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The ancillary reactive power service pricing in a Deregulated electricity market

The ancillary reactive power service pricing in a Deregulated electricity market

The reactive power management and pricing mechanisms are different for each deregulated electricity market and depend on frame work of contracts and market operation. Usually the ISO enters into contracts with reactive power suppliers for their service provisions. As per the NERC’s Operating Policy in the US market , only that reactive power supplied by synchronous generators are considered as an ancillary service and can receive payment( financial compensation) for their services. The same is applied in UK and Australian markets. The Australian market additionally considers reactive power from synchronous condensers as ancillary service. On the other hand, restructured markets in the Nordic countries have not any provision for payments towards reactive power services .In Sweden the accountability for managing reactive power lies with network companies, with certain policies from the ISO, stipulating that there should be no exchange of reactive power over different network voltage levels and transformers. To meet these requirements, individual entities, such as local and regional networks, have to make arrangement for their own reactive power. In a similar manner in Netherlands, the network companies have to take care of their reactive power requirement on their own. These companies However these companies purchase reactive power locally through bilateral contracts with generators or through exchange with other network companies. The generators which have contract for the reactive power service are paid for their reactive power capacity and no payment for reactive energy support.

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Exploring the bilateral and hybrid model in deregulated electricity market

Exploring the bilateral and hybrid model in deregulated electricity market

However, in a deregulated electricity market, while the utility still owns all the infrastructure and is still responsible for distributing electricity to home, competing electricity providers are allowed to buy the electricity and sell it to the consumer directly. Then, if the customers have a power outage or a broken transformer in deregulated electricity market, the utility company which is still responsible for all of those issues would still be called by the customer. But the great thing is, the customer is able to choose to shop around and buy the power from any electricity retailer that does business in the market. This kind of market has being widely applied in those countries including Arizona, Arkansas, California, Connecticut, Delaware, Illinois, Maine, Maryland, Massachusetts, Michigan, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, Texas, Virginia, and the District of Columbia.

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Power Flow Tracing Based Congestion Management Using Firefly Algorithm In Deregulated Electricity Market

Power Flow Tracing Based Congestion Management Using Firefly Algorithm In Deregulated Electricity Market

In a deregulated electricity market, freedom is provided to participants to buy and sell electricity. When the producers and consumers of electric energy desire to transact power in bulk amount, unexpected congestion occurs due to violation of physical limits in transmission system. The undesirable effects of the congestion include prevention of new contracts, increase of the electricity cost in some regions of the electricity market which endanger to the system security and reliability. Congestion in a transmission system cannot be allowed beyond a short duration as it may initiate cascaded outages which forces the system to collapse. Hence an effective control action strategy is necessary to reduce the line overloads to the security limit in minimum time.

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Review of methods to calculate congestion cost allocation in deregulated electricity market

Review of methods to calculate congestion cost allocation in deregulated electricity market

The old England & Wales Pool was one of the pioneers for electricity industry deregu- lation in the world [2]. Uniform Marginal Price was implemented in this market as pricing scheme and congestion management method. Here the National Grid Company has two roles: transmission asset owner (TO) and Independent System Operator (ISO) [5] [6]. The ISO adopts the principle referred to as “re-dispatch first, compensate later” to manage transmission congestion which means it is a two stages operations [3]. In unconstrained dispatch stage, generation companies send generation bidding quantity and price of the following day to the ISO who already forecasted the power demand for each half hour period [1]. Then the ISO starts to accept bids from the cheapest price to higher price until the forecasted demand is satisfied. Then, the ISO sorts out a bid list which contains the generation companies who have been chosen to generate electricity. Those generation companies are called “in merit” generation companies and those who have not been accepted are called “out of merit” generation companies [2]. If there is no congestion violation, the unconstraint dispatch will be executed [5]. When trans- mission congestion occurs, it comes to the security-constrained stage and the ISO will re-dispatch the generation list, at the meantime ensuring the re-dispatch cost is the minimum. An inequality constraint will be added and the security re-dispatched is de- cided by the new algorithm. The congestion relief cost is the generation cost in secu- rity-constrained dispatch minus the generation cost in unconstrained dispatch. The congestion cost is allocated in equal proportional to each load while generators are not charged for transmission congestion [7].

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Sensitivity Based Analysis for Optimal Location of UPFC to Reduce Power Loss and Congestion in Deregulated Electricity Market

Sensitivity Based Analysis for Optimal Location of UPFC to Reduce Power Loss and Congestion in Deregulated Electricity Market

In this paper, the application of Unified power flow controller (UPFC) to relieve congestion has been studied. A sensitivity based analysis has been done for optimal location of UPFC in a deregulated environment. Results had been done on IEEE 5 bus system with and without UPFC to demonstrate the feasibility as well as effectiveness of UPFC to relieve congestion in a network using MATLAB. The results obtained after using UPFC to improve system reactive power losses and hence congestion management is improved.

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Congestion Management in Deregulated Electricity Market with Facts Devices using Firefly Algorithm

Congestion Management in Deregulated Electricity Market with Facts Devices using Firefly Algorithm

Abstract - The job of an self-governing system operator in a aggressive market atmosphere would be to make easy the total send off of the power that gets constricted among the market. With the development of an growing quantity of bilateral contracts being assigned for bazaar trades, the opportunity of inadequate property primary to group congestion may be inevitable. Real-time congestion in transmission line can be defined as the working situation in which present is not sufficient transmission potential to apply all the traded communication concurrently due to a number of unpredicted contingencies. Firefly algorithms is assigned to locate best solutions of piercing non-linear uninterrupted mathematical designs. Firefly Algorithm is solitary of the current elapsing designs which is encouraged by fireflies actions in environment. A sequence of elapsing experiments by every algorithm were studied. The outcome of this testing were understand and compared to the optimal solutions set up consequently far-off on the origin of signify of completing moment to join to the most favorable. The Firefly algorithm seems to execute superior for advanced mode of noise.

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Study on single buyer model and pool trading model in deregulated electricity market

Study on single buyer model and pool trading model in deregulated electricity market

This thesis is divided into six chapters. The first chapter is the overview of the project, problem statement, objectives of project, scope of project, and methodology. It followed by second chapter which is discuss about electricity supply industry restructuring which is include example of several countries that had implemented restructuring, structure of models electricity supply industry, and electricity trading arrangement that applied in each countries. Meanwhile, Chapter 3 describes situation for Malaysia Electricity Supply Industry (MESI) which is applied single buyer model. It consists of MESI planning towards restructuring and implemented single buyer in MESI. Other than that, an agreement between Independent Power Producers (IPP) and Tenaga Nasional Berhad (TNB) which is PPA have been discuss with their types of payment installed capacity for each generators in Peninsular Malaysia.

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Deregulated Electricity Market and Auctions: The Italian Case

Deregulated Electricity Market and Auctions: The Italian Case

The Italian Power Exchange was born as a consequence of Bersani’s law dated 16th march 1999; starting from the following year, customers had the possibility of stipulating bilateral contracts directly with freely selected providers. It was a deregulated market (over the counter); just after the year 2004 an Electricity Exchange has been created, it was committed to “Gestore del Mercato Elet- trico” (GME). The Italian System is mixed, such as many European systems, in which a key role is played by pub- lic companies and an independent control authority. The transmission activity which is operated by the Govern- ment and the distribution activity are guaranteed in au- thorization system. The production activity is free and is carried out in a competitive system.

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Locational Marginal Pricing Approach for a Deregulated Electricity Market

Locational Marginal Pricing Approach for a Deregulated Electricity Market

effective transmission pricing method is required to address transmission issues and to generate correct economic signals to reduce the generation cost. It is necessary to develop an appropriate pricing scheme that can provide the useful information to market users, such as generation companies, transmission companies and customers. These pricing depends on generator bids, load levels and transmission network constraints. Transmission line constraints can result in variations in energy prices throughout the network. The proposed approach is based on DC optimal power flow model with considering of losses. Resulting optimization problem is solved by Quadratic Programming [QP] approach. Locational Marginal Pricing methodology is used to determine the energy price for transacted power and to manage the network congestion and marginal losses. Variation of LMP values with transmission constraint conditions also studied. Simulation is carried out on IEEE 30 bus test system and the results are presented.

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Review Paper on Power Trading Model for Compe...

Review Paper on Power Trading Model for Compe...

S.N. Singh et.al [1] discussed about Power industry restructuring, around the world, has a strong impact on Asian power industry as well. Indian power industry restructuring with a limited level of competition, since 1991, has already been introduced at generation level by allowing participation of Independent Power Producers (IPPs). Chai Chompoo-inwai et.al [2] gives the information about the model of deregulated electricity market in Thiland. Transmission congestion management (TCM) plays a significant role in power-system operation under today‟s deregulated environment. Its two major functions are to maintain power system within security limits and to collect money from market participants paying back to transmission-grid investors. The TCM issue has been widely debated during the past decade. Although the PJM model is adopted in some developing countries where the processes of restructuring of Electricity Supply Industry is still under the beginning phase, many concerns, such as advances in an information technology, energy security, social equity, price volatility, and the need to subsidize poor consumers, are necessitate factors to be considered before the establishment of TCM and settlement processes. Taking into account the above concerns, this paper proposes a TCM model for the electrical utility industry in Thailand during the transition period to the deregulated environment.

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On modelling the electricity futures curve

On modelling the electricity futures curve

At this moment in time we are not able to store large quantities of electricity in an economically efficient way. The only fairly efficient storage possibilities are hydro storage basins, although the storage capacity is small compared to the aggregate demand of electricity. This lack of efficient storage possibilities leads to less flexibility in operating the electricity market since electricity must be produced at the same rate as consumed to avoid a network collapse. In electricity markets, sudden shocks in the demand or supply of electricity due to unscheduled plant outages, changing weather conditions or other unforeseen events can therefore not be balanced by stored electricity or by cutting consumption. Because of the unpredictable nature of the occurrence of these events, the delicate balance between supply and demand can suddenly be disturbed. Although there are some generation plants that can quickly ramp production up or down to balance supply with demand, it is far more (cost) efficient for most plants to operate on a fixed level instead of being switched on and off regularly. It is thus fair to say that the supply of electricity is inelastic to changes in demand, especially at peak levels. On the other side, electricity demand is price inelastic. Consumers don’t think about using electricity and because of the lack of real-time metering consumers cannot react to high prices by cutting consumption. Shocks to the system therefore have a large impact on electricity prices, especially on day-ahead spot markets (delivery of electricity the next day).

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Experimental study on electricity price forec...

Experimental study on electricity price forec...

In Ontario deregulated electric market, for those consumers paying wholesale price from a 24- hour operation wholesale electricity market, the wholesale price is set every 5 minutes. The process of electricity market clearing price determination starts by finding out electricity demand at the first place. Each day, the IESO issues forecasted electricity demand throughout the following day and up to the month ahead. This forecasted electricity demand also includes an energy reserve of approximately 1400 MW above what will actually be consumed. This extra 1400MW is on standby and reserved for emergency usage. The forecasted electricity demand is continually updated as new information comes in such as changes in weather. Typically, the day ahead forecasted electricity demands from IESO are highly accurate, with less than two percents variance from the actual demand figures. After the determination of electricity hourly demand, the next step is to start the electricity auction (electricity market bidding price).

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A Review of Price Forecasting Problem and Techniques in Deregulated Electricity Markets

A Review of Price Forecasting Problem and Techniques in Deregulated Electricity Markets

There has been great deal of research to understand electric power markets, and various methods for modeling, analyzing and selecting bidding strategies for power suppliers. Gaming theory is a natural platform for market competition [78]. It is of great interest to model the strategies of the market participants and identify solution to those games. Since participants in oligopolistic electricity markets shift their bidding curves in order to maximize their profits, these model provides the solution to these games and profit can be considered as the outcome of the power transaction game. In this group of models, equilibrium models [5], take the analysis of strategic market equilibrium as the key point. The gaming models are generally used by the market operators for deciding the market strategies. The detailed discussion on game theory can be found in [79]-[83].

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The Analysis of Spot Price Stochasticity in Deregulated Wholesale Electricity Markets

The Analysis of Spot Price Stochasticity in Deregulated Wholesale Electricity Markets

Spot prices typically exhibit patterns over three different lengths of time. Two of these, intra-day and intra-week patterns, are driven primarily by load, whereas annual patterns are driven by both load and supply. Load varies markedly, according to the time of day (i.e. peak or off-peak), the day of the week (i.e. weekday or weekend) and the time of year (i.e. the season – hot, cold or mild). The intra-day pattern is evident in a series of New Zealand spot prices over the course of a single day, illustrated in Figure 2.1 below, which shows the final half-hourly spot market prices for Thursday 26 June 2003 for the Haywards node in Wellington 5 . It has a clear morning peak, when people are waking up, turning on heating, showering and possibly cooking breakfast, a higher general level during the day on account of commercial activity increasing load, and an evening peak when people prepare their main meal and use other appliances. The difference in price behaviour on a weekday (when people rise early for work and require electricity for commercial activity) compared with a weekend is also understandable 6 .

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A investigative Study about Restructuring of Indian Power Market

A investigative Study about Restructuring of Indian Power Market

In the pre-independence time power sector consists of small private players to meet the local needs of the smaller area around them under the provision of Indian Electricity Act 1910. In 1947, the electricity industry in the UK was nationalized. India followed suit in 1948 and except for some pockets such as Mumbai, Kolkata, Ahmedabad and Surat. The entire industry was nationalized by virtue of the aforesaid Act of 1948, which laid down the structure of electricity industry in the independent India. This Act triggered the formation of State Electricity Boards (SEBs) to handle generation, transmission and distribution of electricity within the states. Subsequently central sector steeped in to support the National Load Dispatch Center (NLDC) is also planned to facilitate inter- regional transfer of power and for optimum scheduling and dispatch of electricity among the Regional Load Dispatch Centers (RLDCs). Given these various changes, the industry structure will be transformed from the current ‘single-buyer model’ to ‘multi- buyer model’. In a multi-buyer model, the distribution entities are totally autonomous in procuring and dispatching their supply. This model would lead to better operation and lower cost to the end consumers. On an overall basis, Electricity Act 2003 is comprehensive and provides for progressive development of a market-based regime in Indian power sector through competition. The benefits will, however, start reflecting after a period of 4-5 years. Over the past two decades a number of countries have restructured their electricity industry by significantly reducing the government’s role in the ownership and management of domestic electricity industries. It has seen as necessary conditions for increasing the efficiency of electric energy production and distribution, offering a lower price, higher quality and secured supply. The forces behind electric sector deregulation taking place worldwide are different in different countries.

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T r a ns m i s s i o n Ne t w o r kC o ng e s t i o n i n D e r e g ul a t e d W ho l e s a l eE l e ct r i ci t yM a r k e t

T r a ns m i s s i o n Ne t w o r kC o ng e s t i o n i n D e r e g ul a t e d W ho l e s a l eE l e ct r i ci t yM a r k e t

In almost every areas of technology, privatization has al- ways made a positive impact on the performance of the industry. In 1989, UK became one of the pioneer coun- try to unbundle their electricity industry [4]. After the success of deregulation in the UK, most of the countries of Europe have started to unbundle their vertically inte- grated utilities. The successes of these countries have en- couraged the other countries to privatize their electricity industry which includes Finland, Australia, New Zealand, Taiwan and Brazil. In India the unbundling procedure has been carried out by most of the states and there ex- ist a state regulatory commission in all states who has opted for deregulation of electricity industry. The devel- opment of electricity market in India is still at nascent stage.

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Management of Congestion in the Deregulated Energy Market

Management of Congestion in the Deregulated Energy Market

……………………………..8 Network Congestion Management Using TCSC Approach In recent years, deregulation of electric industry in the world has created competitive markets to trade electricity. For deregulated transmission network, one of the major consequences of the non-discriminatory open access requirement is substantial increase of power transfers. Congestion management of deregulated transmission network is important to accomplish non discriminative network access. In this example congestion management approach using TCSC is demonstrated considering a 5 bus system. This approach aims at maximization of transmission margin without changing contracted power. In this approach TCSC modelled as a variable reactance is used. In order to check the validity of the proposed method of congestion management, numerical results for a 5-bus system are shown in Figures 4 and 5.

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The State of the US Energy Sector

The State of the US Energy Sector

Some coal power plants that have already paid off their capital costs can produce electricity competitively with natural gas. However, as the plants age they often require major capital spending, which can trigger the New Source Review provision 17 of the Clean Power Plan (CPP). The review

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Pricing Structures in the Deregulated UK Electricity Market

Pricing Structures in the Deregulated UK Electricity Market

After allowing for all these differences the unit charge for prepayment customers is higher, and does not fall so quickly if standing charge increases as for the credit tariffs. This may partly reflect the higher supply costs of prepayment, through handling cash. But it is also probably a reflection of the more recent regulation of these tariffs. As the final price controls are removed from retail electricity tariffs, these results raise important issues for future regulation of the market under the provisions of the Competition Act 1998. The regulator needs to monitor both the mark ups which incumbents are able to charge, and the trend of this price differential over time, as well as how active consumers are in switching. Incumbent mark ups may be a disequilibrium sign of vigorous discounting by entrants, and their absence, as in the prepayment market, may indicate only lackadaisical rather than enthusiastic competition. However continuation of incumbent mark ups in equilibrium would raise two sets of concerns. First, If the market does not erode such price differentials it suggests that incumbents are able to abuse market power. Secondly, if particular groups of consumers are less likely to switch away from incumbents charging higher prices, it raises distributive concerns. This will be of particular concern to the regulator and the consumer watchdog, both of whom have statutory duties to take account of the needs of certain potentially vulnerable categories of households. The different market structures also suggest that the regulator needs to continue separate monitoring of the prepayment market, where tariffs show very different characteristics from those in credit markets, and whose consumers have lower than average income.

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Carbon Tax and Renewable Energy Diffusion in the Deregulated Texas Electricity Market: An Agent Based Analysis

Carbon Tax and Renewable Energy Diffusion in the Deregulated Texas Electricity Market: An Agent Based Analysis

We analyze the installation of RE-based electricity capacity power in the presence of a tax on carbon dioxide emissions. The power generators are treated as the major point source of carbon dioxide emissions and any fines or taxes on carbon output are levied at that level. However, it is assumed that all taxes levied on the PGC entity are fully passed through to the consumers and are reflected in increased electricity prices. Monte Carlo simula- tions are run on multiples of $5 in the range $5 - $25 per metric ton of carbon dioxide emitted, as a proper car- bon tax range suggested by Parry and Pizer [13]. The basic effect of this tax is that it shifts the transition towards cleaner fuels forward as it adds to the cost of the fossil fuels, essentially incentivizing the purchasing of renewa- ble energy. However, this has no effect on the exogenously defined percentage of the population who is instal- ling their own rooftop PV systems and they continue installing PV in accordance with their RE preference. Therefore, the residential RE market continues to grow very similarly to the BAU case for all levels of carbon taxation (Figure 4). In raising the fossil fuel end-use price, the carbon tax makes the usage of RE more finan- cially viable. Therefore, as can be seen in Figure 5, the tax of just $5 per metric ton of carbon emitted actually encourages electricity consumers to begin purchasing RE from the RE power 3 full years earlier than in the base case.

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