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.     

Simulation of current pricing-tendencies in the German electricity market for private consumption

The German electricity market for private consumption is characterized by increasing prices and low participation of the consumers. This prompts us to investigate the interdependencies between the customers’ engagement in the market and the suppliers’ pricing strategies. Based on an analysis of the German retail market, an agent-based simulation model is developed. Whereas the behaviour of private customers is calibrated on field data, the suppliers learn to maximize profits with a feedback-learning heuristic. The simulation results show a tendency of rising prices, which are created without the assumption of tacit collusion among suppliers. We conclude that in Germany the current market pressure of private customers may not be a sufficient incentive for suppliers to lower electricity prices.     

A critical survey of agent-based wholesale electricity market models

The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed.     

Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market

An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration.     

An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation

In this paper, an innovative model of agent based simulation, based on Ant Colony Optimization (ACO) algorithm is proposed in order to compare three available strategies of clearing wholesale electricity markets, i.e. uniform, pay-as-bid, and generalized Vickrey rules. The supply side actors of the power market are modeled as adaptive agents who learn how to bid strategically to optimize their profit through indirect interaction with other actors of the market. The proposed model is proper for bidding functions with high number of dimensions and enables modelers to avoid curse of dimensionality as dimension grows. Test systems are then used to study the behavior of each pricing rule under different degrees of competition and heterogeneity. Finally, the pricing rules are comprehensively compared using different economic criteria such as average cleared price, efficiency of allocation, and price volatility. Also, principle component analysis (PCA) is used to rank and select the best price rule. To the knowledge of the authors, this is the first study that uses ACO for assessing strategies of wholesale electricity market.     

Short-term optimal wind power generation capacity in liberalized electricity markets

Mainly because of environmental concerns and fuel price uncertainties, considerable amounts of wind-based generation capacity are being added to some deregulated power systems. The rapid wind development registered in some countries has essentially been driven by strong subsidizing programs. Since wind investments are commonly isolated from market signals, installed wind capacity can be higher than optimal, leading to distortions of the power prices with a consequent loss of social welfare. In this work, the influence of wind generation on power prices in the framework of a liberalized electricity market has been assessed by means of stochastic simulation techniques. The developed methodology allows investigating the maximal wind capacity that would be profitably deployed if wind investments were subject to market conditions only. For this purpose, stochastic variables determining power prices are accurately modeled. A test system resembling the size and characteristics of the German power system has been selected for this study. The expected value of the optimal, short-term wind capacity is evaluated for a considerable number of random realizations of power prices. The impact of dispersing the wind capacity over statistical independent wind sites has also been evaluated. The simulation results reveal that fuel prices, installation and financing costs of wind investments are very influential parameters on the maximal wind capacity that might be accommodated in a market-based manner.     

An economic welfare analysis of demand response in the PJM electricity market

We analyze the economic properties of the economic demand-response (DR) program in the PJM electricity market in the United States using DR market data. PJM's program provided subsidies to customers who reduced load in response to price signals. The program incorporated a “trigger point”, at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved introduce distortions into the market. We simulate demand-side bidding into the PJM market, and compare the social welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, we estimate that the social welfare gains exceed the distortions introduced by the subsidies. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment. We estimate that the socially optimal range for the incentive trigger point would be $66–77/MWh.     

Biofuels policy and the US market for motor fuels: Empirical analysis of ethanol splashing

Low ethanol prices relative to the price of gasoline blendstock, and tax credits, have resulted in discretionary blending at wholesale terminals of ethanol into fuel supplies above required levels—a practice known as ethanol splashing in industry parlance. No one knows precisely where or in what volume ethanol is being blended with gasoline and this has important implications for motor fuels markets: Because refiners cannot perfectly predict where ethanol will be blended with finished gasoline by wholesalers, they cannot know when to produce and where to ship a blendstock that when mixed with ethanol at 10% would create the most economically efficient finished motor gasoline that meets engine standards and has comparable evaporative emissions as conventional gasoline without ethanol blending. In contrast to previous empirical analyses of biofuels that have relied on highly aggregated data, our analysis is disaggregated to the level of individual wholesale fuel terminals or racks (of which there are about 350 in the US). We incorporate the price of ethanol as well as the blendstock price to model the wholesaler's decision of whether or not to blend additional ethanol into gasoline at any particular wholesale city-terminal. The empirical analysis illustrates how ethanol and gasoline prices affect ethanol usage, controlling for fuel specifications, blend attributes, and city-terminal-specific effects that, among other things, control for differential costs of delivering ethanol from bio-refinery to wholesale rack.     

Cost/benefit analysis of transmission grid expansion to enable further integration of renewable electricity generation in Austria

This paper elaborates on the costs and benefits of expanding the Austrian transmission system and the implementation of innovative grid-impacting technologies (e.g. flexible AC transmission systems (FACTS), dynamic line rating (DLR)) to support further integration of renewable energy sources for electricity generation (RES-E). Therefore, a fundamental market model has been developed - respecting DC load flows - and applied for analysing different future scenarios, notably for the time horizon 2020, 2030 and 2050. Up to 2020 and 2030, special focus is put on the finalisation of the so-called “380 kV-level transmission ring” in Austria to enable enhanced RES-E integration. The results confirm that transmission power line expansion in the states of Salzburg and Carinthia is important to connect imports from Germany with pumped hydro storage capacities, on the one hand, and the wind farms in the east with the pumped hydro storages in the western part of Austria, on the other hand. For 2050, the results indicate that the implementation of FACTS and DLR can reduce RES-E curtailment significantly.     

The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany

The German feed-in support of electricity generation from renewable energy sources has led to high growth rates of the supported technologies. Critics state that the costs for consumers are too high. An important aspect to be considered in the discussion is the price effect created by renewable electricity generation. This paper seeks to analyse the impact of privileged renewable electricity generation on the electricity market in Germany. The central aspect to be analysed is the impact of renewable electricity generation on spot market prices. The results generated by an agent-based simulation platform indicate that the financial volume of the price reduction is considerable. In the short run, this gives rise to a distributional effect which creates savings for the demand side by reducing generator profits. In the case of the year 2006, the volume of the merit-order effect exceeds the volume of the net support payments for renewable electricity generation which have to be paid by consumers.     

An agent-based model to study market penetration of plug-in hybrid electric vehicles

A spatially explicit agent-based vehicle consumer choice model is developed to explore sensitivities and nonlinear interactions between various potential influences on plug-in hybrid vehicle (PHEV) market penetration. The model accounts for spatial and social effects (including threshold effects, homophily, and conformity) and media influences. Preliminary simulations demonstrate how such a model could be used to identify nonlinear interactions among potential leverage points, inform policies affecting PHEV market penetration, and help identify future data collection necessary to more accurately model the system. We examine sensitivity of the model to gasoline prices, to accuracy in estimation of fuel costs, to agent willingness to adopt the PHEV technology, to PHEV purchase price and rebates, to PHEV battery range, and to heuristic values related to gasoline usage. Our simulations indicate that PHEV market penetration could be enhanced significantly by providing consumers with ready estimates of expected lifetime fuel costs associated with different vehicles (e.g., on vehicle stickers), and that increases in gasoline prices could nonlinearly magnify the impact on fleet efficiency. We also infer that a potential synergy from a gasoline tax with proceeds is used to fund research into longer-range lower-cost PHEV batteries.     

Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market

It is commonly known that wholesale spot electricity markets exhibit high price volatility, strong mean-reversion and frequent extreme price spikes. This paper employs a basic stochastic model, a mean-reverting model and a regime-switching model to capture these features in the Australian national electricity market (NEM), comprising the interconnected markets of New South Wales, Queensland, South Australia and Victoria. Daily spot prices from 1 January 1999 to 31 December 2004 are employed. The results show that the regime-switching model outperforms the basic stochastic and mean-reverting models. Electricity prices are also found to exhibit stronger mean-reversion after a price spike than in the normal period, and price volatility is more than fourteen times higher in spike periods than in normal periods. The probability of a spike on any given day ranges between 5.16% in NSW and 9.44% in Victoria.     

Policy changes and the dynamics of capacity expansion in the Swiss electricity market

Capacity of supply is a crucial matter in electricity markets as it directly influences reliability of supply, price volatility and blackout risk. In this paper, we analyse the dynamics of capacity expansion in the Swiss electricity market and the impact of different policies such as nuclear phaseout and management of electricity exchanges – imports and exports – policies. This article develops the conceptualization model presented in [Ochoa, P., 2007b. Policy changes in the Swiss electricity market: a system dynamics analysis of likely market responses. Socio-Economic Planning Sciences 41 (4):336–349.]. We build a system dynamics model based on the dynamics of capacity expansion explained in the latter paper and present and analyse different scenarios. We conclude that international electricity exchanges are important for the Swiss market as they help to lower costs and to increase the income of the utility companies; however, we illustrate the need for explicit policies for managing imports and exports of electricity to avoid import dependence from neighbouring countries.     

Industrial customer response to wholesale prices in the restructured Texas electricity market

This paper estimates the demand responsiveness of the 20 largest industrial energy consumers in the Houston area to wholesale price signals in the restructured Electric Reliability Council of Texas (ERCOT) market. Statistical analysis of their load patterns employing a Symmetric Generalized McFadden cost function model suggests that ERCOT achieved limited success in establishing a market that facilitates demand response from the largest industrial energy consumers in the Houston area to wholesale price signals in its second year of retail competition. The muted price response is at least partially because energy consumers who opt to offer their “interruptibility” to the market as an ancillary service are constrained in their ability to respond to wholesale energy prices.     

Market power in the Nordic electricity wholesale market: A survey of the empirical evidence

We review the recent empirical research assessing market power on the Nordic wholesale market for electricity, Nord Pool. The studies find no evidence of systematic exploitation of system level market power on Nord Pool. Local market power arising from transmission constraints seems to be more problematic in some price areas across the Nordic countries. Market power can manifest itself in a number of ways that have so far escaped empirical scrutiny. We discuss investment incentives, vertical integration and buyer power, as well as withholding of base-load (nuclear) capacity.     

Price formation and market power in the German wholesale electricity market in 2006

From 2002 to 2006, German wholesale electricity prices more than doubled. The purpose of this paper is to estimate the price components in 2006 in order to identify the factors responsible for the increase. We develop a competitive benchmark model, taking into account power plant characteristics, fuel and CO₂-allowance prices, wind generation, cross-border flows, unit commitment, and startup conditions, to estimate the difference between generation costs and observed market prices for every hour in 2006. We find that prices at the German wholesale market (European Energy Exchange—EEX) are above competitive levels for a large fraction of the observations. We verify the robustness of the results by carrying out sensitivity analyses. We also address the issue of revenue adequacy.     

Coordinated generation and transmission expansion planning in deregulated electricity market considering wind farms

This paper deals with a coordinated generation expansion planning (GEP)–transmission expansion planning (TEP) in competitive electricity market. In the proposed method, GEP and TEP are performed at the same time, with consideration of wind farm uncertainty. The uncertainty is modeled by normal probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to include the uncertainty into the problem. The planning is managed for two master and slave levels. At slave level, all generation company (GENCO) and transmission company (TRANSCO) maximize their profit and then at master level, the system constraints are checked by independent system operator (ISO). In other words, the proposed planning aims at maximizing the expected profit of all GENCOs and TRANSCOs, while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). The proposed problem is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs and TRANSCOs profit in the presence of wind farm uncertainty under electricity market.     

Market power analysis for the Iranian electricity market

The market power problem in Iranian electricity market is addressed in this study. This paper by using various structural indices of market power and reviewing market results analyzes the intensity of competition in Iran’s electricity market and examines whether this market is functioning at an appropriate level of efficiency. In this article the most well-known indices of market power are calculated in two approaches for two different scenarios (current situation and future outlook of generation sector’s ownership in Iran’s power industry). Comparing the results of these scenarios promises more competitive market for the second scenario. Calculating Residual Supply Index for Iran’s power market shows despite admissible values of concentration ratios, due to supply scarcity during periods when the demand is close to the total available capacity, some suppliers can exercise market power even with a relatively small market share. The most important price and load indices like weighted average prices and load/price duration curves of Iranian electricity market during March 2007–March 2008 are also analyzed in this paper. These results imply the existence of economic withholding. The main limiting factors of competition and significant implemented countermeasures for market power mitigation in Iran’s electricity market are also mentioned.     

Government procurement of peak capacity in the New Zealand electricity market

This paper analyzes the impact of government procurement of reserve electricity generation capacity on the long-run equilibrium in the electricity market. The approach here is to model the electricity market in a context where the supply companies have market power. The model is then used to analyze the impact of government direct supply of peak capacity on the market. We find that the firms build less peak-generation capacity when the government procures peak generating capacity. The long-run equilibrium with N firms and government capacity of K_G results in an increase of total peak generation capacity of K_G/(N+1) compared to the long-run equilibrium with no government capacity. Supply disruptions of baseline capacity during the peak time period are also considered. It is found that peak prices do not go up any further with (anticipated) supply disruptions. Instead the entire cost of the extra peakers is borne by customers on traditional meters and off-peak customers who face real-time pricing.     

Towards a competitive market for electricity and consumer choice in the Indian power sector

The initial phase of reforms in the Indian power sector was primarily aimed at bringing regulatory reforms and unbundling of the vertically integrated State Electricity Boards (SEBs). Enactment of the Electricity Act 2003 led to deepening of the reform process by dismantling this monopoly in the power sector. Primary issues emerging on account of transition from a single-buyer model to a multi-buyer multi-seller model include, among others, policy and regulatory initiatives related to open access, power exchanges, and transmission allocation and its pricing. The paper provides an overview of the status of competition in various segments of the power sector. It also reviews the phased program for open access outlined by various State Electricity Regulatory Commissions, including their status and impact on competition. The paper highlights a number of residual issues for the wholesale and retail competition, and also discusses the approach to address the same. These include liberalization of fuel markets, market monitoring, unbundling of retail tariffs, universal service obligation, supplier of last resort and demand response.