Bidding Risk Research Articles

Modeling for wind-thermal combined bidding considering bilateral tail information

The stochastic output of wind power will lead to the penalty of bidding deviation in the spot market and bring bidding risk, restricting the participation of wind power in market competition. The combined bidding strategy for multiple power generation stakeholders can help alleviate the output uncertainty of wind power, reducing the bidding deviation penalty. This paper aims at the modeling method for wind-thermal combined bidding in the spot power market. Conditional value at risk (CVaR) is used to describe the bidding risk of the combined bidding. To better reflect the bidding risk, the bilateral tail information of the upper and lower deviations is modeled according to the revenue function. The uncertainties of wind power output and the clearing price in the day-ahead market are considered, and the risk decision-making model for wind-thermal combined bidding is established. The model is solved by the chaotic particle swarm optimization algorithm with constraint handling (EDFC-PSO). The results show that the proposed modeling method can describe the risk indicators in detail, providing a better reference for market bidding. Also, the combination of the wind farm and the thermal power unit can reduce the risk of wind power in bidding and improve its profitability in the day-ahead market. Besides, the risk speculation of the wind farm can be found when facing the inevitable increased risks. It means the behaviors of the market participants can be better explained using the proposed method in this paper.

Statistical methods as a tool to identify bid-rigging: the case of local authorities

Motivation: Disclosure of bid-rigging is not a trivial process. The main difficulty lies in the secrecy of such an agreement. Also, the signals of collusion can be ambiguous. It, therefore, appears that only a tiny percentage of such collusive agreements are disclosed. Of the disclosed conspiracies, a significant proportion was identified due to information from contracting authorities. We have a catalogue of indicators for collusion, and statistical methods are particularly effective. What is the role of statistical methods in revealing bid-rigging? What determines their use in practice? In order to answer these questions, a questionnaire study was carried out. The survey covered local government units — the dominating group of contracting authorities.
 Aim: The research aimed to identify the factors characterising local government units that foster statistical methods as a standard bid evaluation tool.
 Results: The survey results indicate that using a statistical method as standard practice in the process of bids evaluation is related to the level of staff’s professional expertise, the size of the procurement team and the size of the local authority. Concerning the risk of collusive bidding, respondents recognise it but believe that it does not significantly impact the achievement of procurement policy objectives. Despite a sense of responsibility for combating bid-rigging, respondents are reluctant to use statistical methods on a daily basis.

Profit Allocation Strategy of Virtual Power Plant Based on Multi-Objective Optimization in Electricity Market

A virtual power plant (VPP) can aggregate distributed renewable energy and flexible load to participate in the electricity market as a virtual controllable assembly. This pattern can effectively avoid the bidding risk of users, and produce cooperation benefits such as reducing transaction costs. Reasonable profit allocation is the key factor to determine the formation and survival of a VPP, which means a reasonable allocation for the VPP’s market income among participating members. In view of that, this paper proposes a framework of profit allocation in VPPs based on cooperative game theory. Aiming at the competitive environment with multiple VPPs in the electricity market, a VPP’s profit allocation model based on bidding optimization is built, which considers multiple objectives such as fairness of profit allocation, stability of cooperation alliance, and attraction of participating members. Furthermore, a multi-objective evolutionary optimization algorithm based on reference points is introduced to solve the model. Then, a VPP composed of prosumers is taken as an example to carry out the emulation. The results show that all participating members can get satisfactory profit allocation. Its cost-saving ratio ranges from 7.82% to 18.66%, and it confirms that the proposed profit allocation method can encourage prosumers of small size to participate in the VPP cooperation effectively.

Evaluation of bidding risk for wind farm construction projects

With the rapid development and expansion of wind power generation capacity in China, the risk of wind farm construction projects has been paid more and more attention. Based on the method of can-expandable element and multi-level fuzzy comprehensive evaluation method, this paper makes an empirical analysis of the bidding risk of the wind farm construction project of Xintiandi Energy Company in Hebei Province. The research shows that the can-expander element method is more accurate in risk evaluation because there are no different evaluation principles, which can provide effective support for decision makers.

Learning and pricing models for repeated generalized second-price auction in search advertising

In search advertising how much an advertiser is willing to pay for a click or tap on his search ad is private information, which hampers an ad seller’s ability to set the best reserve price to increase the revenue for the generalized second-price (GSP) auctions used to allocate ad slots. We present a series of learning and pricing models for repeated GSP auctions selling multiple heterogeneous items. This paper contributes to the literature in dynamic pricing with learning and complements the existing off-line studies on impact of the reserve price in the multi-billion dollar online advertising business. With few restrictions on the distribution function of the unknown parameter, algorithms are developed to estimate the empirical distribution function and determine the best reserve price to reduce the revenue loss (regret) over time. When bidders bid in the locally envy-free equilibrium, we present an algorithm that has the best attainable regret upper bound. When bidders do not bid in the locally envy-free equilibrium, we propose a GSP auction with position-specific reserve prices and develop an algorithm with the same regret bound to mitigate the risk of strategic bidding. With a high volatility involved, learning becomes more active while earning is more effective. When bidders coordinate bidding, the properly selected starting reserve prices can substantially reduce the revenue loss from possible collusive bidding behaviors.

Risk Evaluation of Bidding for Wind Farm Construction Project

With the rapid development and growth of the installed capacity of wind power generation in China, more and more attention has been paid to the risk of wind farm construction projects. Based on the extension element method and the multi-level fuzzy comprehensive evaluation method, this paper makes an empirical analysis on the bidding risk of the wind farm construction project of Xintiandi energy company in Hebei province. The research shows that the extensible matter element method can provide effective support for decision makers because there are no different evaluation principles and more accurate risk evaluation.

Effective Detection Engineering Cost Price Method Based on Entropy Proportion and Fuzzy Risk Evaluation

For low price bidding method, how to detect the cost price has been the research difficulty and hot. Effective detection method of combination entropy decision and fuzzy risk evaluation was proposed.According to each construction unit’ project bidding risk index systems, using entropy proportion method to determine the weights, and then through the project risk fuzzy evaluation model, fuzzy comprehensive evaluation of risk value, and finally according to the size of risk value in order to determine the level of profits, and the cost was determined. The effectiveness was validated through the practical engineering cases. The method opened up that judge bidding price whether lower than the cost. While overcoming the only pursuit of winning the bid in the lowest price, regardless of the disadvantages whether lower than the cost.

Construction Engineering Bidding Risk Analysis

In the Bill of Quantities mode, the bidder must take risks of his tender offer. This paper researched on the uncertainty of construction projects costs, proposed Monte Carlo simulation method and procedure to simulate the construction projects costs on the basis of the construction projects costs conform to the characteristics of normal distribution, and also put forward a method to calculate risks of the tender offer in accordance with the established bidding strategy, which are helpful to the risk management and control of project contracting enterprises.

Research on the Evaluation Model of Bidding Risk in Engineering Project

The decision of bidding risk in International Engineering project faces many risk factors. It is of significance to identify precisely the assessment of the risk correctly. A concise and practical method of assessing the tender decision risk is presented in this paper based on the principle of AHP method and fuzzy comprehensive evaluation method. We take Inner Mongolia Power Company Limited H 2 × 600MW project for example to verify the practicality and effectiveness of the system. Finally, considering of thermal power construction project's bidding risk characteristics, then we offer some risk control measures, which provides a more objective and applicable method for the risk management in international projects.

Multi-objective optimal strategy for generating and bidding in the power market

Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.

Fuzzy Probability Method-Based Risk Assessment of International Engineering Project

In the present paper, the fuzzy probability method is applied to assess the risk of international engineering project. Firstly, According to the risk from the whole cycle of international engineering project, The influential factors of the project bidding risk assessment are analyzed. The risk of international engineering project is divided into four parts, such as national risk, industrial risk, involved parties risk and project’s risk, and an assessment index system of international project risk is constructed. Secondly, based on the fuzzy probability method, a new model of the risk assessment for international engineering project is developed. In order to assess index weighted value scientifically, the analytical hierarchy process (AHP) is introduced into the fuzzy weighted values. Finally, the validity and rationality of the risk evaluation for international engineering project is verified through the risk instance of a project.

A New Method for Next-Day Price Forecasting for PJM Electricity Market

In the framework of the competitive electricity markets, electricity price forecasting is important for market participants in a deregulated electricity market. Rather than forecasting the value, market participants are sometimes more interested interval of the peak electricity price forecasting. Forecasting the peak price is essential for estimating the uncertainty involved in the price and thus is highly useful for making generation bidding strategies and investment decisions. The choice of the forecasting model becomes the important influence factor how to improve price forecasting accuracy. This paper proposes new approach to reduce the prediction error at occurrence time of the peak electricity price, and aims to enhance the accuracy of the next day electricity price forecasting. In the proposed method, the weekly variation data is used for input factors of the ANN at occurrence time of the peak electricity price in order to catch the price variation. Moreover, learning data for the ANN is selected by rough sets theory at occurrence time of the peak electricity price. This method is examined by using the data of the PJM electricity market. From the simulation results, it is observed that the proposed method provides a more accurate and effective forecasting, which helpful for suitable bidding strategy and risk management tool for market participants in a deregulated electricity market.

Single versus Multiple Prime Contracting

Policies regarding public building construction affect the interests of taxpayers, construction authorities, general contractors, specialty contractors, and other stakeholders. At the state level, the debate as to the optimal form such policies should take has become an ongoing struggle among competing interests. This study presents a systematic analysis of the main issues regarding single versus multiple prime contracting with the purpose of providing objective data to illuminate the debate. A statistical analysis of project bids and final costs from a national sample of state construction projects reveals that public construction projects organized with multiple prime contracts tend to have 5% less direct costs than projects using a single prime contractor. Moreover, approximately 80% of these savings are attributable to lower bid costs for multiple prime projects. The results of this study are in agreement with theoretical bidding models and efficient risk allocation models. Theoretical bidding models suggest that, in the absence of disruptions, multiple prime projects should have lower direct costs than single prime jobs. Efficient cost allocation models suggest that when specialty contractors do not bear the risks associated with the single prime contracting method (e.g., bid shopping and payment delays) they are willing to lower their bids, and forego the premium they would normally charge in response to such risks, as seems to be the case in multiple prime jobs.

Risk avoidance in bidding for software projects based on life cycle management theory

This study explores how to integrate software project management risk into bidding risk, and makes use of life cycle management theory to study risk avoidance in bidding for software projects. The stages in the life cycle of software projects and main risk items are introduced. As many types of risk items exist in the bidding, we analyze the possible risk response measures for different risk categories and the measures’ corresponding strength. Finally, we describe the basic methodology for dynamic risk avoidance in bidding for software projects based on life cycle management theory and give an example.

Public–private partnership projects: Towards a model of contractor bidding decision-making

Public–private partnership (PPP) projects (PPPs) are central to the UK Government's procurement of public services. PPPs are competitively tendered but a significant minority of projects attract insufficient bidders, making it difficult to demonstrate transparency and value for money. Based on an empirical study, this paper posits an initial model of how private sector bidders decide whether to bid for contracts; a distinction is drawn between two separate assessments made by potential bidders, the risk of bidding and the risk of the project. The paper concludes that the former assessment is insufficiently understood by practitioners and scholars. A research agenda is suggested.

Supplier risk analysis in the day-ahead electricity market

In the deregulated marketplace, generation companies sell energy through auctions or bilateral contracts in a daily market. The daily-price volatility creates the need to perform risk assessment. A procedure able to detect the profitability and risk of bidding in a day-ahead energy market is proposed for power producers. In a pool/bilateral market structure, generation companies are assumed to submit supply bids for the auction in the market pool and report the power amount involved in bilateral contracts to the market operator. The market-clearing process is simulated by solving an OPF-based problem that maximises the social welfare. Then, the expected profits are evaluated by running a Monte Carlo simulation, and the value at risk and conditional value at risk are calculated for quantifying risk of the producer portfolio. The proposed procedure provides suppliers with an efficient tool able to handle daily market-price uncertainties and to capture, in powerful aggregate risk measures, all relevant portfolio effects of market-risk exposure. Simulations are carried out in a 24-hour time frame to analyse the profit and the risk faced by one of the generating companies of the Italian electric-power system.

Water and Private Sector Partnership: Case of Karachi, A Mega-City of Pakistan

Implementation of private sector partnership (PSP) into Karachi Water and Sewerage Board (KWSB) of Karachi, a mega-city of Pakistan, was studied. The assignment was categorized into three distinct phases: development of the most appropriate strategy for PSP; execution of the preparatory work for PSP; and implementation of the agreed program. The PSP strategy approved by Government of Sindh (GS) province was designed to ensure that ownership of assets remains in the public sector while the technical, commercial and financial needs of the system become the responsibility of the private operator. The PSP strategy also ensured that benefits of system improvement are devoted to the greatest number of customers. A legal and regulatory framework had also been developed to enable the induction of a private operator into the provision of water sewerage services, to define the role and powers of the regulator and of government, and the rights of customers along with the measures for their enforcement. Six institutes for the framing of regulations of the water sector were identified. An extensive marketing program had been revealed to develop market interest and build up profile of the project. Having a detailed study on different working models of PSP, concession type of contract was the choice to be favored since it has been the basis used in other developing countries. Public awareness campaign was carried out to mitigate the persistent fears and misconceptions which could range from simple apprehensions regarding increases in tariffs and water charges among ordinary consumers to concerns touching issues of national security and sovereignty. Role of government was set to share risks by providing for political, legislative, force majeure, currency risk, and guaranteeing buy out provisions for private operator. While the private operator was anticipated to take normal commercial risks such a bidding risk, market risk including revenue and construction risks for infrastructure investments. Phase I strategy of the partnership was successfully done and approved by the GS in 2000. The phase II included a detailed technical and financial feasibility evaluation of the concession contract is under progress and likely to be completed until mid of this year, and phase III, transfer of ownership, is scheduled by the end of this year. Exact out come of the PSP is still awaited to be public. First initiative in Karachi is to execute successfully since this will develop investors' confidence and interests and will play a role model for the water utilities to follow in other growing cities of Pakistan.