fit shows better fit over weighted Sujatha distribution, weighted Komal distribution, weighted Lindley distribution, weighted Garima distribution and weighted Aradhana distribution.

Integration of renewable energy with conventional energy sources is very challenging due to the uncertain nature of renewable energy, which creates imbalance and congestion in the system. Moreover, every market participant/player in deregulated power market wants to achieve the economic benefits within critical system constraints like congestion. Therefore, this paper presents a simple, efficient and reliable two-step optimization strategy to solve the congestion problem along with maximization of system profit, minimization of system generation cost, congestion cost and emission by optimal placement & numbers of Thyristor Controlled Series Compensator (TCSC) along with wind generators in a deregulated power market. Two new indices i.e. 'Congestion Detection Index (CDI)' and 'Index of Total Congestion Cost (ITCC)' have been proposed towards faster identification and reduction of system congestion effectively. The pool & bilateral deregulated market model has been considered for this study. The maximum system profit has been considerably achieved after optimal placement of wind generator and TCSC(s) in the system. The effectiveness of the proposed approach has been analyzed and tested in modified IEEE 14 bus and modified IEEE 118 bus test system. The proposed approach has been compared with the existing related approach for congestion mitigation, and better results have been achieved from the proposed approach.

Congestion management in cellular networks is of prime importance for the mobile network operators of present and future generations. Nowadays cellular operators utilize improved planning techniques for enhanced capacity management, but on the other hand the number of mobile subscribers rapidly increases and additionally, new data-technologies for wireless access add extra traffic to the already overloaded networks, often causing serious problems to their performance. In this paper, we present a resource management system for increasing the efficiency of 2G and 2.5G cellular networks especially during overloading periods through the introduction of innovative extra elements. For validating the system's behavior, a set of trials have been performed focusing on alleviating both voice and data congestion problems. The results of these trials show important improvements on the network's capacity availability when the presented system intervenes.

The Urmia Lake Basin is located between the West and East Azerbaijan provinces in the northwest of Iran. Lake Urmia is the twentieth largest lake and second largest hypersaline lake in the world. Stratigraphic columns have been constructed, using published information, to compare the sedimentary units deposited from the Permian to the Neogene on the east and west sides of the lake, and to use these to quantity subsidence and uplift. East of the lake, the sedimentary section is more complete and has been the subject of detailed stratigraphic studies, including the compilation of measured sections for some units. West of the lake, the section is incomplete and less work has been done; three columns illustrate variations in the preserved stratigraphy for the time interval. In all cases, the columns are capped by the Oligocene–Miocene Qom Formation, which was deposited during a post-orogenic marine transgression and unconformably overlies units ranging from Precambrian to Cretaceous. Pe...

The paper introduces the mechanism of the Flow-based Capacity Allocation (FBA) method on the electricity market of the Central-Eastern Europe (CEE) Region, proposed by the Central Allocation Office (CAO). The method is a coordinated heterogeneous multi-unit uniform price auction where the allo-cation is determined by the solution of a linear programming problem. On one hand, the properties of the underlying lin-ear programming problem are discussed: the possibilities of multiple solutions are analysed, then a non-standard sensitiv-ity analysis method of the market spread auction is developed. On the other hand, a global optimization problem is presented that yields uniform auction prices corresponding to higher total income than at the original allocation method. Several numerical examples and results of practical test problems are presented.

In this paper, the optimal location and sizing of DESS are proposed for transmission congestion management. Transmission Congestion Cost (TCC) is used to find the optimal location of DESS, whereas hybrid optimization based on Flower Pollination Algorithm (FPA) and Differential Evolution (DE) is proposed for optimal sizing of DESS. The methodology considering Solar PV and Energy Storage System (ESS) as sources of energy. 24 hours real temperature and solar irradiance data of Delhi are taken to mathematically model the generation from Solar PV to manage congestion throughout the 24 hours. ESS is used to store surplus energy. The proposed approach is tested on IEEE-30 and IEEE-57 bus system, and 24 hours demand is assumed to follow the hourly load shape (summer season) of the IEEE reliability test system. The performance of the proposed approach is validated by comparing the results obtained through hybrid (FPA-DE) based hybrid optimization with the results obtained through DE optimiza...

The battery energy storage systems (BESSs) have been increasingly installed in the power system, especially with the growing penetration rate of the renewable energy sources. However, it is difficult for BESSs to be profitable due to high capital costs. In order to boost the economic value of BESSs, this paper proposes a hierarchical energy management system (HiEMS) to aggregate multiple BESSs, and to achieve multi-market business operations. The proposed HiEMS optimizes the multi-market bids considering a realistic BESS performance model, and coordinates the BESSs and manages their state of charge (SOC) values, according to their price penalties based on dynamically generated annualized cost. By taking part in the energy market and regulation market at the same time, the cost-performance index (CPI) of the BESS aggregation is greatly improved. The impact of photovoltaic generation (PV) on system performance and CPI is also studied.

We analyze three applied incentive compatibility conditions within a class of queueing problems motivated by the reassignment of flights to airport landing slots. A preexisting landing schedule becomes wasteful when airlines privately learn updates about their flights ’ cancelations or feasible flight times. The FAA’s objective is to create a new queue that does not waste landing slots. We separately consider the airlines ’ incentives to report their flights ’ (IC1) feasible arrival times, (IC2) delay costs, or (IC3) cancelations. Our first three results show that any Pareto efficient rescheduling rule must be manipulable by each of these three methods separately. By weakening efficiency to a form currently achieved by the FAA, we recover incentive compatibility with respect to (IC2) and (IC3) by extending the Deferred Acceptance (DA) algorithm, while the FAA’s current mechanism fails (IC3). Our extension is consistent with the FAA’s information infrastructure, which does not elicit...

The fuel existing vehicles produce air pollution, noise pollution and it produces many other effects on an environment like global warming, greenhouse effect etc. Due to these impacts, conventional fuel for vehicles is changing to battery. Hence there is increase in number of Electric Vehicle (EV) recently. In EV there is a major disadvantage that it could not travel more than few hundred kilometers. For solving this issue, if the battery capacity of EV increased, then weight and size also increase thus it is not possible. Hence there is a need for setting up the new battery management in the Electric Vehicle. This study provides a full overview as well as an in-depth investigation of this relatively novel and satisfying solution for battery problems in electric vehicles. We divide the battery in half with this innovative battery management technique. One half is for charging and the other half is for discharging. Solar panels and other renewable energy sources, regenerative braking, regenerative suspension is used to charge the vehicle. While one side is charging, the other is simultaneously discharging. We use the charged section of the battery when the other half is totally discharged, and the discharged portion is stored for charging. we don't need external charging because of this management, and the vehicle can charge itself. We're also not using two distinct batteries, so there won't be any space issues, this article will focus on the design and analysis of this battery management system, as well as its benefits and prospective applications. Its ability to solve the electric vehicle's inclination problem.

In deregulated electricity markets congestion in the transmission is one of the technical problems. There are two types of congestion management methodologies to relieve it. In both techniques one technique is non-cost free methods and another is cost-free technique, among them first technique resolve the congestion on the basis of economic point of view whereas another resolve technically. Along with this, the optimal dispatch solution using security constrained economic dispatch eliminates the possible occurrence of congestion. The transmission congestion management involves set of rules and regulation to resolve congestion and ensure control over generators and loads for maintain the system security and reliability within acceptable level. In a deregulated market structure, the market must be modelled so that the market participants engage freely in transactions and play as per market forces, but in a manner that does not threaten the security of the power system. So the main aim of this paper is to explain various congestion management schemes considering both technical as well as economic points.

Today's electricity paradigm requires that the notion of active distribution systems be introduced at both undergraduate and graduate curricula. This involves not only the customary theoretical foundations but also a suitable power engineering lab where flexible enough and affordable resources allow students and researchers to carry out hands-on experiments reinforcing the concepts explained in the classroom. This paper describes the smart grid lab of the Power Engineering Group at the University of Seville, composed of a scaled-down distribution system, along with the required control and monitoring equipment, designed to help its users easily grasp the major influence that distributed generation and storage devices exert in the operation of MV distribution systems.

In this paper, we present a method and a model for managing transmission congestion based on ex ante congestion prices. Our method is influenced by the yield management approach widely used for airline reservation systems, and our model is built based on the relations between transmission congestion prices and electricity commodity prices that exist for an optimal solution. We formulate the congestion pricing problem as a master problem and the electricity commodity (energy and reserve) pricing as subproblems. Examples are presented to illustrate how a system operator can use this approach to compute ex ante congestion prices and how market operators can determine clearing prices and schedules of forward electric energy and reserve markets.

Technological advancements are rapidly changing traffic management in cities. Massive adoption of mobile devices and cloud-based applications have created new mechanisms for urban traffic control and management. Specifically, navigation applications have impacted cities in multiple ways by rerouting traffic on their streets. As different routing strategies distribute traffic differently across the city network, understanding these differences across multiple dimensions is highly relevant for policymakers. In this paper, we develop a holistic framework of indicators, called Socially-Aware Evaluation Framework for Transportation (SAEF), that will assist in understanding how traffic routing and the resultant traffic dynamics impact city metrics, with the intent of avoiding unintended consequences and adhering to city objectives. SAEF is a holistic decision framework formed as an assembled set of city performance indicators grounded in the literature. The selected indicators can be evaluated for cities of various sizes and at the urban scale. The SAEF framework is presented for four Bay Area cities, for which we compare three different routing strategies. Our intent with this work is to provide an evaluation framework that enables reflection on the consequence of policies, traffic management strategies and network changes. With an ability to model out proposed traffic management strategies, the policymaker can consider the trade-offs and potential unintended consequences.

Multi-agent based modeling for electric vehicle integration in a distribution network operation The purpose of this paper is to present a multi-agent based modeling technology for simulating and operating a hierarchical energy management of a power distribution system with focus on EVs integration. The proposed multi-agent system consists of four types of agents: i) Distribution system operator (DSO) technical agent and ii) DSO market agents that both belong to the top layer of the hierarchy and their roles are to manage the distribution network by avoiding grid congestions and using congestion prices to coordinate the energy scheduled; iii) Electric vehicle virtual power plant agents are in the middle level of the hierarchy and their roles are to manage the charge process of the electric vehicles; iv) Electric vehicle agents are placed at the bottom layer of the hierarchy and they represent electric vehicle owners with different users' profiles. To demonstrate the coordination behavior of the proposed system, a multi-agent simulation platform is developed based on the co-simulation environment of JACK, Matlab and GAMS. The aim of the multi-agent system is to simulate the collaborative (all agents contribute to achieve an optimized global performance) but also competitive environment (each agent will try to increase its utilities or reduce its costs). [All rights reserved Elsevier].

To alleviate congestions of grids is one of the most important managerial performance indicators in the electricity market. The role of retail electricity providers (REPs) can be effective in alleviating such congestions. However, little effort has been devoted for involving REPs collaboratively in congestion alleviation. This paper addresses this shortfall in the literature. It proposes an innovative solution for the congestion problem through reinforcing a collaboration between the ISO and REPs in implementing demand response (DR) programs. The idea of economic signaling, conveyed by the ISO to REPs, is employed to assist REPs in trading with demand response aggregators. Stackelberg game theory is adopted for designing such trade in the market. The effectiveness of the proposed method is evaluated using a test power system. The paper demonstrates an effective performance for the proposed method. By providing a novel game theory solution for the congestion problem based on involving REPs in the DR program, a contribution is made to the current practice of grid congestion management. The paper outcomes will be of particular interest when the grid faces the highest possible demand particularly during the hot season. Index Terms Congestion management, demand response, REPs, market framework. Nomenclature Number of grid buses. k Index of REPs participating in the DR market. n Index of DRAs participating in the DR market. DR price. Demand reduction of REPk. Vector containing all REPs' demand reduction other than REP k. DR selling amount of DRA n. Vector containing all DRAs' DR selling other than DRAn. _ Maximum allowable demand reduction of DRAn. Payoff of REPk. Payoff of DRA n. M Maximum number of DRAs participating in DR. Consumer s load interrupt costs. X Demand reduction at all bus. Customers willingness to participate in DR through DRA n. It takes values in the range 0 to 1. A binary coefficient, representing DRAs' decision for participating in the DR trade. a, b Constant coefficients in and , respectively. REPs incomes, before implementing DR. REPs incomes, after implementing DR.

In this paper the sub-problems associated with the economical operation of a power system can be reduced. But the electrical marketing of a system is so complicated. The congestion management is the recent problem facing today much in order to provide cons tant supply of power to the consumers in an reliable manner. So we are trying to remove the congestion in the transmission line by means of generation rescheduling with the cost involved in the rescheduling process will be minimized. In this paper the adaptive bacterial foraging algorithm with Nelder Mead is used for optimizing the congestion cost. The outputs and results are compared with the optimization techniques like genetic algorithm (GA), Particle Swarm Optimization (PSO) and simple bacterial foraging algorithm. The numerical expression for representing the performance of the optimization techniques are done by means of six generating units having standard IEEE 30 bus system. This technique can be reformulated in future for...

This work focused on prescribing, designing, implementing, and evaluating a pilot project conducted in the Greek power system that addressed balancing and congestion management issues that system operators (SOs) face within the clean energy era. The considered pilot project fully focused on the development of the F-channel platform, including the idea behind this application, the steps that were taken in the process, and the outcomes of the performed activities fitting into the overall picture of the OneNet project. The specified F-channel platform is a web-based, client-server application that uses artificial intelligence (AI) techniques and cloud computation engines to improve the management of the active power for the TSO-DSO coordination. The flexibility of the grid’s resources was identified, and an integrated monitoring system based on the precise forecasting of variable generation and demand was implemented. The focus areas were congestion management, frequency control, and v...

Quantized Congestion Notification (QCN) has been developed for IEEE 802.1Qau to provide congestion control at the Ethernet Layer or Layer 2 in data center networks (DCNs) by the IEEE Data Center Bridging Task Group. One drawback of QCN is the rate unfairness of different flows when sharing one bottleneck link. In this paper, we propose an enhanced QCN congestion notification algorithm, called fair QCN (FQCN), to improve rate allocation fairness of multiple flows sharing one bottleneck link in DCNs. FQCN identifies congestion culprits through joint queue and per flow monitoring, feedbacks individual congestion information to each culprit through multicasting, and ensures convergence to statistical fairness. We analyze the stability and fairness of FQCN via Lyapunov functions and evaluate the performance of FQCN through simulations in terms of the queue length stability, link throughput and rate allocations to traffic flows with different traffic dynamics under three network topologies. Simulation results confirm the rate allocation unfairness of QCN, and validate that FQCN maintains the queue length stability, successfully allocates the fair share rate to each traffic source sharing the link capacity, and enhances TCP throughput performance in the TCP Incast setting.

As the world is progressing forward, the load demand in the power system has been continuously increasing day by day. This situation has forced the power system to operate under stress condition due to its limitation. Therefore, due to the stressed condition, the transmission losses faced higher increment with a lower minimum voltage. Theoretically, the installation of the Flexible AC Transmission System (FACTS) device can solve the problem experienced by the power system. This paper presents the Whale Optimization Algorithm for loss minimization using FACTS devices in the transmission system. Thyristor controlled series compensator (TCSC) is chosen for this study. In this study, WOA is developed to identify the optimal sizing of FACTS device for loss minimization in the power system. IEEE 30-bus RTS was used as the test system to validate the effectiveness of the proposed algorithm.

As pressures to decarbonize the electricity grid increase, the grid edge is witnessing a rapid adoption of distributed and renewable generation. As a result, traditional methods for reactive power management and compensation may become ineffective. Current state-of-art for reactive power compensation, which rely primarily on capacity payments, exclude distributed generation (DG). We propose an alternative: a reactive power market at the distribution level designed to meet the needs of decentralized and decarbonized grids. The proposed market uses variable payments to compensate DGs equipped with smart inverters, at an increased spatial and temporal granularity, through a distribution-level Locational Marginal Price (d-LMP). We validate our proposed market with a case study of the US New England grid on a modified IEEE-123 bus, while varying DG penetration from 5% to 160%. Results show that our market can accommodate such a large penetration, with stable reactive power revenue streams. The market can leverage the considerable flexibility afforded by inverter-based resources to meet over 40% of reactive power load when operating in a power factor range of 0.6 to 1.0. DGs participating in the market can earn up to 11% of their total revenue from reactive power payments. Finally, the corresponding daily d-LMPs determined from the proposed market were observed to exhibit limited volatility.