Renewable electric energy integration: Quantifying the value of design of markets for international transmission capacity

Integrating large quantities of variable renewable electricity generation remains a political and operational challenge. One of the main obstacles in Europe to installing at least 200 GWs of power from variable renewable sources is how to deal with the insufficient network capacity and the congestion that will result from new flow patterns. We model the current methodology for controlling congestion at international borders and compare its results, under varying penetrations of wind power, with models that simulate an integrated European network using nodal/localised marginal pricing. The nodal pricing simulations illustrate that congestion and price patterns vary considerably between wind scenarios and within countries, and that a nodal price regime could make better use of existing network capacity, introducing substantial operational cost savings and reducing marginal power prices in the majority of European countries.     

Congestion management through topological corrections: A case study of Central Western Europe

The integration of an increasing amount of renewable generation within Europe is posing operational challenges that require various balancing actions. System operators therefore need to rely increasingly on the active control of the transmission network. Transmission topology control is a fast and economical option to add flexibility to the transmission system. We model the current methodology for controlling congestion in the Central Western European (CWE) market and quantify the benefits of topology control. We also compare the results with a nodal pricing model. Our computational results suggest that topology control can significantly reduce congestion management costs under the current market coupling regime whereas the benefits of topology control are limited under nodal pricing. Topology control emerges as an attractive and implementable means of managing congestion as it provides a significant percentage of the cost savings that would be achieved by overhauling the existing European market design and shifting to a nodal pricing regime.     

Evaluation of safety distances related to unconfined hydrogen explosions

A simple approximate method for evaluation of blast effects and safety distances for unconfined hydrogen explosions is presented. The method includes models for flame speeds, hydrogen dispersion, blast parameters, and blast damage criteria. An example of the application of this methodology for hydrogen releases in three hypothetical obstructed areas with different levels of congestion is presented. The severity of the blast effect of unconfined hydrogen explosions is shown to depend strongly on the level of congestion for relatively small releases. Extremely large releases of hydrogen are predicted to be less sensitive to the congestion level.     

An approach to locational marginal price based zonal congestion management in deregulated electricity market

Congestion of transmission line is a vital issue and its management pose a technical challenge in power system deregulation. Congestion occurs in deregulated electricity market when transmission capacity is not sufficient to simultaneously accommodate all constraints of power transmission through a line. Therefore, to manage congestion, a locational marginal price (LMP) based zonal congestion management approach in a deregulated electricity market has been proposed in this paper. As LMP is an economic indicator and its difference between two buses across a transmission line provides the measure of the degree of congestion, therefore, it is efficiently and reliably used in deregulated electricity market for congestion management. This paper utilizes the difference of LMP across a transmission line to categorize various congestion zones in the system. After the identification of congestion zones, distributed generation is optimally placed in most congestion sensitive zones using LMP difference in order to manage congestion. The performance of the proposed methodology has been tested on the IEEE 14-bus system and IEEE 57-bus system.     

Sustainable Generation Portfolio

The concept of congestion management is extended to include dynamic effects. Based on a hybrid market structure, a new framework is proposed to eliminate congestion when system stability is threatened. It is shown that by fully utilizing the available resources, system stability as well as the transactions in the bilateral and balancing markets can be secured after a stability contingency, while the total dynamic congestion management cost is minimized.     

The effect of counter-trading on competition in electricity markets

In a competitive electricity market, nodal pricing is the most efficient way to manage congestion. Counter-trading is inefficient as it gives the wrong long term signals for entry and exit of power plants. However, in a non-competitive market, additional entry will improve the competitiveness of the market, and will increase social benefit by reducing price–cost margins. This paper studies whether the potential pro-competitive entry effects could make counter-trading more efficient than nodal pricing. We find that this is unlikely to be the case, and expect counter-trading to have a negative effect on overall welfare. The potential benefits of additional competition (more competitive prices and lower production cost) do not outweigh the distortions (additional investment cost for the entrant, and socialization of the congestion cost to final consumers).     

Multi-objective congestion management incorporating voltage and transient stabilities

Congestion in a power system is turned up due to operating limits. To relieve congestion in a deregulated power market, the system operator pays to market participants considering their bids to alter their active powers. After relieving congestion, the network may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. The proposed multi-objective framework for congestion management in this paper simultaneously optimizes competing objective functions of congestion management cost, voltage security, and dynamic security. The voltage stability margin and corrected transient energy margin are employed as indices to be incorporated into the multi-objective congestion management. A fuzzy decision maker is proposed to derive the most efficient solution among Pareto-optimal solutions of multi-objective mathematical programming problem. Results of testing the proposed method on the New-England test system elaborate the efficiency of the proposed method.     

Multi-objective congestion management by modified augmented ε-constraint method

Congestion management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the congestion management framework. The multi-objective congestion management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective congestion management framework is presented while simultaneously optimizing the competing objective functions of congestion management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented ε-constraint method, is based on the augmented ε-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective congestion management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method.     

Congestion management enhancing transient stability of power systems

In a competitive electricity market, where market parties try to maximize their profits, it is necessary to keep an acceptable level of power system security to retain the continuity of electricity services to customers at a reasonable cost. Congestion in a power system is turned up due to network limits. After relieving congestion, the network may be operated with a reduced transient stability margin because of increasing the contribution of risky participants. In this paper, a novel congestion management method based on a new transient stability criterion is introduced. Using the sensitivity of corrected transient stability margin with respect to generations and demands, the proposed method so alleviates the congestion that the network can more retain its transient security compared with earlier methods. The proposed transient stability index is constructed considering the likelihood of credible faults. Indeed, market parties participate by their security-effective bids rather than raw bids. Results of testing the proposed method along with the earlier ones on the New-England test system elaborate the efficiency of the proposed method from the viewpoint of providing a better transient stability margin with a lower security cost.     

A new approach to congestion pricing in electricity markets: Improving user pays pricing incentives

Electricity pricing has traditionally been based on average cost pricing where consumers pay a ‘flat’ tariff based upon the average cost of production and transportation of electricity. The introduction of new ‘smart’ meters allows electricity providers to differentiate tariffs on the basis of time. Utilising congestion pricing theory, the energy industry has embraced ‘time-of-use’ (ToU) tariffs with a view to more efficiently pricing electricity. This paper demonstrates that pricing as a function of demand variability (reflecting capacity utilisation) is a more appropriate alternative to existing ToU tariffs for more efficiently allocating costs to end users. We call this new alternative pricing model ‘first derivative ratio’ FDR pricing. This new approach to congestion pricing could be applied to markets other than electricity, such as road transportation.     

Market-based congestion management in electric power systems with increased share of natural gas dependent power plants

The paper addresses market-based congestion management (MBCM) in electric power systems taking into account the constraints of the electric power system (EPS) and the natural gas system (NGS). The proposed method is based on the countertrade methodology, where the system operator performs minimum-cost redispatching according to bids from generators and loads. The EPS is presented by the DC model for power flow calculation, which uses power transfer distribution factors (PTDFs) to describe the relation between generators/loads and line-power flows. The proposed solution applies the Benders decomposition method to decouple the problem into a master problem and subproblem. The master problem includes the bid-based redispatching for congestion relief and the EPS feasibility check. The subproblem checks the NGS operation feasibility when gas-fired generating units are redispatched in the master problem. Any NGS violations from the subproblem are incorporated into the master problem as power constraints for the next iteration of congestion management. The master problem is solved by linear programming. The NGS is presented in a nonlinear model and its feasibility check is performed using successive linear programming. Case studies illustrate the applicability of the proposed congestion management method on simple test models of the EPS and the NGS.     

Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment

This study discusses a new use of DEA environmental assessment to measure a possible occurrence of desirable congestion, or eco-technology innovation, in electric power plants. The phenomenon is compared with an occurrence of undesirable congestion in this study. The identification of undesirable congestion is important to avoid a cost increase and a shortage of generation. However, the identification of desirable congestion is much more important than that of undesirable congestion from the perspective of environmental assessment. This study looks for a sustainable economic growth by identifying eco-technology innovation that can be effectively used to reduce the amount of air pollution so that electric power companies satisfy a governmental standard on environmental protection. The proposed approach is applied to evaluate the performance of coal-fired power plants in the United States. This study finds two policy implications. First, power plants operated by bituminous coal (i.e., black coal) outperform those with sub-bituminous coal (i.e., brawn coal). The result implies that power plants with sub-bituminous coal should be replaced by bituminous coal. Second, the undesirable congestion, due to a line limit between points of power generation and consumption, may occur on most of coal-fired power plants. In contrast, desirable congestion, due to eco-technology innovation, may occur on a limited number of power plants. Thus, the identification of desirable congestion assists us in selecting which technology, or the type of power plant, should be invested to facilitate eco-technology innovation and its related engineering management for a future sustainable economic growth.     

Optimal generation and reserve dispatch in a multi-area competitive market using a hybrid direct search method

With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator’s bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market.     

Identification of congestion and valuation of transport infrastructures in the European natural gas market

Rising import dependency, increasing market liberalization and cross-border trade and security of supply fears facilitate investments in natural gas supply infrastructures in Europe. In order to ensure an efficient allocation of capital resources, it is important to identify congestion in the existing system and investment requirements based on economic principles. This paper first outlines an analytical framework for the identification of bottlenecks and the evaluation of transport capacities and the cost of congestion based on nodal prices. Secondly, an infrastructure model of the European gas market with high temporal and spatial granularity which exhibits the characteristics of the theoretical model is introduced. Parameterizing the model with the existing infrastructure and applying a demand and supply scenario for the year 2015, congestion mark-ups between countries in Europe are estimated. This approach indicates potential bottlenecks which might arise within the next five years and quantifies their economic costs. With only some temporary congestion, physical market integration is found to be high in Western Europe. In Eastern Europe, severe bottlenecks are identified and discussed. Implications for efficient investment decisions arising from the findings are examined in the context of the theoretical considerations.     

Optimal model of congestion management in deregulated environment of power sector with promotion of renewable energy sources

In the competitive electricity market it becomes very much important to give special consideration for development of renewable energy sources (RESs) due to environmental and other social problems related with conventional generations. So this paper presents an optimal model of congestion management with special emphasis for promotion of RES in competitive electricity market. This paper presents a generalized optimal model of congestion management for deregulated power sector that dispatches the pool in combination with privately negotiated bilateral and multilateral contracts while maximizing social benefit. This model determines the locational marginal pricing (LMP) based on marginal cost theory. It also determines the size of non-firm transactions as well as pool demand and generations. Both firms as well as non-firm transactions are considered in this model. The proposed model has been applied to IEEE-30 bus test system with addition of some RES for analysis of the proposed model. The RES supplies its power to load either through the firm transaction or through power pool. The power from RES is not subjected to any curtailment in proposed model of congestion management.     

Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage

This paper presents a methodology to minimize the total cost of buying power from different energy producers including renewable energy generations particularly within the context of a microgrid. The proposed idea is primarily based on the controlled operation of a battery energy storage system (BESS) in the presence of practical system constraints coupled with our proposed cost optimization algorithm. The complex optimization problem with constraints has been solved using the well-known concept of dynamic programming. The methodology has been assessed using actual power and price data from six different power generation sites and cost reduction has been calculated for a number of BESSs by varying their energy and power capacities. Twofold benefits of the proposed methodology lie in minimizing the total cost along with the constraint-based efficient operation of the BESS. Simulation results depict that the given power demand at a particular region can be fulfilled properly at all times using a BESS and multiple power generation.     

A methodological note on the evaluation of new technologies: the case of coal gasification

The traditional methodology of engineering cost analysis employed in the evaluation of emerging technologies implicitly assumes an economic independence between output and factor markets. For certain processes currently under investigation in the energy area (e.g. coal gasification), this assumption is violated. As a result, a bias is introduced into the process evaluation procedure by use of the conventional methodology. This paper proposes and demonstrates a simple revised methodology that incorporates an economic analysis of the relevant cross-market price effect with the engineering cost results to correct this bias.     

Price regimes in an energy island: Tacit collusion vs. cost and network explanations

In this paper, we explore the determinants of wholesale electricity prices in an energy island such as Sicily, by estimating regime switching models with fixed and time-varying transition probabilities on daily data in the 2012–2014 period. Explanatory variables used alternatively in the price equation and in the switching equation include power demand, the supply of intermittent renewables, the residual supply index, and a congestion indicator. Four competing hypotheses on the determinants of price regimes are tested (arbitrary market power, cost profile, tacit collusion, congestion) in order to understand why, despite the general trend of declining prices induced by renewables in southern Italy, Sicilian prices stood high. The pattern of estimated coefficients is consistent with a tacit collusion story.     

Adding wind power to a wind-rich grid: Evaluating secondary suitability metrics

As the quantity of renewable electricity generation from wind farms increases in a region, the costs associated with integrating it into the broader electricity system also grow. This is primarily due to the need for dispatchable generators that vary power output to compensate for wind farm power variations. Such “balancing services” are an economic cost to the system that is typically not passed on to wind farms. We propose including the use of technical merits other than capacity factor and cost of energy for evaluating new wind farm sites and present a new graphical geospatial method, with the intention of identifying sites that minimize the need for additional electricity balancing service and transmission congestion. Specifically, locations with low correlation to existing wind farms, locations with high correlation to load, locations with high characteristic power time-shift from existing wind farms, and locations that relieve or do not negatively impact electricity transmission congestion are identified. A geospatial Venn diagram-based method of visualization is presented. These methods will equip regional planners with new tools to encourage wind farm development in areas that benefit the electricity grid beyond the lowest bid price.     

含高渗透率海上风电电网的DSSC优化配置与运行控制策略

随着海上风电并网规模的不断增大,高渗透率风电引起的线路潮流阻塞问题已成为制约风电并网规模的重要因素之一。针对高渗透率海上风电区域的输电线路阻塞问题,文章提出一种含高渗透率海上风电电网的分布式静态串联补偿器(DSSC)优化配置与运行控制策略。该策略包含两个阶段:第一阶段为考虑多场景下DSSC的优化配置,以线路阻塞程度最小为目标,确定DSSC的配置地点与容量;第二阶段为DSSC的运行控制,利用DSSC的潮流控制能力,优化调度系统中的发电机,降低系统运行成本,并考虑系统在出现风电水电高出力场景下DSSC的运行控制,从而提高系统可再生能源的消纳。仿真结果表明,与采用静态串联补偿器(SSSC)和不采用柔性交流输电(FACTS)设备相比较,所提策略可降低系统的运行成本,提高可再生能源的消纳水平。