Deregulated Electricity Markets

En este capítulo se identifican los componentes esenciales de la política de reorganización del sector eléctrico, como desenlace de la instrumentalización de la política neoliberal practicada desde la década de 1980. Se trata, según el autor, de un rediseño del Estado y del capitalismo mexicano, así como de la coherencia productiva y simbólica de la empresa pública, en los que se combinan exigencias de un mejor servicio y de la calidad/costo y satisfacción/cliente.

One of the major challenges in deregulated power system is determination of Available Transfer
Capability on the interconnected transmission lines. It is necessary to determine and accurately gauge the transfer
capability remaining in the lines for further transactions, ATC determination methodology that enables one to
evaluate the realistic transmission transfer capability by accounting for all related important requirements. The
assessment of ATC gives valuable information to the system operator regarding the ability of an interconnected
network to reliably transfer bulk power between two nodes or between different areas of the network without
causing threat to system reliability. There are several methods to find ATC in deregulated system. The proposed
computation of the ATC using AC power transfer distribution factors (ACPTDFs) and to determine the shortest path
for the power flow between buyer and seller which is implemented by shortest path algorithm were discussed. ATC
calculation of IEEE-5 bus have been simulated by using Power world simulator and the results have been
presented by considering PTDF/OTDF factor and shortest path between buyer and seller is determined by
considering the line impedance as parameter simulation is carried out using MATLAB

Congestion management is a common issue in power system and becomes more challenging task in
competitive electricity market. Power lines are often loaded beyond their thermal limits in order to satisfy the
increased demand. With increase in demand the unplanned power exchange takes place between producers and
consumers. In the deregulated electricity market, Independent System Operator (ISO) is the one responsible for
keeping track of various transactions taking place between various entities. The ISO is an entity entrusted with the
responsible of ensuring the reliability and security of the entire system. Therefore Congestion Management and
Demand Side Response are very necessary in this context. The economical benefit comes from reducing the line
losses. This is because the energy usually has to travel a considerable distance from power plants to customers.
These two concepts contribute in relieving heavily loaded lines and reducing losses. Demand Side Management
(DSM) provides an excellent reliability resource for the most critical reliability needs. The graph theory shortest
path algorithm finds more suitable to identifying the shortest path power flow and determination of Available
Transfer Capacity (ATC) in the lines avoids unnecessary loading the lines to avoid the congestion in the power
network.

En la presente entrevista, el interlocutor analiza, de forma general, cuáles son los problemas que su-pone la reforma del Estado, fundamentalmente en tres áreas importantes: reforma del servicio civil, del sistema de contrataciones del Estado, y promo-ción de la inversión privada. De esta manera, el interlocutor critica la manera en la que se han llevado a cabo reformas en ciertas áreas; señala cuáles son, según su consideración, los aciertos de algunas reformas; y esboza pro-puestas de solución para el camino que aún falta por recorrer para la modernización del Estado. Palabras clave: Derecho Administrativo; reforma del Estado; contrataciones del Estado; servicio civil; inversión privada. In this interview, the interlocutor analyzes, in general terms, which are the issues that the government reform involves, mainly in three important fields: civil service reform, public contracting system reform, and promotion of the private investment. Thus, the interlocutor criticizes the way the...

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.

Power supply has been one of the key public utility industries in Hong Kong, as protected by official franchise granted by the government for regulating and controlling entry. It is the purpose of this paper to explore and investigate how the impending advents of 'market de-regulation' have affected people management and employee perception within two monopolistic power plants in Hong Kong. The authors have postulated and illustrated empirically the strategic role played by enhanced activities of human resource management and employment practices in the process of corporate renewal in face of the challenge of escalated business competition in the power supply market.

Climate-related power outages have increasingly compromised the lives and well-being of medically vulnerable populations. For the millions reliant on electricity for home medical equipment, even short-term power outages can lead to a potentially life-threatening situation. Society’s most vulnerable populations— elders, the ill, and the poor—face the greatest risks. Yet, technologies that provide backup energy in the face of power outages are limited and existing resources are often inaccessible outside of healthcare settings and mostly do not directly reach low-income populations. With the increasing prevalence of climate-related events that induce power outages such as hurricanes, wildfires and windstorms, there is an imminent need to increase access to backup power, for both residences and critical community facilities. This paper sheds light on the increasingly relevant problem of power outages and offers a view toward a socio-technically-based solution to protect vulnerable populations and improve health outcomes in the event of an outage. It provides a comprehensive overview of the impacts of power outages on electricity-dependent populations by highlighting existing research on affected populations, describing the gaps in the field, and featuring two case studies in Puerto Rico and California that provide preliminary evidence for the potential uses of resilient power resources. Resilient power systems-- battery storage ideally paired with solar photovoltaics-- can provide clean, reliable emergency backup power by storing electricity for use when grid power is unavailable. Backup power can mitigate the adverse health impacts of power outages on electricity-dependent populations, many of whom are medically and socioeconomically vulnerable. We describe a future of energy that is resilient and just, by presenting the possibility for access to clean energy technologies that can support healthcare that is home-based and features multiple co-benefits in light of climate change. With additional evidence, policies, incentives, and market designs in place, resilient power technologies can serve all populations in need of reliable and resilient access to electricity in the near future.

This work, focused on an idea about hybrid solar car technology which solves the major problem of fuel and pollution in present days. Determine how feasible widespread change to hybrids would be in future with all information taken into account, concluded that hybrids have several advantages as fuel efficient, low pollution. In the present work a complete drawing and drafting of hybrid solar car have been prepared using CATIA V5R19 software. After complete analysis of this drawing by using ANSYS 14.5 it is find out bear capability of load, stress, and strain of front & rear collision of car frame. A completed data are analyzed to examine the technical aspects of the hybrid car technology. Overall, hybrid technology has a lot of potential in the distant future, but as for right now they are not a significant applied over today's internal combustion engine.

This paper proposes an Enhanced Particle Swarm Optimization (EPSO) approach to the Unit Commitment Problem (UCP). The Binary Particle Swarm Optimization (BPSO) algorithm for on/off decision and the Classical Particle Swarm Optimization (PSO) algorithm for the economic load dispatch problem are enhanced to find the optimal solution and reduce the overall computation time. The proposed technique is tested on 10 to 100 unit systems with a 24-h scheduling horizon. The results of the EPSO on the benchmark datasets are comparable with the results of other heuristic approaches found in the literature. This preliminary experimental study shows that EPSO is suitable for the UCP and the promising results promote further study.

This paper presents several applications of Wien Automatic System Planning (WASP) tool to address specific modeling challenges encountered in power system expansion planning problems. Although WASP has been used by power system planners around the world for many decades, its standard formulation does not allow the user to explicitly model many situations that can occur in realistic power systems. Examples of such situations include dual-fuel plants, options for electricity exports, energy exchange agreements with neighboring systems, and considering large generating units as candidates in relatively small-size systems. A number of alternative modeling solutions are proposed in the paper based on the authors' long-term experience in carrying out generation expansion studies for electricity systems of various types and sizes. These solutions demonstrate the flexibility of using WASP to model atypical features of power systems.

The scarcity of fossil fuels used in automobiles is currently a crisis. Furthermore, CO2 emissions have a significant detrime ntal influence on the environment. As a result, developing a sustainable energy system has become a major concern that has attracted a lot of attention. For daily consumption, the modern world requires enormous amounts of energy, resulting in exhaustion energy resources that aren't renewable. As a result, using renewable energy resources in the production of energy is a good idea. In today's world, the most significant difficulty is the proposed concept is t o generate electricity by exploiting the natural resources around us. The car's motion produces opposing wind forces. This study focuses on the design of a wind turbine that will be mounted on an electric vehicle and used to generate electricity to charge the vehicle's batteries while it is in motion. Because of the car's aerodynamic nature, the turbine is mounted on the roof near the windscreen, where the air velocity flowing around it, is highest. When the car starts moving, it produces an air current.

The augment of ecological shield and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating renewable energy sources into existing power system. Wind power is becoming worldwide a significant component of the power generation portfolio. Profuse literature have been reported for the thermal Unit Commitment (UC) solution. In this work, the UC problem has been formulated by integrating wind power generators along with thermal power system. The Wind Generator Integrated UC (WGIUC) problem is more complex in nature, that necessitates a promising optimization tool. Hence, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm has been chosen as the main optimization tool and real coded scheme has been incorporated to handle the operational constraints. The standard test systems are used to validate the potential of the GWO algorithm. Moreover, the ramp rate limits are also included in the mathematical WGIUC for...

A robust trading system is vital to promote competition in the Indian electricity market. In India, the exchange trading market is still at an incipient stage, despite being the best option for innovation, due to the presence of high volatility huge losses are incurred by the power market participants such as power generators and distribution companies. Hence, a descriptive research was conducted to identify the major factors leading to the periods of spikes and jumps in the Indian energy exchange's day-ahead market (DAM) prices of all the regions (north, south, east, west and north east) from August 2008 until June 2017. It was found that the major factors affecting DAMs prices are regulatory, weather, fuel supply, transmission congestion; power plant outages/new plants operational, frequency and reservoir levels. This study will encourage the stakeholders to further model and forecast prices devising profit maximisation techniques thereon.

In an electricity market generating companies and large consumers need suitable bidding models to maximize their profits. Therefore, each supplier and large consumer will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. In this paper, bidding strategy problem is modeled as an optimization problem and solved using a novel algorithm based on social behavior PSO. PSO is an optimization algorithm inspired on fish schooling. Therefore the proposed method overcomes the short comings of selection of operators and premature convergence of other optimization techniques like Genetic Algorithm (GA). The proposed method tested with numerical examples, and its results compared with other existing methods. The result shows that PSO gives better results and takes less computational time and producing higher profits.

The worldwide electricity industry is in an era where an overwhelming transition towards deregulation is taking place. Since its start in the early 1980s, the industry has been in a continuous change to a different atmosphere; the ultimate benefit being providing the enduse customer with a reliable but yet cheaper electricity supply. In the old monopolistic system, utilities were the only authoritative body to set the tariff based on their aggregate cost. In the contrary, as a newly emerging structure, deregulation has come-up with a new way of functioning; leading generation, transmission and distribution to be independent activities. This market is generally a customer driven market and since the early days of deregulation, price forecasting has become an important task to all the market players engaged. Unless each body is fairly aware of the market, it might result in losses to a generating company or inadequate supply to the system; resulting in a huge crisis. Hence, understanding the market behavior is of vital importance for the well-functioning of the industry and the benefit of each party. This thesis addresses the importance of electricity price forecasting in the deregulated market. After a comprehensive review of previous works in the subject, it is concluded that forecast accuracy varies depending on the forecast method used and the electricity market under study. In this thesis multiple linear regression approach are proposed to predict next day's electricity prices. The developed models are tested in the Nord Pool and the Ontario electricity markets and satisfactory results are achieved. Comparing the forecast results from the two markets, results in the Nord Pool market are significantly more accurate than the Ontario market. This arises from the fact that Ontario market is very volatile and its market prices are hardly predictable. The forecast results in this thesis work show that the proposed models perform very well with the absence of volatility. For instance, the developed models for the first week of December 2007 generated results with weekly Mean Absolute Percentage Error (MAPE) of about 5.04%. In early spring even better results are achieved where the models generated results with a daily MAPE of up to as low as 1.83% and weekly MAPE of about 2.96%. On the other hand, during summer where prices vary considerably even between hours of the same day, the models generated a relatively poor forecast. A day with a price of as low as 2.96 EURO/MWh to as high as 23.52 EURO/MWh is observed and this price fluctuation contributed for poor forecast. For instance, the models generated forecasts with a weekly MAPE of about 13% for the period from August 29 to Sept. 4, 2007. For the Ontario market, these models generated forecast results with a weekly MAPE of about 17%. The issue of strategic bidding is also discussed in this thesis. Once the next day electricity price is forecasted, generating companies schedule their production based on the forecasted electricity price and bid strategically in order to maximizing their profit. An analysis on the correlation between reservoir level and market clearing price is also carried out. Taking the Nord Pool market as a case study, it is found out that during winter there is a strong positive correlation between the two; showing system price increasing with reservoir level and vice versa. However, for other periods of the year a logical negative correlation is observed; price goes down with an increase in reservoir level and vice versa. v Forecasting Spot Electricity Market Prices Using Time Series Models ____________________________________________________________________________________ Acknowledgments During the course of my studies, many colleagues and friends have contributed greatly and I would like to take this opportunity to thank them all. First and foremost, I would like to express my deepest appreciation and thank to my supervisor Dr. Tuan A. Le for his invaluable support and continuous supervision in this thesis work. I also would like to acknowledge the Swedish Institute and SIDA for the MKP scholarship, which I was receiving during my study period. My sincere thank also goes to the Nord Pool staff for allowing me to have access to their data base. Finally, I am grateful to my friend Mebtu for his invaluable help in this work and also all my friends and personnel at Chalmers University of Technology for the knowledge and priceless lessons that I have gained during those days. This thesis is dedicated to Queen, with Love; your support and courage have been wonderful in all those days! vi Forecasting Spot Electricity Market Prices Using Time Series Models

A robust trading system is vital to promote competition in the Indian electricity market. In India, the exchange trading market is still at an incipient stage, despite being the best option for innovation, due to the presence of high volatility huge losses are incurred by the power market participants such as power generators and distribution companies. Hence, a descriptive research was conducted to identify the major factors leading to the periods of spikes and jumps in the Indian energy exchange's day-ahead market (DAM) prices of all the regions (north, south, east, west and north east) from August 2008 until June 2017. It was found that the major factors affecting DAMs prices are regulatory, weather, fuel supply, transmission congestion; power plant outages/new plants operational, frequency and reservoir levels. This study will encourage the stakeholders to further model and forecast prices devising profit maximisation techniques thereon.

Electric energy market is to increase their profit for electricity providers (generators) in an open competitive electricity market and reduce reduced consumer costs by taking into account available power supply, power demand, market clearing prices (MCP) and constraints. The main contribution of this paper is provided more benefit for supplier and this new technique has used overcome the problem of electricity bidding. It may be highly important to manage the market of electricity as per the fair rules. In this paper, PSO and APSO are used to solve the bidding problem. PSO and APSO have many characteristics that similar to Genetic Algorithm (GA) evolutionary computational strategies. Firstly, by integrating the random solution and updating the generation, we get optimal results in the problem space. The possible solutions known as particles are flowing in every direction through the problem area in the PSO, following the optimal current (particle) solution. APSO is recommended for ...

The augment of ecological shield and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating renewable energy sources into existing power system. Wind power is becoming worldwide a significant component of the power generation portfolio. Profuse literature have been reported for the thermal Unit Commitment (UC) solution. In this work, the UC problem has been formulated by integrating wind power generators along with thermal power system. The Wind Generator Integrated UC (WGIUC) problem is more complex in nature, that necessitates a promising optimization tool. Hence, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm has been chosen as the main optimization tool and real coded scheme has been incorporated to handle the operational constraints. The standard test systems are used to validate the potential of the GWO algorithm. Moreover, the ramp rate limits are also included in the mathematical WGIUC for...

El proposito central del presente trabajo es mostrar, de forma generica, las posibilidades reales de la reforma electrica en nuestro pais, a partir de las coincidencias presentes en las diversas iniciativas de ley por discutirse en el Congreso de la Union, en los periodos ordinarios de sesiones de los proximos dos anos que le quedan a la actual legislatura. Con base en su analisis, todo parece indicar que la reforma en ciernes abrira las puertas para la creacion de un mercado electrico para grandes usuarios (calificados) y seguira bajo la rectoria del Estado para los pequenos usuarios (usuarios finales). La discusion y aprobacion de la reforma son impostergables. La experiencia internacional confirma que cuando han faltado los energeticos, el impacto negativo en la economia ha sido brutal.

The analysis of the electricity sector in Southeast Europe shows that hydropower and coal represent the most important energy sources for electricity generation. Hydropower provides a necessary flexibility and storage capacity to help ensure stability of a transmission system and security of supply and supports the integration of increasing amounts of renewables, especially wind. Coal has a high share in total installed capacity in most countries and it will put high pressures on these countries in the context of undergoing changes and decarbonisation in electricity sector of European Union and Energy Community. Obviously, the electricity sector will face huge changes and is expected to contribute to the new energy revolution. However, during the 90s, the electricity sector of SEE countries changed dramatically. Generation and industrial demand have decreased considerably due to the wars and painful transition, while the household demand increased rapidly. This extensive use of elec...

Solar energy has great importance since it is clean, reliable and renewable. Solar-powered cars enable the car to start with the solar energy by transforming the energy, which they receive from the sun, into the electrical energy by means of photovoltaic panels and giving that energy to the engine. In this study, a solar-powered vehicle was designed and its prototype was built. Apart from the design of the solar-powered vehicle, the materials used, its manufacture and driving performance were researched by doing tests.

Electricity markets are open after the deregulation of power systems due to competition. An optimization problem based on dynamic economic dispatch has recently come up in the new context of deregulated power systems known as bid-based dynamic economic dispatch (BBDED). It is one of the major operations and control functions in the electricity markets used to determine the optimal operations of market participants with scheduled load demands during a specified period. BBDED involves power generation companies (GENCOs) and customers to submit energy and price bids to the independent system operator (ISO) in a day-ahead market. The ISO clears the market with the objective of social profit maximization. In this paper, a BBDED problem is solved using an improved simulated annealing algorithm (ISA), including system constraints with different periods under bidding strategies. The proposed ISA technique is implemented in MATLAB and applied on a 3-unit system, a 6-unit system, and a 40-uni...

In an open competitive electricity market generators (supplier) and large consumer (buyer) need a suitable bidding model for enhancing their profits. Therefore, each generators (supplier) and large consumer (buyer) will bid strategically for the selection of bidding coefficients to check out the rivals bidding strategy. In this paper, bidding strategy problem is treated as an optimization problem and solved using Particle Swarm Optimization (PSO) and Adaptive Particle Swarm Optimization (APSO). PSO and APSO possess many similar characteristic with evolutionary computation techniques such as Genetic Algorithm (GA). First we have initialized The system with a population of random solutions and searches for optimal result in problem space by updating generation. In PSO, the potential solutions, known as particles, fly through the problem space in all direction by following the current optimum solution (particle). APSO is proposed to improve the performance of PSO (i.e. weight update technique is different in APSO and weight vary according to performance of particle). A numerical problem with six Generator (suppliers) and two large consumers (buyer) is used to describe the essential features of the proposed method. The results indicate that the APSO is better than PSO with respect to total profit.

In today's era of growing digital technology, different e-commerce websites compete with each other by providing new products and adopting various strategies to attract customers, because customers are the main asset of any business organization, specifically the e-commerce sites. To attract customers and making them by the goods, organizations try to understand the preferences and analyze the buying behavior of customers. Considering the above fact, this paper focuses on the strategies of organization to attract the consumers by gathering the information about customer, past purchase history and analyze the customer's behavior towards the purchase of products using sentiment analysis.

The augment of ecological shield and the progressive exhaustion of traditional fossil energy sources have increased the interests in integrating renewable energy sources into existing power system. Wind power is becoming worldwide a significant component of the power generation portfolio. Profuse literature have been reported for the thermal Unit Commitment (UC) solution. In this work, the UC problem has been formulated by integrating wind power generators along with thermal power system. The Wind Generator Integrated UC (WGIUC) problem is more complex in nature, that necessitates a promising optimization tool. Hence, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm has been chosen as the main optimization tool and real coded scheme has been incorporated to handle the operational constraints. The standard test systems are used to validate the potential of the GWO algorithm. Moreover, the ramp rate limits are also included in the mathematical WGIUC for...

The ongoing restructuring of the electric utility industry has many implications for electricity economics and the mix of generating resources holding both promise and peril.  The authors make the case for a hybrid system of market mechanisms and policy safety nets.

In today's era of growing digital technology, different e-commerce websites compete with each other by providing new products and adopting various strategies to attract customers, because customers are the main asset of any business organization, specifically the e-commerce sites. To attract customers and making them by the goods, organizations try to understand the preferences and analyze the buying behavior of customers. Considering the above fact, this paper focuses on the strategies of organization to attract the consumers by gathering the information about customer, past purchase history and analyze the customer's behavior towards the purchase of products using sentiment analysis. keywords-E-commerce, Customer behavior, Sentiment analysis, Organization strategies. _____________________________________________________________________________________________________ I. INTRODUCTION E-commerce means a network where various products stored virtually for online buying and selling purpose of goods and services and payment is possible through credit and debit cards, net banking and cash on delivery time. E-commerce provide various benefits to organization like fast online service, information of market behavior and customer interest and provide benefits to customers are variety of same type of products, reasonable cost, good services and secure transaction and quick delivery. But there are many e-commerce web sites are present that is meant for online shopping, so to increase the growth of an organization and to sustain in market, organization must have to understand the preferences and analyze the behavior of customers. Considering the statistics report, in today's generation, online purchase decision has the growing importance. Like, in 2016 it is increased by 20%, in 2017, 18% increment globally in B2C and now a days 10% increment in retailing. E-commerce consists of both youngster and middle age customers but an immense increment shown in older consumers like 50 years old and older than that for buying goods and services online ([1], [2], [3]).

The European Commission’s Target Model’s main objective is to integrate European electricity markets, leading to a single internal energy market and guaranteeing the instantaneous balance between electricity generation and demand. According to the target model for electricity trading, proposed by the European Network Transmission System Operators for Electricity (ENTSO-E), within each zone, electricity can be traded freely without taking into consideration network limitations. In contrast, for cross-border trading, the exchanges with other market areas are taken into account. Cross-border trade poses a further burden on the interconnection lines, resulting in increasing network congestion, which in turn restricts electricity trading. Thus, calculating the available capacity for trade has a significant ramification on the market. Today, the Available Transfer Capacity (ATC) mechanism dominates cross-border trading, but this methodology may be replaced by the Flow-Based (FB) approach ...

In the perspective of the emerging Smart grid concept, the future distribution network requires repeated and fast load flow solutions. This is helpful in distribution planning, automation, optimization and restoration. This paper presents an approach using graph theory to determine optimal path for power flow in the distribution network. Distribution automation is an essential part of development of an effective smart distribution system. The distribution network is modeled involving distributed generation. An attention is paid to the techniques that deal with balanced/unbalanced, radial/ meshed configuration, with and without Distributed Generation (DG). The method is tested on IEEE 5 and 14 bus systems to find the shortest path for the power flow with MATLAB graph theory function. The results obtained indicate the proposed method as yet another approach to find the optimal path for power flow in distribution network.

Due to the problems caused by the gasoline engine on the environment and people, the automotive industry has turned to the electrical powered vehicle. This report explains how an electric vehicle works and compares the electric vehicle to the internal combustion engine and hybrid vehicle. The report provides some of the advantages and disadvantages of the electric vehicle. At a time when the fuel prices are rocketing sky high , the daily running cost of a vehicle and its cost of ownership are hitting the roof and there is a dire need to protect our environment , alternative means of transport are few. Electric vehicle are slow expensive with limited range the solution comes in the form of electrical vehicle .

Electric energy is an essential resource in today's life. So we are try to solving Challenge ROADEF/EURO 2010: A large-scale energy management problem with varied constraints. No matter if we make our first cup of coffee or tea in the morning or run a multi-million euro business, all the time we rely on a secure and inexpensive supply of electricity. Our goal is to full the respective demand of energy over a time horizon of several years, with respect to the total operating cost of all machinery. Determining optimal maintenance schedules and production plans is not easy because of the number of alternatives to assess. As the exact electricity demand of each forthcoming day is unknown and depends on a large variety of factors, this leads to the need of multiple uncertainty scenarios. Additionally, the increasing proportion of renewable energies in today's energy mix makes things more complicated for an utility company, because it has to feed the energy of thirdparty solar or ...

In a Day Ahead Electricity Market (DAEM) the power suppliers need to adopt adequate bidding procedures to maximize their individual profits. So each Genco participating in the market has to bid strategically i.e. choose its own bidding coefficients so as to win the auction at any particular hour among the rival Gencos of the market. In this paper a very recent and robust bio inspired technique named Grey Wolf Optimization (GWO) is used to determine the optimal bidding parameters. The strength of GWO lies in the fact that it converges very fast compared to all such methods developed so far and also found to be very efficient in providing a better optimal biding strategy as evidenced by the statistical analysis report provided. This method is applied to IEEE 30 Bus system with 6 no of Gencos and an Indian 75-bus practical system with 15 no of Gencos and is verified by mathematical modeling through MATLAB simulation. It was evidenced by the output that the proposed method results in mu...

Highlights • The introduction of explicit demand response (DR) in the electricity markets for energy, capacity and ancillary services requires a definition of the customer baseline load (CBL). Such counterfactual – that is, what the customer would consume in the absence of demand response – is necessary to measure the effective performance of a demand resource and to properly compensate the DR provider.

The book presents the results of a study of the development of Bulgarian electric power industry during the last two decades, applying the actor-network theory and pathdependency approach. The methodology included in depth interviews with experts-...

Hong Kong has resisted the global trend toward electricity market restructuring and deregulation, and maintains two vertically integrated utility monopolies. However, the regulated market achieves impressive performances with relatively low tariffs, rare electricity disruptions, and quick service restoration following outages. This research examines electricity reliability and resilience in the context of Typhoon Mangkhut in September 2018, with a particular focus on how the regulatory framework of the Scheme of Control Agreement (SCA) shapes planning, operating, and investing decisions. The SCA quantitively establishes financial incentives for utilities to achieve high-quality service and guard against potential political influence on utility decision-making.

In our ecosystem mostly Gasoline engine cars are used by the public which have high cost of refueling that cause
emission of greenhouse gases. In this way to reduce the automotive emission which causes the Greenhouse gases, an alternative
technology is needed. The most convenient way is to use renewable energy sources. In this scenario we provide an alternative
fuel for vehicles by using renewable energy resources. Among the various resources available, we design a solar power
controlled motor device for automotive application.
In this project, the Electric Car is the way to alter the energy source. Sunlight is the main source of energy to obtain light energy
which is converted into electricity. Amount of energy obtained from the source may vary from time-to-time. The vehicle chosen
for the experiment is Marathi Omni. The solar panels are placed on the top of the car. Energy obtained from the solar panel is
given to the charge controller. Charge controller can prevent overcharging and also the over discharging of the battery. Output
of the charge controller is given to the Valve Regulated Sealed Lead-Acid Battery. Then the Valve Regulated Sealed Lead-Acid
Battery is given to the Motor through Driver circuit which controls speed of the Motor.
Battery charging time through charge controller is four to five hours and the Electric Car travels for the distance of about
150Km with the speed of 30 to 40 Km/hr. Thus the proposed system of automotive vehicle helps to achieve zero pollution, zero
noise effect and fuel consumption

Supply chain is a widely discussed topic in the last decades. The Just-in-Time concept in manufacturing was a massive success towards the end of the millennium. The Just-In-Time delivery has become a crucial indicator of a company’s competitive advantage. Whilst Supply Chain is an integral part of logistics, this paper systematically reviews the fundamentals of supply chain including the definition and difference between a value chain and a supply chain in an academic context, including some key supply chain management principles.

In deregulated electricity markets, generation companies (GENCOs) make unit commitment (UC) decisions based on a profit maximization objective in what is termed profit based unit commitment (PBUC). PBUC is done for the GENCO's demand which is a summation of its bilateral demand and allocations from the spot energy market. While the bilateral demand is known, allocations from the spot energy market depend on the GENCO's bidding strategy. A GENCO thus requires an optimal bidding strategy (OBS) which when combined with a PBUC approach would maximize operating profits. In this paper, a solution of the combined OBS-PBUC problem is presented. An evolutionary particle swarm optimization (EPSO) algorithm is implemented for solving the optimization problem. Simulation results carried out for a test power system with GENCOs of differing market strengths show that the optimal bidding strategy depends on the GENCO's market power. Larger GENCOs with significant market power would typically bid higher to raise market clearing prices while smaller GEN-COs would typically bid lower to capture a larger portion of the spot market demand. It is also illustrated that the proposed EPSO algorithm has a better performance in terms of solution quality than the classical PSO algorithm.

Smart grid technology make end users to participate in the electricity market possible. Recently, the Singapore government has change the rule for participation in the wholesale market. The Smart Community project, develop by NTU, DNV GL and Green Koncepts, will look into critical factors for retail consumer to participate in the demand responses (DR) programs and time of use pricing. For example: (1) review benefit for current retail consumer, (2) review the impact of real-time energy consumption data to the users, (3) review the impact of user experience-focus application toward smart grid participation program. The DR program will allow the users to become an active participant in the energy market. For the government, it allows better planning on the limited and costly energy resources, improved system reliability, reduce transmission and distribution congestion, check and balance on the market power generation. A mobile based user-experience focus application will be developed for consumers to actively participate in the demand-side management program, which make Singapore Energy Market more flexible.

Clustering is a ubiquitous technique in machine learning. Clustering is useful when we do not have
labeled data. In the present study, three of the most useful and easy to implement clustering algorithms, namely kmeans

method, greedy-k-means method, and in the last but not the least is improved-k-means method have been
studied. A study on the behavior of k-means clustering technique is being presented here. Next, we present
discussion on two improved versions of k-means algorithm – in the first version, a greedy method is being applied
to overcome some of the limitation whereas in the second version, using some pre-computation, we can improve
the traditional k-means to some extent. While comparing the greedy version to the original to the original k-means
method, our execution results suggests that the clustering quality of greedy version is better than original, but not
more than that. We are not sure yet whether the size of the input dataset affects the clustering quality of the greedy
version. We found that, among these three algorithms, the original k-means more-or-less performs best. While
comparing the improved version to the original k-means method; the original version performs better than the
improved version in most cases. For k <= 15, the improved version performs better. But as k > 15, the original
version outperforms the improved version.

In the perspective of the emerging smart grid concept, the future distribution networks involves the distributed generations. In vertically integrated system the operator was responsible for the system in balance, to ensure that the production and imports continuously match the consumption and exports. Distribution system planning with distributed generation work perfect with future grid. Thus system has to undergo a process of transition and restructuring to provide low cost electricity to everyone. The restructuring process involves separation of transmission activity by generation activity, by introducing competition in generation activity through creation of power pool in spot electricity market. Efficient management of networks required a shortest route power flow from one point to another. It is often necessary to determine alternative routes through the network in deregulated electricity market. The aim of this work is to apply Dijkstra’s Algorithm to determine the optimal path for power flow in deregulated environment.

Derivado de la Reforma Energética reflejada en la modificación a los artículos 25, 27 y 28 Constitucionales publicada en el Diario Oficial de la Federación el 20 de diciembre de 2013, se crea un nuevo paradigma en la integración de la Administración Pública Federal, consistente en la transformación de dos organismos descentralizados integrantes de la Administración Pública Paraestatal; en un nuevo ente denominado "empresa productiva del estado". Dicha transformación se tradujo en la consecuente reforma de diversos ordenamientos, impactando en la estructura convencional que hasta entonces tenía la Administración Pública Federal que regía en nuestro estado de derecho. Lo anterior, dado que las empresas productivas del estado adquieren un nuevo sistema cuyo objetivo es la menor regulación con la finalidad de generar valor económico. Para ello, se parte de la figura denominada Gobierno Corporativo, el cual, según la OCDE constituye un "elemento clave para la eficacia económica" …y "contribuye a generar el grado de confianza necesario para el funcionamiento correcto de una economía de mercado". Dicha reforma adquiere relevancia, dado que las empresas productivas del estado tendrán un marco jurídico flexible, lo que les permitirá aplicar el derecho privado, implicación que se verá reflejada en la naturaleza jurídica de los contratos de adquisiciones, arrendamientos, servicios y obras que celebren. En ese orden de ideas, el presente trabajo abordará dos vertientes derivadas de esta reforma constitucional: 1.-El establecimiento de una nueva forma de organización dentro de la Administración Pública Federal, y 2.-El sistema mixto en la contratación de adquisiciones, arrendamientos, servicios y obras ciñéndose a de Petróleos Mexicanos. Finalmente, derivado de la reciente transformación de Petróleos Mexicanos a empresa productiva del Estado, las referencias doctrinales aún están en construcción.

The present competitive world is witnessing tremendous change in technology and its applications to the needs of mankind. The booming wireless technology IoT (Internet of Things) has captured the greater share of such. The present work explores the application of such technology in developing an energy meter and that unit transmits the used energy units to the control center using IoT. This wireless energy metering and E billing for the domestic user overcome the manual reading of energy from the consumer meter and undue delays in billing as well as associated erroneous readings etc. The proposed unit consists of a Arduino controller with associated hardware and display unit to indicate the consumed energy in the users meter as well as interactive messages to the user regarding Tariff, usage pattern, conservation opportunities and probable load shedding etc. The user can set the required probable maximum limit of usage of energy unit and an alert message is received as the usage is reached or just after crossing. An encouraging message is sent to the user on saving specific block of energy leading to the conservation. The meter relay turns off the power on special condition like door lock (Non usage of power) and avoid un intended billing and possible theft. An interactive message is sent to the consumer regarding the same as when such abnormalities are detected. The IoT WiFi module transmits the usage information for the E billing process and avoids actual paper work and delayed payment etc. The meter tampering is also monitored in the proposed work. The system from the billing center send the message to the user mobile with bill amount and encourage online payments through E-Seva centers, Net-banking and even through mobile phones. This kind of interfaces is really needed for the smart grids. It will help to monitor centrally and proper load management can be done controlling the user's consumption.