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With the acceleration of energy storage construction, investors are paying attention to how the costs of storage projects can be recovered. Market rules and incentive policies affect the dissemination of energy storage costs. This article simulates the interactive behavior of multiple agents based on evolutionary game theory, taking into account market factors such as prices, capacity, and incentive policies. It views the dissemination of storage costs as an interactive decision-making problem involving multiple agents' adoption of technology, and analyzes how market factors influence the outcomes of cost dissemination. [ABSTRACT FROM AUTHOR]

As China's electricity market continues to evolve, the increasing number and diversity of market participants have led to a rapid increase in data volume. An immediate challenge is designing a robust blockchain system that ensures not only the transparency, credibility, tamper-resistance, traceability, privacy, and security of substantial market data in a complex environment, but also provides trusted data support for intelligent dispatching within the power market. This paper proposes a solution to this pressing issue through Blockchain as a Service (BaaS). BaaS leverages the capabilities of cloud computing platforms to enhance the ease and efficiency of deploying and operating blockchain systems. Specifically, the paper introduces a BaaS system built upon an integrated intelligent scheduling and operation cloud-edge platform (CEP). It incorporates technological solutions such as data on-chain, trusted comparison, edge cluster data transmission, optimized transaction authentication, and lightweight storage nodes. Rigorous testing has conclusively demonstrated that the proposed BaaS system meets the requirements of the digital transformation of the China Southern Power Grid, and provides robust technical support for its future practical applications. [ABSTRACT FROM AUTHOR]

This paper addresses the conundrum of optimizing electricity consumption patterns in response to fluctuations in demand and price, a task managed by both load aggregators and the distribution system operator (DSO). The conventional approaches in the literature to integrate demand response (DR) into optimal power flow (OPF) problems typically overlook the price responsiveness of consumers or simplify power flow equations to account for price-elastic demand. In this paper, we strive to close this gap by introducing a bi-level primal-dual optimization framework that incorporates aggregators' objectives into the market-clearing process while preserving the precision of the OPF equations. At the upper level, the model seeks to minimize both the total payment and peak load. The lower level, structured as a second-order conic (SOC) problem, aims to reduce overall generation costs subject to constraints of the second-order conic (SOC) branch flow model (BFM). The two levels interact through the optimal demand response and distribution locational marginal prices (DLMPs). The principles of convex duality principles together with the strong duality constraint are leveraged to transform the market-clearing problem into a single primal-dual problem. We also circumvent the non-linearity that stems from the DR payment term by incorporating discretizing loads and the big- M method, thus converting the problem into a mixed-integer SOC (MI-SOC) formulation. The merits of the proposed MI-SOC framework are validated through case studies conducted on the IEEE 33-bus test system, showcasing its potential to enforce price-elasticity demand response in distribution system's electricity markets. [ABSTRACT FROM AUTHOR]

Global decarbonisation is driving investments in intermittent renewable generation, with most plant entering the market by way of a Power Purchase Agreement. In Australia's National Electricity Market, a surprising number of renewable generators have entered on a merchant basis. To maintain tractable revenues some minimum level of hedging is required, but in an energy-only electricity market with a very high market price cap, merchant intermittent generators require some level of associated firming capacity to ensure spot price exposures can be adequately managed. This article uses unit commitment, battery arbitrage and stochastic discounted cashflow valuation models to compare an Open Cycle Gas Turbine and a battery as firming options for a hypothetical wind farm in the South Australian region of the NEM. Using historic market data from 2010–2020, we find OCGT firming capacity helps the wind farm to generate consistent net cash flows, allowing it to withstand the highs and lows of spot market prices whilst covering required contract-for-difference payments associated with hedging. When battery firming is deployed, the wind farm/ battery portfolio generated higher cash flows at specific times, reflecting participation in price arbitrage under low spot price scenarios. However, battery performance was constrained by costly storage capacity. [ABSTRACT FROM AUTHOR]

In September 2020, China has made a commitment to achieving "peak carbon dioxide emissions" before 2030 and "carbon neutrality" before 2060 at the General Assembly of the United Nations. Then, at the Climate Ambition Summit, China pointed out the important responsibility and mission of the power industry to serve "peak carbon dioxide emissions and carbon neutrality". The key issues such as what kind of electric market to build and what kind of main energy will be chosen to build the power system were proposed. For the new power system, there will be new changes in the links of "source, network, load, storage". However, the reform of the electricity market cannot be ignored, either. How to determine the type of electricity sales company and how to develop a suitable electricity sales strategy is one of the important studies that need to be explored at present. Therefore, the main body of electricity sales companies under new power system reform in China are analyzed in our studies, Then, we reviewed the current situation of electricity market reform at home and abroad. Finally, the thought on electricity market reform is presented. [ABSTRACT FROM AUTHOR]

Energy integration is considered to play a key role in the successful development of the European Union. It is assumed that purely market-based mechanisms in this sector, according to the neo-liberal model, can secure a constant supply at low prices. This is the basis of the Union's energy policy, launched by the European Commission (EC). The main goal of this paper is to examine the adequacy of this model and the extent to which the energy policy succeeds in achieving its objectives. There is a difficult combination of technological, economic and political factors expressed in the Union's energy mix. In particular, the document examines the gap between neo-liberal freemarket postulates and the practices of modern protectionism, assessing the sustainability of the EU's energy strategy and policy, which often avoid taking efficiency into account. Significant attention is paid to the link between energy and national security, as well as the politically justified intervention of the European Commission in energy projects related to energy supplies for the whole Union. Our research is based on statistics for a long period of time, allowing a comparison between stated intentions and achieved results. Our results stress on the direct link between energy, foreign policy and national security. This link, the cause of the unsatisfactory results, casts doubt on the full integration of the industry and contradicts the views of the Commission. [ABSTRACT FROM AUTHOR]

Microgrids (MGs) are designed to serve their hosting critical load in an island mode in case of major events. However, in normal conditions when MGs are in a grid-connected mode, they may face an opportunity to achieve financial profits through optimization of the operation of energy resources and proper participation in wholesale markets. This paper proposes a model to optimize the participation of MGs in the markets and operation of energy resources. Since MGs usually host renewable energy resources, making decisions without considering uncertainties may put MGs at risk. Therefore, the model considers uncertainties associated with the generation of renewable Distributed Generation (DGs), demand, and market prices via robust optimization technique. The model is formulated as a bi-level max-min optimization problem. The problem is solved in two iterative steps. In the first step, a Genetic Algorithm (GA) finds the worst situation of uncertain parameters such that MG profit is minimized. Then, a mixed-integer linear problem is solved to maximize the profit over MG decision variables considering the values determined in the first step. The steps are iterated to reach convergence to the best solution. To confirm the performance of the approach, it is applied to a typical MG and the results are reported. [ABSTRACT FROM AUTHOR]

The limitations of production subsidies for variable renewable energy (VRE) plant as a means of decarbonising electricity markets are well known. Despite this, production subsidies for VRE plant are the most prevalent form of policy intervention in Australia. In the absence of cost-effective storage, production subsidies for VRE plant can create incentives to produce electricity at times the system may not need it, thereby severing the link between the spot market and financial incentives to generate. Such production subsidies can also reduce the incentive for new VRE plant to participate in 'firm' forward derivative markets. In this paper, we examine two adjustments that could be made to production subsidies for VRE plant that would correct for these unintended consequences. Firstly, the quantum of the subsidy could be a function of the wholesale electricity price, electricity demand or emissions; and secondly, new generators would be ineligible to receive production subsidies without demonstrating that they are facilitating the supply of financial derivative contracts. The effect of both adjustments would be to increase the incentive of VRE plant to demand-follow; that is, make its output 'firmer'. [ABSTRACT FROM AUTHOR]

Abstract In electricity market, generation companies (Gencos) face the risk in both the spot market and contract market. Their strategies of contracts in electricity market will directly affect their profits. Therefore, it is crucial for Gencos to determine the total amount of contracts at a certain risk. This paper proposes an optimal management of contract power for generators considering bidding risks in spot market. Based on the risk-based Pareto front, the power quantity-price bidding curve of generators is constructed. We build a bi-level optimization model with upper-level objective function as generators revenue maximization and lower-level total objective function as production cost minimization. The Differential Evolution (DE) technique and Optimal Power Flow (OPF) tools are utilized in model solving. The simulation results of the modified IEEE system show the feasibility and effectiveness of this strategy. [ABSTRACT FROM AUTHOR]

Abstract Under the pressure of global environmental climate change, all countries in the world are developing renewable energy such as hydropower, wind energy, and solar energy As a result, the electricity price varies in different patterns depending on the penetration of renewable energy. In this paper, a non-parametric model is employed to analyze the historical data of electricity spot price from Danish price areas of the Nord Pool (with high percentage of wind power), Swedish price areas of the Nord Pool (with high percentage of hydropower) and PJM market (with little renewable energy penetrated). The objective is to deeply understand the influence of renewable energies on electricity price volatility. It is found that electricity prices are more stable in Swedish price areas as hydropower is a more stable energy source. The electricity price in PJM market is also comparatively stable, only more volatile than Swedish market, as fossil fuels are dominant energy resources. For Danish price areas, the volatility of electricity prices is clearly affected by wind power, which is a highly intermittent energy resource. [ABSTRACT FROM AUTHOR]

Abstract The restructuration of electric power sector has renovated the power system operational planning. In the deregulated market, electricity is treated as an entity unlike in the traditional vertically integrated market model where it is treated as a service provided by the generation companies (GENCOs). The task of GENCO is to perform self-scheduling of available units so as to achieve maximum profit in restructured power sector. Therefore, the problem of profit based unit commitment (PBUC) in deregulated markets can be formulated as a commitment and generation allocation through self-scheduling procedure. The commitment schedule optimization, i.e whether the status of a thermal unit is to be changed to on or off state, is a binary problem. Thus, the PBUC problem requires binary optimization for commitment and real valued optimization for generation allocation. In this paper, three binary grey wolf optimizer (BGWO) models are presented to solve the profit based self-scheduling problem of GENCO. The BGWO models proposed in this paper differ with respect to the transformation function used to map real valued wolf position into a binary variable. The binary mapping of commitment status is carried out using sigmoid and tangent hyperbolic transfer functions. Also, in the sigmoidal transfer function, two binary transformation procedures, namely crossover and conventional sigmoidal transfer function, are presented. The effectiveness of the proposed models in improving the solution quality of PBUC problem is examined using two test systems, a 3 unit and a 10 unit test system. In addition, two cases of GENCO market participation with and without reserve market participation are simulated. In the test case with reserve market participation, two commonly used reserve payment models are examined. Simulation results are presented and compared to existing approaches that have been used to solve the PBUC problem. The simulation results and statistical analysis demonstrate the improved solution quality (profit or fitness value) of the PBUC problem and statistical significance of the BGWO models with respect to solution quality obtained as compared to other established meta-heuristic approaches. [ABSTRACT FROM AUTHOR]

Abstract Aiming at the fuzziness and randomness existed in the electric power market operation efficiency evaluation, and evaluation index selection in different regional electricity market such as subjectivity and uncertainty problems, put forward reasonable and effective method of electric power market operation efficiency evaluation. Firstly, on the basis of the electric power market operation efficiency level boundary information, the subjective weighting method of the analytic hierarchy process and the objective weighting method of entropy weight method are combined to integrate by additive integration to evaluate the comprehensive weight of all indexes of the operation efficiency of the power market. Secondly, the analysis method of the uncertainty of the cloud model is combined with the qualitative and quantitative analysis methods of the matter-element theory in the extension theory, and it establishes an evaluation model of power market operation efficiency based on extension cloud theory. On this basis, the credibility factor and risk factors are introduced to reflect the credibility and risk information of the assessment results. Finally, an example is given to verify the rationality and validity of this method. [ABSTRACT FROM AUTHOR]

In the global context of intensive energy resource consumption and substantial greenhouse gas emissions, as the energy sector with the highest share of carbon emissions, the power generation industry is destined to play a central role in China's efforts to promote energy conservation and emission reduction. With the emergence of local carbon pilot projects and the implementation of a national carbon market, key emission units in the power industry, in addition to the electricity market business, also need to fulfill and pay carbon emission rights on schedule. The power generation rights are a market-based mechanism for clean energy units to replace conventional energy units in electricity generation, which can promote carbon emission reduction by incorporating the actual carbon emissions from conventional energy units. This paper establishes an optimized social welfare model that incorporates the interdependency between the thermal power generation unit market and the electric carbon market. It is based on the social welfare model of power generation rights and the initial allocation of carbon emission rights for the units, while considering the cost increase of excess emission under monthly forecasted power generation by the thermal power units. Taking a certain hydropower province as the simulation object, it was verified that the optimized model has a higher transaction rate of power generation rights, greater social welfare, and no reduction in unit revenue. • A groundbreaking linkage between power generation rights trading and carbon emissions trading is introduced. • A novel market optimization objective function is presented to enhance social welfare and encourage participation. • An innovative matching method is proposed to boost the transaction rate in power generation rights trading. • The proposed model is corroborated through a real case study in southwestern China. [ABSTRACT FROM AUTHOR]

Abstract This paper briefly discusses the present framework and status of Indian power market and guides through the possible adaptations to accommodate the growing renewable energy (RE) integration into the grid. The participation of RE generators in the wholesale energy market would provide them a platform to optimally manage their generation portfolio which would help them in compensating the high investment cost. The increased competition in the market would eventually bring down the electricity price. The objective of this paper is to identify an ideal framework and optimal bidding mechanism for RE generators (wind energy in particular) to maximize the overall capital gain (social welfare) in the Indian power market. The inputs from various foreign electricity markets having high wind energy penetration have been considered. Recent studies suggest that battery energy storage system (BESS) can play a significant role in handling risks associated with the uncertainties in wind power generation and thus can help in maximizing the revenue for wind farm owners. It can also be instrumental in active/reactive power balancing which will further help in the frequency regulation. The paper probes into the combined wind and battery energy trading, and various bidding strategies in the day-ahead market (DAM), intraday energy market, real-time balancing, and other ancillary markets. Highlights • Reviews the state of renewable energy in major electricity markets worldwide. • Overviews the present structure and status of RE in Indian power market. • Literature survey on optimal trading of wind energy and battery energy storage. • Brings forward the major challenges in large-scale wind energy trading. • Suggests framework for Indian power market to facilitate renewable integration. [ABSTRACT FROM AUTHOR]

Restructuring of power system has enabled generating companies to sell the power in energy markets. To avail maximum profit, every generating company frame strategies and bid in competitive energy markets. Prediction of rival behavior and information of future energy price is a major difficulty, while exercising the profit making strategies. A powerful optimization tool is required to handle the profit maximization process in dynamically changing market; keeping this fact in consideration, a new variant of Grey Wolf Optimizer (GWO) named as Intelligent Grey Wolf Optimizer (IGWO) is proposed. This variant employs two mathematical frameworks first an efficient sinusoidal truncated function and another one is oppositional based learning concept for ensuring the better exploration and exploitation properties. The accuracy of IGWO is tested and compared with other contemporary algorithms on 22 benchmark functions. Once proved, the proposed algorithm is applied for framing bidding strategy in uniform and dynamically changing market conditions. The results of IGWO are compared with GWO, oppositional-GWO (OGWO) and PSO. The rivals behaviors are modeled through normal distribution of the bids and two cost models are prepared. Further, Monte Carlo simulations are performed. It is observed that profit obtained from IGWO is more from OGWO, GWO and PSO for both a single trading hour and a trading day. A considerable amount of profit can be earned by a generation company by employing proposed methodology. [ABSTRACT FROM AUTHOR]

The concept of transactive energy (TE) been adapted in the regulation of electricity market within the context of economic planning and control for grid reliability enhancement. The objective is to improve productivity and participation of the players in the market that is composed of distributed energy resources (DER). The main goal of implementing a market structure based on TE is to secure permission for the market players so that they could attain a higher payoff. In this study, an optimization-based algorithm in which an objective function premised on economic strategies, distribution limitations and the overall demand in the market structure is proposed. The objective function is solved for near global optima using four heuristically guided optimization algorithms. The proposed algorithm which ensures that none of the independent players has priority and/or advantage over others, emphasizes optimum use of electrical/thermal energy distribution resources, while maximizing profit for the owners of the home microgrids (H-MGs). Reduction in the market clearing price (MCP) for further participation and the response of the consumers’ responsive loads are also considered in the study. The feasibility of the proposed algorithm is validated in a coalition formation scenario among the existing H-MGs. Results show an increase in the profit attained, enhanced system reliability and a reduction in the electricity cost of the consumers. [ABSTRACT FROM AUTHOR]

A hybrid energy generation system (HEGS) exploits the synergies of various energy to improve the utilization rate of renewable energy while enhancing economic efficiency. In deregulated energy markets, this study proposes a scheduling model for HEGS trading in both day-ahead electricity and hydrogen markets to maximize total profits based on price arbitrage. This HEGS is based on a real case in Southwest China and comprises three hydro units, two photovoltaic (PV) plants a pumped-storage facility, and an electrolyzer. The uncertainty of available PV power generation is modelled using polyhedral uncertainty set and then the proposed model is cast as an adaptive robust optimization (ARO) model in which the conservativeness can be controlled by the PV uncertainty budget (ΓPV). Then the column-and-constraint generation algorithm is employed to solve this model. The numerical results reveal that the total profit of HEGS trading in two markets can be increased compared to the case of only trading in the electricity market. For instance, the increase in the total profit is 1.01 % (i.e. 5091 CNY) when ΓPV = 2. Besides, the total profit is considerably affected by ΓPV. As ΓPV increases from 2 to 8 (i.e. the robustness increases), the total profit decreases from 507,045.5 CNY to 503,036.1 CNY. Moreover, sensitivity analysis of the total profit related to the pumped-storage capacity and hydrogen price are also presented. [ABSTRACT FROM AUTHOR]

• A novel carbon emission reduction(CER) methodology is proposed. • The Black-Scholes mode is introduced to measure carbon emission option pricing. • Case studies of campus grid CER assessment are conducted in Shenzhen. • Methods and policy suggestions of CER are given for grid integration of EVs. China, as the world's largest emitter of carbon emissions, has implemented carbon markets to reduce carbon emissions, but the economic feasibility of integrating electric vehicles (EVs) into these markets remains uncertain. To address this challenge, we propose a novel methodology for grid integration of EVs based on the Shenzhen carbon inclusive management measures. Our proposed methodology can optimize EV charging schedules based on carbon emission prices and improve the economic feasibility of low-carbon transitions through EVs in China. We incorporate the Black-Scholes model to measure carbon emission option pricing and develop an optimal bidding strategy that considers spatiotemporal uncertainties of EVs and electricity markets. We use numerical simulations with real-world data from Shenzhen carbon emission market and Guangdong electricity market to demonstrate the effectiveness of our proposed methodology. Results reveal that scheduling 100 EVs' charging/discharging behavior properly can generate a revenue of 2379.4 yuan for the distribution system operator, while the revenue for carbon emission reduction (CER) is only 9.35 yuan. This paper demonstrates that the potential revenue of CER may be substantially based on the future scenario for the carbon emission market. These findings provide valuable insights for policymakers and stakeholders seeking to reduce carbon emissions in China's electricity sector. [ABSTRACT FROM AUTHOR]

This article describes set up of the German "Energiewende" translated to energy transition with its strong focus on the electricity market and the most traditional form of renewable energy systems: hydropower. With the definition of the future development corridor of renewable energy Germany could achieve the really ambitious self-imposed greenhouse gas reduction. To implement the future development corridor of renewable energy, Germany applies over the years different versions of feed-in laws for renewable energy systems. A technology-independent funding of renewable energy systems is not intended in Germany. Wind power is seen as the most cost efficient technology. Regarding to the presented figures from three different perspectives: political and social, economic and technical, and global warming the current and future possible contribution of hydropower is underestimated. At least in the most powerful federal tectorial states Bavaria and Baden-Wuerttemberg considered by gross domestic product, hydropower has the biggest share of renewable gross electricity production. In these federal states hydropower has still growth potential and altogether the biggest growth potential compared to all other German federal states. Due to this fact it is incomprehensible why hydropower is not be seen as a bigger role player in the Energiewende. Additional research is needed to evaluate further possibilities for hydropower to support the aspired way of transforming the existing electricity market within the Energiewende. [ABSTRACT FROM AUTHOR]

China is quickly installing advanced metering infrastructure (AMI), which could provide tremendous opportunities in developing and utilizing demand response resources. Demand response may potentially create a profitable industry and contribute to efficiency improvement, cost reduction, and pollution mitigation of the entire electricity sector. However, China lags behind the developed world in utilizing demand response. Institutional barriers, including the lack of competitive electricity market and the resistance by the state grid corporations, are preventing the commercialization of demand response. In order to fully realize the potential of smart grid, China needs to push forward the reforms toward establishing an open access electricity market so the pollution-free demand response resources may compete with power generators on leveled field. [ABSTRACT FROM AUTHOR]

• Providing a four-stage model for scheduling smart buildings and designing microgrids strategy. • Utilizing the potential of smart buildings to improve the technical and economic indicators. • Reducing the electricity bill of smart buildings and the market price using V2G services. • Improving the technical and economic indicators of the system by smart buildings participation in a DRP. • Evaluating the impact of local generations of smart buildings on economic and technical aspects. After the restructuring of the electricity market, one of the challenges of researchers has always been to design markets that can use the maximum potential of smart consumers to improve the economic and technical indicators of the system. Therefore, this article presents a four-stage model in which the scheduling of smart buildings, microgrids and the main grid is done. In the first stage of this model, subscribers of smart buildings do their day-ahead scheduling with the aim of minimizing their electricity bill and send it to the central control unit of the building. In the second stage, the central control unit of the smart building performs its day-ahead scheduling according to the received programs and sends it to the microgrid operator. Then, in the third stage, the microgrid's strategy for participating in the day-ahead market is designed, considering the programs received from smart buildings. Finally, in the fourth stage, the market manager receives buy / sell offers of microgrids and calculates the market settlement price (MSP) with the aim of maximizing the social welfare (SW) index. The simulation results illustrate that equipping smart buildings with solar panels and energy storage systems (ESSs) not only reduces the MSP during peak hour by 6.66%, but also improves the network voltage profile. In addition, the results reflect that changing the behavior of smart subscribers and electric vehicles (EVs) by the incentive programs leads to a significant improvement of the technical and economic indicators of the network. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy in the power system and stricter restrictions on the air pollutants, more gas-fired generators have been accessed into the power system. To analyze the impacts of high proportion of gas-fired units on the power system, a liberalized electricity market Nash-Cournot equilibrium model has been proposed in this paper. Then a numerical example is given to present the influence of high proportion of gas-fired units on the energy price, demand and the accommodation of renewable energy in the market equilibrium. Comparisons between high and low proportion of gas-fired units in the power systems are also presented. [ABSTRACT FROM AUTHOR]

An efficient, low-cost and reliable operation of a power system by adjusting the available electricity generation resources to supply demand of the system is required to ensure satisfied economic plant dispatching. This paper proposes a scheme for economic redispatch model considering the transmission issues such as transmission congestion and network losses, in order to obtain an optimal energy price in supporting competitive electricity market under deregulated environment of a power system. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of DYNA: Energía y Sostenibilidad is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

“Congestion costs” occur in the electricity market when the power flows, equivalent to a projection mapping of energy injection and withdrawal, established by the “electricity stock exchange” and by “bi-lateral contracts”, are incompatible with the transfer capacity guaranteed by the power grid, in required security conditions. Transfer restrictions in the national and transboundary transmission grid can potentially determine the market segmentation in different geographical areas, preventing the producers to compete freely to satisfy the overall demand in those areas. As a result of power congestions, those producers that have reduced limitations in the power transfer are obviously favored, also if in the presence of high marginal production costs and prices, leading to the constitution of pools of producers that de facto control the local market. In particular this paper aims at describing and discussing the problem of power congestions, electricity price formation and congestion risk management. [ABSTRACT FROM AUTHOR]

Under the conditions of promoting the production of electricity from medium and small power sources (distributed generation), it is required that the connection of these groups to the already existing electrical substations in the National Power System is functional. This paper presents an analysis of the reliability of existing electrical substations in order to connect new sources for generating electricity. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new paradigm based on Shuffled Frog Leaping Algorithm (SFLA) is proposed. [•] It combines the advantages of both Memetic Algorithm (MA) and PSO and overcome the drawbacks of PSO. [•] A local search algorithm is applied to improve only the frog with the worst fitness (not all frogs) in each cycle. As a result, frogs tend to move towards the best position, which avoids premature convergence and permits a faster convergence. [•] The proposed method is numerically verified through computer simulations on IEEE 30-bus system and practical 75-bus Indian System. [•] The result shows that the proposed algorithm can generate better quality solution within shorter computational time and stable convergence characteristics compared to FAPSO, PSO and GA. [ABSTRACT FROM AUTHOR]

Abstract: The paper considers mechanisms for organizing free trade in the electricity market, which are based on submitting bids of energy consumers and producers to the market operator. The research focuses on the models of market operation as a double sided auction where participants have different rights (price takers and active competitors). The authors discuss and compare possible strategies of generator behavior that lead to different equilibrium situations and correspond to Cournot model and the models of supply function equilibrium, and a perfectly competitive equilibrium. The mechanisms are tested on the basis of the Siberian electric power system, Russia. [Copyright &y& Elsevier]

Abstract: Determinant factors of the Romanian energy systems’ transformation processes include both positive and negative ones. The former refer to European integration, creation of the Single Energy Market, the important number of clients/consumers, the energy systems’ performances - the first economic structure integrated with the European ones -, the existing primary energy resources etc. The latter include the lack of a coherent domestic industrial policy and the vulnerability of decision makers facing external pressures. The Romanian electricity generation structure has modified during the last 23 years. The main coordinates comprise: a continuous reduction, nearly to extinction, of the main generation company's share of the electricity market; atomization of the generation sector; privatization of five from eight existing distribution companies; creation of the supply segment; and, last but not least, the electricity price liberalization. The paper analyses some of the contradictory tendencies in over 20 year late history of the Romanian energy system and draws a series of possible measures to implement in order to counteract the negative results. [Copyright &y& Elsevier]

Abstract: A novel stochastic optimization approach to solve optimal bidding strategy problem in a pool based electricity market using fuzzy adaptive gravitational search algorithm (FAGSA) is presented. Generating companies (suppliers) participate in the bidding process in order to maximize their profits in an electricity market. Each supplier will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. The gravitational search algorithm (GSA) is tedious to solve the optimal bidding strategy problem because, the optimum selection of gravitational constant (G). To overcome this problem, FAGSA is applied for the first time to tune the gravitational constant using fuzzy “IF/THEN” rules. The fuzzy rule-based systems are natural candidates to design gravitational constant, because they provide a way to develop decision mechanism based on specific nature of search regions, transitions between their boundaries and completely dependent on the problem. The proposed method is tested on IEEE 30-bus system and 75-bus Indian practical system and compared with GSA, particle swarm optimization (PSO) and genetic algorithm (GA). The results show that, fuzzification of the gravitational constant, improve search behavior, solution quality and reduced computational time compared against standard constant parameter algorithms. [Copyright &y& Elsevier]

Abstract: This paper presents an in-depth performance evaluation of three different optimization algorithms, in particular genetic algorithm (GA), particle swarm optimization (PSO), and firefly (FF) algorithm for power demand forecasting in a deregulated electricity market and smart grid environments. In this framework, this paper proposes a hybrid intelligent algorithm for power demand forecasts using the combination of wavelet transform (WT) and fuzzy ARTMAP (FA) network that is optimized by using FF optimization algorithm. The effectiveness and accuracy of the proposed hybrid WT+FF+FA model is trained and tested utilizing the data obtained from ISO-NE electricity market. [Copyright &y& Elsevier]

Copyright of Academia: Revista Latinoamericana de Administración is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Electricity market operation involves complex and cooperative technical and economic links among its subsystems, the nonlinear interaction within the subsystems should be taken into account to depict the operational state. Based on principles of Synergy theory, a branch of complex system engineering theory, a synergistic evolutionary model of electricity market was established. Data processing showed that HHI and settlement price were the order parameters and correlation dimension found that there were at least two critical factors maintaining the market. Thus, the two order parameters could be used to describe the electricity market. The model showed high precision, revealed the dynamic relationship between its subsystems and laid a foundation for further study of the market operation. [Copyright &y& Elsevier]

Abstract: With the continuous development of the electricity market, its character as a complexity system is increasingly revealed, which requires that we should integrate complexity theory into the evaluation of electricity market operation and should have the systems engineering way of thinking at the same time. This paper uses entropy to measure the complexity of the electricity market, then regards complexity as an indicator and integrates it into the index system of electricity market, after that a model which is modified based on entropy theory to evaluate the operation efficiency of the electricity market is established. Finally, the complexity and operational efficiency of the electricity market are evaluated by simulating data. Form consequence we can find that the complexity of the electricity market is higher than the general market, the efficiency of region 5 is relatively low, region 3 is the most efficient, other four regions are small in difference. The result shows that the entropy as a measure of the complexity of the electricity market is simple in calculation, it can also accurately reflect the complexity of the electricity market. The use of chaos optimization of entropy-random DEA model has good flexibility and feasibility for the evaluation of the operational efficiency of the electricity market. [Copyright &y& Elsevier]

Abstract: The power system economic dispatch model was improved, which only considered the feathers of cost and emission. The conception of energy conservation factor is suggested. Established a new model of economic dispatch considering energy conservation and environmental protection in electricity market, then, used it in a simulation system to verify its effectiveness. The new model gives a preliminary exploration and attempt on the implementation of the energy conservation power generation dispatch. [Copyright &y& Elsevier]

Abstract: The whole Electric Power System includes three aspects: Generation, Transmission and Distribution that all need maintenance to enhance system reliability and energy efficiency. Most unit maintenance scheduling (MS) packages consider preventive maintenance scheduling for generating units over one or two years time horizon in order to minimize the total operation costs while satisfying system energy requirements. The inclusion of network constraints in generating unit maintenance will increase the complexity of the problem. This paper mainly considers the generation maintenance scheduling taking into account the system security and reliability indices. For more realistic study transmission, security constraints as well as crew constraints and system reliability indices such as amount of not supplied energy are considered for the proposed maintenance scheduling problem. General Algebraic Modelling System (GAMS) is the utilized for solving optimization problem. An IEEE 24 bus test system is employed for simulation and show the accuracy of results. [Copyright &y& Elsevier]

This paper deals with market power and information issues in the ongoing process of the European Electricity Market. We present a regulatory game played among the key group of utilities, the customers and the regulatory authority. The development of the game allows us to state for a clear commitment to entry freedom reducing the informational strategic advantage of incumbents. As the assumption of such a commitment involves another game, we develop it and we conclude that the liberalisation of entry is also a key factor for credibility and effectiveness of flexible regulation and tariffs reduction as well. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzes market opportunities for power plants equipped with post-combustion carbon capture. The focus is on an Ultra Super Critical Pulverized Coal plant and a Natural Gas Combined Cycle plant, which both have flexible CO2 capture (i.e., the capture plant can be turned on and off). In a methodological framework, it is first demonstrated that flexible operation yields higher profits compared to operating strictly with or without carbon capture. The most beneficial operating mode is determined by the ratio between the CO2 and electricity price. Furthermore, a definition is proposed for the marginal cost which can be attributed to the additional capacity which is made available by turning off the capture plant (which could serve as reserve power). A detailed optimization model is employed, to account for the power plants’ technical constraints, and to determine the benefits of flexible capture quantitatively. It is shown that at moderate CO2 prices, capture plants can serve as back-up capacity, i.e., making additional power available by turning off the capture plant can be cheaper than having to start-up and operate additional single cycle gas turbines. Furthermore, the option of turning off the capture plant might avoid investment in additional back-up capacity and could therefore also prove useful at higher CO2 prices. [Copyright &y& Elsevier]

Abstract: A focus of study in auction market design is revenue comparison. Revenue Equivalence Theorem implies that bidders receive the same amount of revenue invariant to the auction type. This paper explores the applicability of this theorem in the context of the electricity market. We develop experimental test cases using agent-based simulation to examine the impact of different pricing rule on total dispatch cost. Using Q-learning in a repetitive trading environment, generator agents can quickly learn the market characteristics and seek to maximize their revenue by adapting their bidding strategies. A look-up table is utilized as a learning mechanism to improve the agent''s bidding strategies. We conclude that Revenue Equivalence Theorem holds in a multi-unitmulti- period in symmetric bidding. In asymmetric bidding and when the market share of generator agents differs significantly, the computer simulation allows us to observe the rapid increase in revenue with uniform auction. [Copyright &y& Elsevier]

Abstract: Online service providers (OSPs) have Internet data centers in multiple geographical locations in order to satisfy global user demand. Increased data centers consume a large amount of energy, and at the same time causes increased heat dissipation, greater cooling requirements, reduced computational density, and higher operating costs. It places a heavy burden on both the environment and energy resources. OSPs are now focusing more than ever on the need to improve energy efficiency. A new challenge has emerged besides the energy cost, the reduction of the carbon footprint. Although electricity is a clean and relatively safe form of energy to use, there are environmental impacts associated with the production and transmission of electricity. Meanwhile, increased online services require more Internet usage, especially with the trend of cloud computing; the network costs account for a large portion of operation costs for OSPs. This paper proposes an optimal energy-aware load dispatching model to minimize the electricity and network costs for OSPs. Our model can greatly reduce the costs for OSPs by considering the volatility of electricity market and applying energy-efficiency strategies in each data center. We conduct extensive evaluations based on real workload data and electricity price data. The results prove the effectiveness of our energy-aware load dispatching model with a theoretically guaranteed quality of service (QoS). [Copyright &y& Elsevier]

Abstract: In this paper, we compare different policy incentives for overcoming investment uncertainties that are typical for low-carbon technologies prior to their commercialisation, some of which may be attributable to market failures. The paper focuses on the particular case of carbon capture and storage (CCS) technologies and conducts a qualitative multi-criteria analysis of different public policy support schemes for CCS demonstration to evaluate their suitability. The assessed schemes include mandatory CCS, emission performance standards and several different financial incentives (in addition to the European Union Emission Trading Scheme). Based on the available literature and on experience in the UK and Germany with promotion instruments for low-carbon technologies, the results of our analysis suggest that two alternative schemes, a CCS bonus incentive or a carbon dioxide (CO2) price guarantee, perform best in comparison with the other assessed instruments. While they reduce the uncertainty of CCS investments in the face of low European Union Allowance prices, they also avoid significant adverse impacts on operational and investment decisions in electricity markets. [Copyright &y& Elsevier]

Analysis in this Article is focused on usage of transmission grid under liberalized market with implicit transmission capacity allocation method, e.g. Nordic market. Attention is paid on fundamental changes in transmission utilization and its economical effective operation. For interconnection and power flow analysis and losses calculation model of Nordic grid was developed and transmission losses calculation method was created. Given approach will improve economical efficiency of system operation in electricity market conditions. [ABSTRACT FROM AUTHOR]

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