Bidding

About: Bidding is a research topic. Over the lifetime, 15371 publications have been published within this topic receiving 294233 citations. The topic is also known as: competitive bidding.

Comprehensive bidding strategies with genetic programming/finite state automata

Abstract: This research is an extension of the authors' previous work in double auctions aimed at developing bidding strategies for electric utilities which trade electricity competitively. The improvements detailed in this paper come from using data structures which combine genetic programming and finite state automata termed GP-Automata. The strategies developed by the method described here are adaptive-reacting to inputs-whereas the previously developed strategies were only suitable in the particular scenario for which they had been designed. The strategies encoded in the GP-Automata are tested in an auction simulator. The simulator pits them against other distribution companies (distcos) and generation companies (gencos), buying and selling power via double auctions implemented in regional commodity exchanges. The GP-Automata are evolved with a genetic algorithm so that they possess certain characteristics. In addition to designing successful bidding strategies (whose usage would result in higher profits) the resulting strategies can also be designed to imitate certain types of trading behaviors. The resulting strategies can be implemented directly in online trading, or can be used as realistic competitors in an off-line trading simulator.

Simulation and Pricing Mechanism Analysis of a Solar-Powered Electrical Microgrid

Abstract: A framework is proposed for an electrical power microgrid, such as for a colony or small township of homes that generate electrical power from solar energy and use it directly when possible, and via stored battery power at other times. The situation is described as a demand and supply problem in a multi-agent system with many consumers and suppliers and no explicit communication or coordination among the agents. Such a demand and supply problem is modeled as a Potluck Problem, a generalization of the Santa Fe Bar Problem. Power produced by PV panels and batteries may be used in the local market, in addition to being consumed locally. The proposed microgrid system model is able to determine the optimum operation of a solar-powered microgrid with respect to load demand, environmental requirements, PV panel and battery capacities. The results indicate the effect of various such parameters on the performance of these micro-grids. This paper also analyzes and proposes, based on auction theory, the most efficient and competing pricing mechanism in the proposed microgrid system model. Two important market bidding techniques, single bidding and discriminatory bidding, are considered. The microgrid is made to participate in the bidding process to serve the consumers at a reduced price and to provide better revenues. The viability of the model proposed is illustrated with analyses using realistic assumptions and published historical data.

A hierarchical energy management system for multiple home energy hubs in neighborhood grids

Abstract: This paper presents a hierarchical energy management system (HEMS) for multiple home energy hubs in the neighborhood grid (MHEHNG). The main objectives are maximizing financial profit and shaving the peak of upstream grid. This way, the proposed HEMS manages the energy generation and energy storing, as well as energy purchase/sale of each home energy hub (HEH) under the two levels including lower and upper levels. The lower level is responsible for supplying the internal load and reducing the energy cost in each HEH. The upper level is the central energy management system (CEMS) which is focused on forming a coalition between the local HEHs, as well as giving the tempting offers to increase the financial profit through a heuristic bidding strategy. The principle of proposed bidding strategy is based on weighted distributing of excess power among consumers that is one of the contribution of this paper. It leads to trading more energy at the lowest possible price. Determining the most appropriate operational scenario in each HEH requires the investigation of both technical and financial aspects. A novel scenario selector method has been proposed based on SOC-tariff plane. This is another contribution of this work. A simulator has been implemented in the MATLAB/GUI software environment to facilitate the evaluation of proposed HEMS performance. The simulation results indicate the effectiveness of the proposed HEMS. They show a decrease in the total energy cost of the CBs by almost 9.4%, and an increase in the total profit of the HEHs by 4.55%. Also, it was found out that the energy can be purchased from HEHs at varying rates and can be sold to the consumers at almost constant rates by using the proposed bidding strategy. This motivates HEHs to submit more power at lower tariffs to the CEMS.

Quantifying the supply-side benefits from forward contracting in wholesale electricity markets

Abstract: SUMMARY The assumption of expected profit-maximizing bidding behavior in a multi-unit, multi-period auction with step-function supply curves is used to estimate cost functions for electricity generation units and derive tests of expected profit-maximizing behavior. Applying these techniques to data from the National Electricity Market in Australia reveals statistically significant evidence of output-dependent marginal costs within and across half-hours of the day, but no evidence against the hypothesis of expected profit-maximizing behavior. These cost function estimates quantify the economic significance of output-varying costs and how forward financial contract obligations impact the amount of these costs the generation unit owner incurs. This supplier’s existing obligations imply average daily production costs that are 8% lower than the profit-maximizing pattern of output with no forward contract obligations. Copyright  2007 John Wiley & Sons, Ltd.

Econometric Analysis of 15-Minute Intraday Electricity Prices

Abstract: The trading activity in the German intraday electricity market has increased significantly over the last years. This is partially due to an increasing share of renewable energy, wind and photovoltaic, which requires power generators to balance out the forecasting errors in their production. We investigate the bidding behaviour in the intraday market by looking at both last prices and continuous bidding, in the context of a fundamental model. A unique data set of 15-minute intraday prices and intraday-updated forecasts of wind and photovoltaic has been employed and price bids are modelled by prior information on fundamentals. We show that intraday prices adjust asymmetrically to both forecasting errors in renewables and to the volume of trades dependent on the threshold variable demand quote, which reflects the expected demand covered by the planned traditional capacity in the day-ahead market. The location of the threshold can be used by market participants to adjust their bids accordingly, given the latest updates in the wind and photovoltaic forecasting errors and the forecasts of the control area balances.