Session 03: Electricity Market Simulation and Modeling (1)
Short Term Constraints for a Long Term Energy and Reserve Market Equilibrium Simulation
Universidad Pontificia Comillas
The increasing penetration of interruptible sources of energy is making security of supply a key aspect of present and future networks management, and reserves markets are gaining significant relevance. Demand representation used in traditional long term market models normally consists in a set of non chronological demand levels corresponding to hours with similar demand values. However, reserve issues are closely related with short term constraints (such as ramps), and this lack of chronological coupling does not allow for an appropriate representation of these technical constraints.
This paper presents a joint energy and reserve conjectural equilibrium model that provides signal prices for both commodities and computes productions accordingly by satisfying system demand and reserve requirements. Generation is represented at a technological level, and water contributes to energy and reserve requirements with daily constraints. To reduce the feasible region, clustering is used to simplify hourly demand series into only a few daily patterns. In addition, keeping the link between hours and demand levels allows the model to combine short term technical constraints with traditional long term strategic planning constraints.
Efficiency of Continuous Double Auctions in the Electricity Market
1EnBW Transportnetze AG, Germany; 2Risø DTU National Laboratory for Sustainable Energy, Denmark
Intra-day electricity markets are considered as important mechanisms to reconcile short-term fluctuations of energy production with consumption. This even gains in significance in systems with heavy intermittent production at virtually no variable costs, such as wind energy. In Europe, intra-day markets are often designed as continuous double auctions where bid and ask orders are collected continuously, ranked by price and time of arrival. Although this market type can be considered as delivering more or less efficient results, the trading process itself is time-consuming. This poses the question whether continuous markets yield comparably good results when flexibility of market participants to change their schedules at short notice is costlier than having changed them earlier. We apply an extended zerointelligent- trader simulation model to assess the impact of costly flexibility on market outcomes. We find that costly flexibility with a correspondig demand for flexibility may negatively affect the efficiency of continuous double auctions. For the energy market, this could imply that the markets’ ability to exploit flexibility is systematically limited.
Agent-based Simulation of New Energy Markets
FTW Forschungszentrum Telekommunikation Wien GmbH, Austria
This paper presents a simulation framework that is being developed to evaluate possible setup of an electricity market which includes grid-agile customers who trade their capability to control their load or offer energy from their renewable sources. The framework is based on the multi-agent technology with agents presenting the building blocks for realization of different market actors.
Bilateral Electricity Market Theory based on Conjectural Variation Equilibria
Brunel University, United Kingdom
The growth of electricity markets and evolution of electricity utility systems around the world towards a competitive environment have aroused considerable interest in the investigation of mechanisms for trading electricity, especially in such an environment that participants compete in both spot market bidding and bilateral contract trading. Equilibrium models using a Conjectural Variation (CV) approach to optimize the participants' behaviors in oligopolistic and oligopsonistic market frameworks have been represented. CV will provide the constituents of an electricity market with an expectation of how their rivals will react to their behavior changes. This paper reviews the bilateral electricity market structure, such as the UK electricity market (BETTA), analyses the conjectural equilibrium formula for both generation side and demand side markets. The paper shows how the generators and suppliers can self-dispatch and manage their contracts to meet demand in a double-sided market to reach equilibrium using a hierarchical optimization method.
A Method for Calibration of a Fundamental Model of Electricity Price
1Elektro Ljubljana, d.d.; 2University of Ljubljana, Slovenia
In the liberalized electricity markets, the utilities need the right model to forecast the stochastic behavior of electricity market prices. The models range from quantitative models, cost-based models, economic equilibrium models, agent-based models, experimental models, and fundamental models determining the stochastic properties of electricity prices.
The focus of the investigation was to calibrate a fundamental model using actual data on electricity price and load from the European Energy Exchange EEX. Stationarity of historical data was ascertained using the Dickey-Fuller test. The calibration entailed the use of principal component analysis and a linear regression model in conjunction with Kalman filter and maximum likelihood method. Using the calibrated model, the electricity price for year 2011 and 2012 was simulated. The results of simulations were compared with the results obtained with the method of moving average and advantages and disadvantages of the fundamental method were considered.
An Agent Based Game Theory Approach to Analysing Constrained Electricity Markets
University of Birmingham, United Kingdom
Game Theory is a long standing method of analysing the way in which participants interact within a market space, recently agent based approaches have been utilised to understand even more about these interactions. This agent based approach can be utilised to understand very complex market designs, such as those for an electricity market, with there being potential room for identifying potential problems with market power.
By looking at the way in which a set of intelligent agents form optimal bids in a constrained electricity market, it is possible to identify where potential weaknesses are in the market design. Agents simulate the market repeatedly, aiming to find the Nash- Equilibrium point for the the market at the given time step. By predicting other agents reactionary moves, they can identify the best course of action, with this information it is possible to identify the contributing factors that have caused the agent’s choice of action. As such, this work sets out to identify where and when an electricity market can be forced into undesirable situations, only as a result of optimised bidding and existing market constraints.