Impact of unplanned power flows in interconnected transmission systems – Case study of Central Eastern European region

The unplanned power flows at the interconnections of the Central Eastern Europe and Central Western Europe electricity markets are assessed. The assessment is accomplished using optimal power flow simulations of the linked transmission systems of Germany, Poland, the Czech Republic, Austria and Switzerland. The unplanned flows are modeled using a multivariate model that is a function of time series of wind- and solar-generated electricity, power demand and commercial power flows. It is shown that for the case of Poland there is a 25% higher loading on sections of transmission grid in Poland due to the unplanned flows. The unplanned power flows are largely a consequence of the wind-generated electricity in northern Germany that must be routed to southern Germany through the grid in Central Eastern Europe region due to an inadequate grid capacity along the north–south German corridor. It is shown without the planned 2020 developments of the grid, Poland's grid will be very susceptible to congestion and destabilization.     

Strategic bidding and rebidding in electricity markets

Successful deregulation in electricity markets depends crucially on the ability of market regulation to promote and maintain free competition. There are, however, important physical characteristics in electricity markets, such as the constraints imposed by the physical transmission infrastructure, that have the potential to undermine competition and provide opportunities for market participants to exploit temporary positions of market power. In this paper, the regional market of Queensland, Australia is analysed. It is found that strategic behaviour by generators exists and is closely related to the occurrence of the kind of extreme price events that characterise many deregulated electricity markets. In addition, rebidding behaviour by base-load generators immediately after extreme price events is shown to have negative impacts on the operation of the market. The key message is that promotion of competition in electricity markets can have undesirable consequences unless the regulatory policy is carefully designed to counter strategic behaviour by market participants.     

Impact of the German nuclear phase-out on Europe's electricity generation—A comprehensive study

The combination of the ambitious German greenhouse gas reduction goals in the power sector and the nuclear phase-out raises many questions concerning the operational security of the German electricity generation system. This paper focusses on the technical feasibility (electricity generation and transmission) and CO₂-impact of the German nuclear phase-out on the short term (2012–2022).A detailed electricity generation simulation model is employed, including the German transmission grid and its international connections. A range of different conventional and renewable energy sources (RES) scenarios is considered. Results are presented for the change in generation mix, on the flows on the transmission network and on operational reliability issues.The scenario analysis shows that nuclear generation will be replaced mainly by coal- and lignite-based generation. This increases the CO₂-intensity of the German electricity sector. Furthermore, the results indicate that the German electricity export will decrease and under certain circumstances, the system becomes infeasible. Keeping some nuclear power plants online, would mitigate these effects. The amount of electricity generated from RES is shown to be the main driver for grid congestion.     

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.     

Measuring the competitiveness benefits of a transmission investment policy: The case of the Alberta electricity market

Transmission expansions can increase the extent of competition faced by wholesale electricity suppliers with the ability to exercise unilateral market power. This can cause them to submit offer curves closer to their marginal cost curves, which sets market-clearing prices closer to competitive benchmark price levels. These lower wholesale market-clearing prices are the competitiveness benefit consumers realize from the transmission expansion. This paper quantifies empirically the competitiveness benefits of a transmission expansion policy that causes strategic suppliers to expect no transmission congestion. Using hourly generation-unit level offer, output, market-clearing price and congestion data from the Alberta wholesale electricity market from January 1, 2009 to July 31, 2013, an upper and lower bound on the hourly consumer competitiveness benefits of this transmission policy is computed. Both of these competitiveness benefits measures are economically significant, which argues for including them in transmission planning processes for wholesale electricity markets to ensure that all transmission expansions with positive net benefits to electricity consumers are undertaken.     

Transmission capacities and competition in Western European electricity market

The integration of national electricity markets into a single European one is expected to reduce the ability of dominant players to exercise market power. This paper investigates whether or not existing transmission capacities of cross-border interconnectors are sufficient to achieve this result and create vigorous competition in the market. A model with two decision levels is used. On the first level profit maximizing generators play Cournot game against each other. On the last level the system operator clears the market and determines flows in the network to maximize social welfare subject to a set of physical constraints. As each strategic generator anticipates her impact on equilibrium prices and congestion in the system, her optimization problem is subject to equilibrium constraints from the system operator's problem.The analysis demonstrates that interconnector capacities in Western Europe are insufficient for integration alone to reduce the exercise of market power. I compare several possible competition-enhancing policies: expansion of interconnectors and different scenarios of national markets’ restructuring. I show that although increase of line capacity is a useful tool to stimulate competition in an integrated market, it is not a substitute for the restructuring of large players.     

Real-world market representation with agents

As power markets are relatively new and still continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of electricity markets over time and how market participants may act and react to the changing economic, financial and regulatory environments in which they operate. A new and rather promising approach is to model the electricity market as a complex adaptive system using an agent-based modeling and simulation (ABMS) approach. The purpose of an ABMS model is not necessarily to predict the outcome of a system but to reveal and understand the complex and aggregate system behaviors that emerge from the interactions of the heterogeneous individual entities. Emergent behavior is a key feature of ABMS and is not easily inferred from the simple sum of the behavior of its components. By relying on both established engineering modeling techniques as well as advanced quantitative economic market principles, the ABMS approach is uniquely suited to addressing the strategic issues of interest to different market participants as well as those of market monitors and regulators.     

A Mixed Integer Linear Programming model of a zonal electricity market with a dominant producer

We consider a liberalized electricity market, divided in zones interconnected by capacitated transmission links, where a large dimensional power producer operates. We introduce a model for determining the optimal bidding strategies of the large dimensional producer, so as to maximize his own market share, while guaranteeing an annual profit target and satisfying technical constraints. The model determines the optimal medium-term resource scheduling and yields the hourly zonal electricity prices, as it includes constraints representing the Market Clearing process. In order to compute the global solution, the complementarity conditions are formulated as mixed integer linear constraints and the revenue terms are expressed by piece-wise linear functions. The model can be used for analyzing the behavior of market prices in electricity markets where a large dimensional producer can exert market power. It can also be used by investors as a simulation tool for evaluating both the impact on the market and the profitability of investment decisions in the zonal electricity market. A case study related to the Italian electricity market is discussed.     

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.     

考虑内部多地区间交互协作的复杂省级电力市场交易优化决策

为实现电力市场大范围资源优化配置,提出了一种考虑内部多地区间交互协作的省级电力市场交易优化决策方法.首先介绍了市场交易架构和机制,同时以全省社会福利和跨地区交易电量最大化为出清目标,其中社会福利计及了线路的输配电成本.然后,优化决策中考虑了全省各地区内部的电网安全约束、供热机组运行约束和交易决策约束等多约束条件,并对地...     

Convergence bids and market manipulation in the California electricity market

Financial instruments are designed to improve the efficiency of a physical market in theory. In practice, underlying physical relationships may prevent financial instruments from working as intended. This paper analyzes the relationship between two financial instruments in electricity markets: convergence bidding and congestion revenue rights. Convergence bids allow participants to trade virtual power, whereas congestion revenue rights capture the value of congestion on a transmission line. Both instruments were introduced to solve inefficiencies, however the interaction of these two instruments provides incentives for manipulation. In this work I test whether the financial instruments are being used as intended. The results show that electricity market participants are more likely to hold unprofitable convergence bids on a node where the convergence bid can benefit the value of the congestion revenue rights held at that node. This type of uneconomic convergence bid is consistent with manipulative behavior. I then perform a back of the envelope calculation that shows these potentially manipulative convergence bids create inefficiencies in the market.     

Demand response resources: Who is responsible for implementation in a deregulated market?

Demand response resources (DRR) have potential to offer substantial benefits in the form of improved economic efficiency in wholesale electricity markets. Those benefits include better capacity factors for existing capacity, reductions in requirements for new capacity, enhanced reliability, relief of congestion and transmission constraints, reductions in price volatility, mitigation of market power and lower electricity prices for consumers. However, DRR has been slow to penetrate. There has been substantial disagreement as to which entities in a restructured market should promote the expanded implementation of DRR. This paper contends that no single entity can perform this function. But rather, wider implementation will need to accrue from coordinated actions along the electricity supply chain.     

Optimal bidding strategy in a competitive electricity market based on agent-based approach and numerical sensitivity analysis

The objective of this study is to present a new method for determination of the optimal bidding strategies among generating companies (GenCo) in the electricity markets using agent-based approach and numerical sensitivity analysis (NSA). While agent-based approach provides for decision making, NSA can help with identifying the critical control points that lead to proper decisions to be taken by GenCos. To achieve the objective, the pricing mechanism used for settling the electricity market and determining the GenCos rewards is locational marginal pricing (LMP) and the sensitivity of each GenCo reward with respect to its bid is analyzed, then, the optimal strategy is determined. An example and a case study are used to illustrate the efficiency of the proposed method. The LMPs and allocated generations of GenCos show that the proposed method leads GenCos to learn a strategic manner and, as a result, increase prices and maximize their rewards. To validate the proposed method, the results from this study are compared with those available in the literature. The comparison of results shows an improved simulation time by 8.16 percent and total reward of market by 2.46 percent.     

Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles

Plug-in electric vehicles (PEVs) are expected to balance the fluctuation of renewable energy sources (RES). To investigate the contribution of PEVs, the availability of mobile battery storage and the control mechanism for load management are crucial. This study therefore combined the following: a stochastic model to determine mobility behavior, an optimization model to minimize vehicle charging costs and an agent-based electricity market equilibrium model to estimate variable electricity prices. The variable electricity prices are calculated based on marginal generation costs. Hence, because of the merit order effect, the electricity prices provide incentives to consume electricity when the supply of renewable generation is high. Depending on the price signals and mobility behavior, PEVs calculate a cost minimizing charging schedule and therefore balance the fluctuation of RES. The analysis shows that it is possible to limit the peak load using the applied control mechanism. The contribution of PEVs to improving the integration of intermittent renewable power generation into the grid depends on the characteristic of the RES generation profile. For the German 2030 scenario used here, the negative residual load was reduced by 15–22% and the additional consumption of negative residual load was between 34 and 52%.     

Support schemes for renewable electricity in the European Union: Producer strategies and competition

Current discussion about how to reform European support schemes for renewable electricity neglects certain risks of market power in wholesale electricity markets. In a stylized Cournot model of interacting spot and forward electricity markets, I analyze how different price-based support schemes affect producer strategies and, ultimately, competition in the wholesale market. I compare the strategic behavior of renewable and conventional producers in terms of electricity production and forward market sales in the presence of two different price-based support schemes: feed-in tariffs and feed-in premiums. I show that the feed-in premium, which is the European Commission's current scheme of choice, may enhance market power and favor conventional electricity production. It may also reduce the likelihood of achieving the political objective to increase production from renewable energy sources.     

Congestion management rules and trading strategies in the Spanish electricity market

This paper analyses the economic incentives embodied in the rules governing the resolution of transmission constraints in the Spanish wholesale electricity market and the way these incentives may have influenced on the trading behaviour of both the generators and the demand side. The evidence obtained is consistent with them responding to these incentives. In particular, buyers would respond to the way congestion costs are billed to them by abandoning the daily market in favour of the intraday market as far as possible. Additionally, some strategic generators may have been prompted the system operator to require them to inject electricity into the system to solve network congestions. Finally, these results may contribute to shed light on what should be expected of the reform in the aforementioned rules.     

Evaluating the efficiency of divestiture policy in promoting competitiveness using an analytical method and agent-based computational economics

Choosing a desired policy for divestiture of dominant firms’ generation assets has been a challenging task and open question for regulatory authority. To deal with this problem, in this paper, an analytical method and agent-based computational economics (ACE) approach are used for ex-ante analysis of divestiture policy in reducing market power. The analytical method is applied to solve a designed concentration boundary problem, even for situations where the cost data of generators are unknown. The concentration boundary problem is the problem of minimizing or maximizing market concentration subject to operation constraints of the electricity market. It is proved here that the market concentration corresponding to operation condition is certainly viable in an interval calculated by the analytical method. For situations where the cost function of generators is available, the ACE is used to model the electricity market. In ACE, each power producer’s profit-maximization problem is solved by the computational approach of Q-learning. The power producer using the Q-learning method learns from past experiences to implicitly identify the market power, and find desired response in competing with the rivals. Both methods are applied in a multi-area power system and effects of different divestiture policies on market behavior are analyzed.     

Germany's nuclear power plant closures and the integration of electricity markets in Europe

This paper examines the potential implications of national policies that lead to a sudden increase of wind power in the electricity mix for interconnected European electricity markets. More specifically, it examines market integration before and after the closures of eight nuclear power plants that occurred within a period of a few months in Germany during 2011. The short- and- long run interrelationships of daily electricity spot prices, from November 2009 to October 2012, in: APX-ENDEX, BELPEX, EPEX-DE, EPEX-FR, NORDPOOL, OMEL and SWISSIX; and wind power in the German system are analysed. Two MGARCH (Multivariate Generalized Autoregressive Conditional Heteroscedasticity) models with dynamic correlations are used to assess spot market behaviour in the short run, and a fractional cointegration analysis is conducted to investigate changes in the long-run behaviour of electricity spot prices. Results show: positive time-varying correlations between spot prices in markets with substantial shared interconnector capacity; a negative association between wind power penetration in Germany and electricity spot prices in the German and neighbouring markets; and, for most markets, a decreasing speed in mean reversion.     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

Interaction among competitive producers in the electricity market: An iterative market model for the strategic management of thermal power plants

The liberalization of the electricity sector requires utilities to develop sound operation strategies for their power plants. In this paper, attention is focused on the problem of optimizing the management of the thermal power plants belonging to a strategic producer that competes with other strategic companies and a set of smaller non-strategic ones in the day-ahead market. The market model suggested here determines an equilibrium condition over the selected period of analysis, in which no producer can increase profits by changing its supply offers given all rivals’ bids. Power plants technical and operating constraints are considered. An iterative procedure, based on the dynamic programming, is used to find the optimum production plans of each producer. Some combinations of power plants and number of producers are analyzed, to simulate for instance the decommissioning of old expensive power plants, the installation of new more efficient capacity, the severance of large dominant producers into smaller utilities, the access of new producers to the market. Their effect on power plants management, market equilibrium, electricity quantities traded and prices is discussed.