Competitive Power Market Research Articles

Integrated pricing of roads and electricity enabled by wireless power transfer

This paper explores integrated pricing of electricity and roads enabled by wireless power transfer technology. We envision that high-power, high-efficiency wireless power transfer technologies are mature in the near future, which electrify roads to be charging infrastructures. The prices of electricity at electrified roads will affect electric vehicles’ route choices while the energy requirement of those vehicles will in return affect the operations of the power network and thus the prices of electricity. To determine the optimal prices of electricity and roads to maximize social welfare, first- and second-best pricing models are proposed under different authoritarian regimes. More specifically, assuming that a government agency manages both transportation and power systems, we develop the first-best pricing model, based on which a marginal-cost pricing scheme is derived. The second-best pricing model is proposed if the agency participates in a competitive wholesale power market while being able to impose tolls on electrified roads. The toll design is formulated as a mathematical program with complementarity constraints, and is solved by a manifold suboptimization algorithm. Numerical examples are presented to offer insights on integrated pricing of roads and electricity and demonstrate its effectiveness on improving social welfare.

Enhancement of ATC by Optimal Allocation of TCSC and SVC by Using Genetic Algorithm

This paper proposes Improving of ATC is an important issue in the current de-regulated environment of power systems. The Available Transfer Capability (ATC) of a transmission network is the unutilized transfer capabilities of a transmission network for the transfer of power for further commercial activity, over and above already committed usage. Power transactions between a specific seller bus/area and a buyer bus/area can be committed only when sufficient ATC is available. Transmission system operators (TSOs) are encouraged to use the existing facilities more effectively to enhance the ATC margin. Heavily loaded circuits and buses with relatively low voltages can limit ATC usually. It is well known that FACTS technology can control voltage magnitude, phase angle and circuit reactance. Using these devices may redistribute the load flow, regulating bus voltages. Therefore, it is worthwhile to investigate the impact of FACTS controllers on the ATC. In this thesis focuses on the evaluation of the impact of TCSC and SVC as FACTS devices on ATC and its enhancement during with and without line outage cases. In a competitive (deregulated) power market, optimal the location of these devices and their control can significantly affect the operation of the system and will be very important for ISO.

Perspectives of Renewable Energy Sources in the Future Indian Competitive Electricity Markets

Energy is considered to be a key factor in the generation of wealth, social development and improved quality of life in all developed and developing countries in the world. Renewable energy development is of great importance from the point of view of long term energy supply security, decentralization of energy supply particularly for the benefit of the rural population, environmental benefits and sustainability in competitive power market also. India is on the path of rapid economic growth along with speedy overall development; simultaneously it has to face the global threat of climate change. India has a vast supply of renewable energy resources, and it has one of the largest programs in the world for deploying renewable energy based products and systems. These technologies have long been recognized as an important part of the solution to address energy security concerns and ensure economic growth in an environment friendly manner. India had cross 25 GW milestone installed grid connected renewable energy capacity. For renewable development in India, the renewable energy program has been in existence for more than three decades, but a market for renewable energy technologies still need to be exists. The country is aiming to achieve up to 20% of additional installed capacity to be set up till 2020 to come from RES. In this paper, efforts have been made to summarize the availability, current status, environmental effects, promotion policies and future potential & strategies of renewable energy options in Indian competitive electricity markets. Keywords: Competitive power market, renewable energy sources, renewable policy

Profit based unit commitment and economic dispatch of IPPs with new technique

Each generation company may have number of generating units of different fuel consumption characteristics, some generating units consume more fuel as compared to other units this directly effects the production cost and profit of the company. Production cost and profit of the company is also affected by unit commitment and economic dispatch. Each and every power generation company wants to maximize/increase profit, same is the case for independent power producers (IPPs). Profit can be maximized by changing the unit commitment and economic dispatch strategy. Previously it was achieved in such a way that production cost goes to minimum level. But as the competition in power market is going to increase day by day IPPs trend of UC solution is toward achieving maximum profit. Previously achieved solution by LR–PBUC is slow and may face convergence problem. In this paper, we will see the way how a GENCO or IPP can earn more by UC on the base of profit, with minimum computational time and always with some final solution. Hamiltonian method has been used for ED. To demonstrate the effectiveness of the PBUC achieved and Hamiltonian economic dispatch, it will be tested on two test cases. Profit and computational time comparison of proposed technique with already available/techniques for evaluation of performance are also presented.

Reduction in subsidy for solar power as distributed electricity generation in Indian future competitive power market

Developed countries have seen renewable energy as a key tool for emission reduction as well as reducing reliance on oil, gas, and coal. Renewable energy sources (RESs) and technologies have potential to provide solutions to the longstanding energy problems being faced by the developing countries. In the future competitive electricity market for India, it becomes very much important to give special consideration for development of RESs due to economic, environmental, and other social problems related with conventional generations. Solar energy can be an important part of India's plan not only to add new capacity but also to increase energy security and lead the massive market for renewable energy. The major problem with solar power generation (SPG) is high cost of renewable generation. The Indian government is providing a lot of subsidy in order to encourage renewable energy generations. This paper presents an approach for reduction in subsidy of SPG used as distributed generator in competitive power market. The proposed approach has been validated with IEEE 14-bus and IEEE 30-bus systems.

Congestion management in hybrid power markets using modified Benders decomposition

Congestion management is one of critical tasks in electric power markets. Although congestion management using a centralized optimal power flow may give an efficient solution, it lacks enough transparency in a competitive power market for its participants about congestion related costs. On the other hand, clearing the market and mitigating congestion separately may not result in an efficient solution from cost viewpoint. In this paper, a two-stage method using a modified Benders decomposition technique is proposed for congestion management in hybrid electricity markets including pool and bilateral transactions. An innovative convergence criterion and a new type of the sub-problem are proposed in using Benders decomposition in congestion management. The proposed method not only gives the efficient solution, but also provides enough transparency about congestion cost. Results of testing the method on the New-England test system are presented and discussed in detail. The results confirm the efficiency of the proposed congestion management method.

Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach

In this study, a model is developed to investigate the implications of an hourly day-ahead competitive power market on generator profits, electricity prices, availability and supply security. An integrated simulation/optimization approach is employed integrating a multi-agent simulation model with two alternative optimization models. The simulation model represents interactions between power generator, system operator, power user and power transmitter agents while the network flow optimization model oversees and optimizes the electricity flows, dispatches generators based on two alternative approaches used in the modeling of the underlying transmission network: a linear minimum cost network flow model and a non-linear alternating current optimal power flow model. Supply, demand, transmission, capacity and other technological constraints are thereby enforced.The transmission network, on which the scenario analyses are carried out, includes 30 bus, 41 lines, 9 generators, and 21 power users. The scenarios examined in the analysis cover various settings of transmission line capacities/fees, and hourly learning algorithms. Results provide insight into key behavioral and structural aspects of a decentralized electricity market under network constraints and reveal the importance of using an AC network instead of a simplified linear network flow approach.

Cascade BPN based transmission line overload prediction and preventive action by generation rescheduling

This paper is a modest attempt to address an intelligent technique based on Cascade Back Propagation Neural network (CBPN) for detection of line overloads, prediction of overloading amount and alleviation of overloads using generation rescheduling with N-1 contingency in restructured power system. In the present competitive power market, power transmission congestion has become more intensified and recurrent than the vertically bundled system. Transmission line congestion initiates the cascading outages which forces the system to collapse. Accurate prediction and alleviation of line overloads are the suitable corrective actions to avoid network collapse. The most obvious technique for network Congestion Management (CM) is rescheduling the power output of generators. The proposed CBPN comprises three Artificial Neural Networks (ANNs) in cascade. ANN1 is used as a classifier, which classifies the system state as secure or insecure. ANN2 is used for the prediction of overloading amount in the overloaded lines and ANN3 gives optimal generation rescheduling values for alleviating the overloads. The real power and reactive power of loads at all the load buses and the line outage number are considered as input variables to ANN1, ANN2 and ANN3. The effectiveness of the proposed approach is tested for various contingencies in the IEEE30 Bus System. The experimental results show that the proposed approach is computationally fast, reliable and efficient, in restoring the system to the normal state after a contingency with minimal control actions.

Retail power market competition with endogenous entry decision—An auction data analysis

Deregulation in the electric power industry has been aimed at promoting competition and thereby enhancing the industry’s efficiency. We use the auction data of public power procurements to study the impact of the reform on the retail power market in Japan. We quantify this impact by measuring a decline in power charges, controlling for the endogeneity bias caused by the entrants’ bid-submission decisions. Our results suggest that power charges would decline by about 0.48yen/kWh on average when two or more providers bid at an auction.

Sustainable Generation and Transmission Expansion Planning in Competitive Power Markets

This paper, presents on the coordination of power system expansion planning including sustainable generation expansion planning (GEP) and transmission network expansion planning (TEP). For this purpose, a game theory based model is proposed to determine the dominant strategy of each investor entities in the generation and transmission sectors. In this model, all power producers compete with each other at the same level for maintaining the energy and reserve services. At this stage, after determining the Cournot equilibrium, the suggestions accepted in previous stage are evaluated in the transmission planning stage. Here, according to the existing units and the units proposed in the previous stage, transmission network expansion planning takes place based on cost, social welfare and reliability indices by independent system operator. Thereafter transmission expansion planning results announced, the accepted unit and not accepted units can offer their new strategies to the market. This iterative process continues until the dominant strategy of each entity is satisfied and the final equilibrium is obtained. To solve this game and finding its Nash equilibrium, the mixed integer non-linear programming (MINLP) optimization is used by all decision makers for optimizing their desirable strategies to invest in the power market. A conceptual test system is proposed to show the ability of the model. Simulation results verify the feasibility and capability of the proposed modeling of the long-term expansion planning.

Strategic role of capacity management in electricity service centre using Markovian and simulation approach

In today’s competitive power market integrated with industrial growth, capacity management becomes a perennial technical issue. Power utilities lose customers when they lack sufficient capacity to provide their demanded service which severely affects the business process of the industries. Interruption time is one of the key characteristics of quality service and customer satisfaction. While additional capacity improves service quality, but the cost for providing capacity increases. Thus, the capacity management is having a conflicting role with the utility effectiveness. The important strategy role of capacity management should be arriving at a point wherein it is optimally economical and maximising the customer satisfaction. A live case of Electrical Service Centre of Goa Electricity Department is modelled using Markov model by a code written in MATLAB 7.0 and the working of Electrical Service Centre was modelled in general purposes simulation system. Results, conclusions and future scope are discussed.

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

This paper proposes a nodal ant colony optimization (NACO) technique to solve profit based unit commitment problem (PBUCP). Generation companies (GENCOs) in a competitive restructured power market, schedule their generators with an objective to maximize their own profit without any regard for system social benefit. Power and reserve prices become important factors in decision process. Ant colony optimization that mimics the behavior of ants foraging activities is suitably implemented to search the UCP search space. Here a search space consisting of optimal combination of binary nodes for unit ON/OFF status is represented for the movement of the ants to maintain good exploration and exploitation search capabilities. The proposed model help GENCOs to make decisions on the quantity of power and reserve that must be put up for sale in the markets and also to schedule generators in order to receive the maximum profit. The effectiveness of the proposed technique for PBUCP is validated on 10 and 36 generating unit systems available in the literature. NACO yields an increase of profit, greater than 1.5%, in comparison with the basic ACO, Muller method and hybrid LR-GA.

The model of chaotic sequences based on adaptive particle swarm optimization arithmetic combined with seasonal term

Within a competitive electric power market, electricity price is one of the core elements, which is crucial to all the market participants. Accurately forecasting of electricity price becomes highly desirable. This paper propose a forecasting model of electricity price using chaotic sequences for forecasting of short term electricity price in the Australian power market. One modified model is applies seasonal adjustment and another modified model is employed seasonal adjustment and adaptive particle swarm optimization (APSO) that determines the parameters for the chaotic system. The experimental results show that the proposed methods performs noticeably better than the traditional chaotic algorithm.

Capacity management of an electricity service centre using simulation

In today’s competitive power market integrated with industrial growth, capacity management becomes a perennial technical issue. Power utilities lose customers when they lack sufficient capacity to provide their demanded service which severely affects the business process of the industries. Interruption time is one of the key characteristics of quality service and customer satisfaction. Higher the frequency of it may even force customer to switch over, resulting in a situation of loss of customer. While additional capacity improves service quality, but the cost for providing capacity increases. Electrical service centre of Goa Electricity Department is a customer complaint redressing mechanism hence its modelling becomes essential for investigating its efficacy. Thus the whole scenario gets placed in non-exponential and dynamic, wherein the classical stochastic models become transcendental. Using discrete event simulation, the working of electrical customer service centre was modelled and coded in general purposes simulation system.

Neural Network-Based Approach for ATC Estimation Using Distributed Computing

In the competitive electric power market allowing open access transmission environment, the knowledge of available transfer capability (ATC) is very important for optimum utilization of existing transmission facility. ATC information conveys how much power can be transmitted through the power network over and above already committed usage without violation of system security limits. This paper presents a Levenberg-Marquardt algorithm neural network (LMANN)-based approach for fast and accurate estimation of system ATC. System ATC has been estimated for both varying load condition as well as for single line outage contingency condition by employing distributed computing. Principal component analysis (PCA) has been applied for effective input feature selection. Contingency clusters are formed such that each cluster contains almost similar ATC values. For each contingency clusters separate LMANNs have been developed. All the proposed LMANNs have been trained and tested under distributed computing environment and a considerable speed up in the training is obtained. The proposed approach has been examined on 75-bus Indian power system and IEEE 300-bus system and found significantly efficient.

건설분야의 IT 융합기술 개발모델

국내 건설산업이 새로운 도약을 이루기 위해서는 해외 시장에서의 경쟁력 확보와 새로운 시장의 창출이 필요하다. 국제적인 기술경쟁력을 가진 건설 분야와 IT 분야의 융합기술 개발을 통한 국제 경쟁력 확보와 새로운 시장창출은 성공가능성이 매우 높게 평가된다. 그렇지만, 구체적인 실현에 있어서 기술적 장벽뿐만 아니라, 융합개발의 명확한 모델이 정립되어 있지 않기 때문에, 건설 산업 관점에서 융합기술의 가능영역과 적절한 개발모델의 제시가 요구되고 있다. 건설 분야의 IT 융합기술은 생산성 향상과 노동력 절감 및 유지관리 구조물의 생애주기 비용절감을 통한 경쟁력 강화 분야와 u-city와 같은 수요창출형 신상품의 개발로 구분될 수 있다. 특히, IT 융합기술 개발 단계에서 건설사 관점에서 철저한 수요중심의 접근과 빠른 IT 기술발전에 대응하는 전략이 요구되며, 융합개발의 주도그룹을 선두로 선순환적인 순환모델을 적용하는 전략이 효과적일 것이다. 【In the edge of new jumping up in global market, our construction industry is required to develop a competitive power and new construction market. As a considerable global player, our construction industry and information technology industry are regarded as to achieve more competitiveness and new market by developing fusion technology between information and construction technology. But, practically not only the technologic barrier but unripe developing model, it is time to visualize fusion strategic model and possible area as a constructional point of view. The aim of fusion technology is to increase productivity by reducing labor power and over all life cycle cost and to suggest new market with effective demanding power such as ubiquitous-city. As a successful development model, both the demand driven approach dealing with prompt IT developing speed and a circular leading model boosted by leading group will be key factors.】

Enhancement of Available Transfer Capability with Facts Device in the Competitive Power Market

In order to facilitate the electricity market operation and trade in the restructured environment, ample transmission capability should be provided to satisfy the demand of increasing power transactions. The conflict of this requirement and the restrictions on the transmission expansion in the restructured electrical market has motivated the development of methodologies to enhance the Available Transfer Capability (ATC) of the existing transmission grids. The insertion of FACTS devices in electrical systems seems to be a promising strategy to enhance ATC. In this paper, the viability and technical merits of boosting ATC using Thyristor Controlled Series Compensator (TCSC) is being analyzed. The work has been carried out on IEEE 30 bus and IEEE 118 bus systems. Bilateral and multilateral transactions are considered. Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) are employed to obtain the optimal settings of TCSC.

Computation of Capacity Benefit Margin using Differential Evolution

In a competitive electric power market, the knowledge of Available Transfer Capability (ATC) can help power marketers, sellers and buyers in planning, operation and reserving transmission services. Capacity Benefit Margin (CBM) is an important factor in the calculation of ATC, without which ATC may be overestimated and this will lead to the risk of having generation unreliability. In this paper, a new algorithm using Differential Evolution along with Monte Carlo is proposed to evaluate CBM. The superiority of the proposed algorithm is tested on modified IEEE 30 bus system, over PSO.

A Study on the Reliability of the Distribution Automation System for the Lightning Effect

In today's competitive power market, electric power utilities have strived to provide energy at an acceptable level of quality due to increased expectations from customers. For this reason, electric power utilities have invested in electric equipment and new techniques. That is the Distribution Automation System (DAS). A merit of DAS is the ability to reduce outage time because of fast service restoration. However, DAS is usually installed in outdoor environments. Therefore, their efficiency is affected by the external conditions. Lightning creates varying degrees of physical stress on DAS. This paper focuses on the reliability of DAS for lightning. Four application studies were performed to compare the reliability indices.

구역전기사업자 구성을 위한 Phasor Discrete Particle Swarm Optimization 알고리즘

본 논문에서는 구역전기사업자를 구성하는데 적용하기 위해, 기존의 최적화 기법인 Discrete Particle Swarm Optimization (DPSO) 알고리즘을 개량한 Phasor DPSO (PDPSO) 알고리즘을 새롭게 제시한다. 구역전기사업자는 전력구입 뿐만 아니라 전력판매도 가능하고, 미리 계약한 수용가의 전력부하에게 전력을 공급할 의무가 있다. 하나의 배전계통에 다수의 구역전기사업자가 존재할 경우, 해당 배전계통 내의 모든 수용가에게 최소의 운영비용으로 전력을 공급하기 위해서는 다수 구역전기사업자 간에 구성형태를 조정할 필요가 있다. 이에 적용할 최적화 기법으로 본 논문은 PDPSO 알고리즘을 제안하며, 제안된 알고리즘의 각 개체는 기존의 다변수 벡터 대신 크기와 위상각으로 이루어진 다변수 페이저 값을 갖는다.