考虑电力衍生产品的风险管理和资产组合优化模型

在竞争的电力市场中,不确定的电价和电量使市场参与者面临电力市场风险.文中根据国外成熟竞争性电力市场实际情况,对电力市场风险的来源、测度指标和管理工具进行了分析,建议采用条件在险现金流作为测度电力市场风险的指标.提出了竞争性电力市场下的电力市场风险计算模型,通过典型电力企业实例分析了电力市场风险的特点、电力衍生产品交易对电力市场风险管理的作用以及电力实物资产和衍生产品投资组合优化等问题,计算了不同市场条件下样本企业的电力资产组合有效前沿,并对竞争性电力市场中的电力市场风险管理和资产组合优化策略进行了总结.     

Managing Price Risk in a Multimarket Environment

In a competitive electricity market, a generation company (Genco) can manage its trading risk through trading electricity among multiple markets such as spot markets and contract markets. The question is how to decide the trading proportion of each market in order to maximize the Genco's profit and minimize the associated risk. Based on the mean-variance portfolio theory, this paper proposes a sequential optimization approach to electric energy allocation between spot and contract markets, taking into consideration the risks of electricity price, congestion charge, and fuel price. Especially, the impact of the fuel market on electric energy allocation is analyzed and simulated with historical data in respect of the electricity market and other fuel markets in the U.S. Simulation results confirm that the proposed analytic approach is consistent with intuition and therefore reasonable and feasible for a Genco to make a trading plan involving risks in an electricity market     

电力市场下发电公司和大用户间电力交易的双方叫价拍卖模型

随着我国电力体制的改革和发电侧竞争市场的建立,在需求方很快也会引入竞争,并建立完全开放的双边电力市场。在完全开放的双边电力市场下,大用户直接购电问题已成为我国电力改革的重大课题。研究发电公司和大用户如何建立有效的报价策略具有十分重要的理论和实践价值。作者提出一种直接交易方式,由大用户直接与发电企业进行一对一的交易,并自定价格。因而,这是发电公司和大用户的双方叫价拍卖问题,通过对双方叫价拍卖的交易规则进行描述。针对发电公司的生产成本和大用户的估价是私有信息的情况,建立了完全开放市场下发电公司和大用户的双方叫价拍卖的不完全信息贝叶斯博弈模型,并求解贝叶斯纳什均衡,给出了发电公司和大用户的均衡报价策略。     

电力市场竞价交易结算价格机制研究

对电力市场拍卖交易中的系统边际价格、投标价格、混合价格、灵活价格、系统价格权拍卖、当量价格等价格结算机制的基本原理和特点进行了综述和比较分析，为电力市场交易规则设计和电力市场模拟分析提供参考。     

流域水电公司在电力期货交易下的竞争策略

电力期货是规避现货市场风险的有效管理工具,目前国外主要的电力市场均以合约交易为主、现货交易为辅,实现了现货的价格调节功能与期货的价格风险规避功能的结合,在成熟的合约市场交易基础上出现了电力期货交易所.在电力期货交易背景下,结合流域水电公司的特点,分析价格风险,结合其收益模型探讨了流域水电公司在电力期货交易下的竞争策略.     

Multi-agent based experimental analysis on bidding mechanism in electricity auction markets

Determining the best market pricing rule is a controversial issue in the design of electricity auction markets. Pay-as-bid (PAB) has been proposed to replace the market-clearing price (MCP) in deregulated electricity markets, with the expectation that it would lower market prices and reduce price volatility. A multi-agent based experiment was constructed to compare and analyze the balanced process of the two auction mechanisms. Each adaptive agent represents a generator who develops a bid price and quantity based on a reinforcement learning algorithm. In the simulation experiments, the experimental results are not as expected. Before the market reaches equilibrium, the market price with the PAB mechanism is lower than it is with the MCP mechanism. However, the market price in the PAB mechanism is higher than it is with the MCP when the market achieves a state of equilibrium. With the PAB mechanism, the volatility of volume and price of each generator is less than it is with the MCP system, as expected. The experimental results also show that unconscious collusion behaviors by generators during the game process are a key reason for producing generator market power in the two auction mechanisms.     

Effective market monitoring in deregulated electricity markets

Experience with deregulated electricity markets has shown that the assumption that markets will naturally produce competitive results is not justified. The existing independent system operators (ISOs) and emerging regional transmission organizations (RTOs) all have developed or are developing systems and procedures to accomplish the monitoring task in their markets. This paper provides an overview of the key elements necessary for effective design and implementation of market monitoring systems. Market monitoring must be concerned primarily with ensuring efficient market performance by identifying market inefficiencies, the potential for market abuses, and market power problems. In this paper, we define market power and identify factors that allow the exercise of market power in electricity markets. We also propose market efficiency objectives that should be used to design market rules that discourage gaming. We then identify the issues relevant to designing and implementing an effective market monitoring function.     

A price competition model for power and reserve market auctions

In our recent work, we formulated a price competition game model for modeling oligopolistic competition in a single-period electricity market auction. An assumption made in the study is that generator marginal costs are un-identical. In this paper, we continue to study single-period auction games, with the assumption that generator marginal costs are identical. We found that the later assumption facilitates a sharper result, which states that the market clearing price (CP) at equilibrium under tight capacity constraint is unique. This assumption also permits us to obtain simpler equilibrium characterization and mathematical proofs. Furthermore, we extend the model to study the auction game in which power and reserve are auctioned simultaneously. As an application, we derive market power indices out of the suggested game-theoretic models.     

统一价格和PAB竞价的实验分析

采用实验经济学的方法和多个商品同时拍卖的模型,研究了电力市场不同需求响应条件下统一价格竞价和PAB（pay—as—bid）竞价的市场行为和发电商报价策略问题。实验结果表明,2种竞价机制下市场均能收敛到完全竞争均衡附近,但PAB竞价的市场平均价格高于统一价格竞价的市场平均价格且价格较稳定,因此购电费用较高;市场需求弹性较小时2种竞价机制的市场价格均有显著提高,但在发电容量充足时仍可保持充分的竞争性;在不同的竞价机制下,发电商将采取不同的报价策略,统一价格竞价中发电商之间的竞争更为明显。     

Auction design in day-ahead electricity markets

Competition in day-ahead electricity markets has been established through auctions where generators and loads bid prices and quantities. Different approaches have been discussed regarding the market auction design. Multi-round auctions, despite its implementation complexity, allow market participants to adapt their successive bids to market prices considering their operational and economic constraints. However, most of the day-ahead electricity market implementations use noniterative single-round auctions. This paper presents a market simulator to compare both auction models. Different auction alternatives, such as the Spanish single-round auction that takes into account special conditions included in the generator bids, and multi-round auctions with different stopping rules, are analyzed. The results and acquired experience in the simulation of the Spanish market, started in January 1998, are presented. Hourly market prices, average daily price, price/demand correlation and several economic efficiency indicators, such as generator surplus, consumer surplus and social welfare, are compared to derive conclusions regarding the performance of the auction alternatives     

Realistic electricity market simulator for energy and economic studies

Electricity market simulators have become a useful tool to train engineers in the power industry. With the maturing of electricity markets throughout the world, there is a need for sophisticated software tools that can replicate the actual behavior of power markets. In most of these markets, power producers/consumers submit production/demand bids and the Market Operator clears the market producing a single price per hour. What makes markets different from each other are the bidding rules and the clearing algorithms to balance the market. This paper presents a realistic simulator of the day-ahead electricity market of mainland Spain. All the rules that govern this market are modeled. This simulator can be used either to train employees by power companies or to teach electricity markets courses in universities. To illustrate the tool, several realistic case studies are presented and discussed.     

Auction design in day-ahead electricity markets

Competition in day-ahead electricity markets has been established through auctions where generators and loads bid prices and quantities. Different approaches have been discussed regarding the market auction design. Multi-round auctions, despite its implementation complexity, allow market participants to adapt their successive bids to market prices considering their operational and economic constraints. However, most of the day-ahead electricity market implementations use noniterative single-round auctions. This paper presents a market simulator to compare both auction models. Different auction alternatives, such as the Spanish single-round auction that takes into account special conditions included in the generator bids, and multi-round auctions with different stopping rules, are analyzed. The results and acquired experience in the simulation of the Spanish market, started in January 1998, are presented. Hourly market prices, average daily price, price/demand correlation and several economic efficiency indicators, such as generator surplus, consumer surplus and social welfare, are compared to derive conclusions regarding the performance of the auction alternatives     

有差价合约日前市场中计及风险约束的最优报价策略

日前市场是国内外目前实际运营的以联营体为基础的单一购买者模式的电力市场所采用的最主要的形式.在有些日前市场中采用了差价合约来规避单一购买者和发电公司可能面对的由于电价波动所带来的财政风险.针对具有差价合约的日前市场,在假设市场规约要求发电公司采用线性报价函数申报下一个交易日每个时段的报价而且市场按统一清算价对每个交易时段分别进行结算的前提下,构造了发电公司在日前市场考虑风险约束的最优报价策略的数学模型,计及了发电机组的运行约束和启动成本,并发展了以遗传算法为基础的有效的求解方法.最后,用一个算例说明了所提出的方法的基本特征.     

Short-term electricity prices forecasting in a competitive market: A neural network approach

This paper proposes a neural network approach for forecasting short-term electricity prices. Almost until the end of last century, electricity supply was considered a public service and any price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices and technical improvements. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive electricity markets. In this new competitive framework, short-term price forecasting is required by producers and consumers to derive their bidding strategies to the electricity market. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgement of future price movements, and for consumers to maximize their utilities. A three-layered feedforward neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of mainland Spain and California.     

Coordinated spot market for congestion management of inter-regional electricity markets

The rapid growth of inter-regional trading among electricity markets requires the development of new market-oriented mechanisms for the inter-regional congestion management of such trading. In this paper, we deal with the operation of power systems consisting of several interconnected electricity markets. We propose an alternative approach to inter-regional trade that avoids the flaws of forward markets with explicit auctioning of interconnections capacities. We propose the integration of a forward market with a balancing (spot) market for inter-regional exchanges based on nodal pricing. The interaction of transmission system operators (TSOs) belonging to adjacent markets is efficiently taken into account through a decentralized optimal power flow (OPF), which is solved by interior point methods.     

The impacts of different bidding segment numbers on bidding strategies of generation companies

In a competitive electricity market, generation companies design bidding strategies to maximize their individual profits subject to the constraints imposed by bidding rules. For a generation company, obviously, the optimal bidding strategy and hence the potential of exercising market power may be different if different bidding rules are employed. Hence, a well-designed bidding protocol is vital to the effective and efficient operation of an electricity market. Based on the widely used stepwise bidding rules, the impacts of different numbers of bidding segments on the bidding strategies of generation companies are investigated. This study is focused on a price-taker generation company in an electricity market. A probabilisic model is used to simulate electricity price in the competitive market environment. With a given number of bidding segments, the optimal bidding strategy for a price-taker generation company is then developed. The effects of risk preferences as well as information asymmetry on the optimal bidding strategy are also examined. With particular references to the impacts of different numbers of bidding segments on the optimal bidding strategy, a numerical example is employed to demonstrate the validity of the proposed model and methodology.     

The importance of market interdependencies in modeling energy systems - The case of the European electricity generation market

The analysis of complex electricity generation systems such as the European one require large scale models based on extensive databases of the relevant infrastructures. Such models are increasingly used to assist policymaking by developing scenarios to investigate the impact of certain policies on generation capacities, investments and prices. The continuing liberalization and interconnection of energy markets thereby requires the considerations of multiple interdependencies with other markets. Most models, however, do not take this into account. This paper develops and applies a large scale electricity investments and dispatch and natural gas market dispatch model to highlight the importance of recognizing interdependencies between power generation and the gas market. In an exemplary analysis, it is demonstrated that seasonal gas price patterns resulting from temperature-dependent household gas demand have a significant impact on the competitiveness of gas-fired power stations in competition with other technologies. Spatially, we show that competitive cost-based gas prices would lead to a relocation of such plants closer to the sources of natural gas.     

An oligopolistic power market model with tradable NO/sub x/ permits

Models formulated as complementarity problems have been applied previously to assess the potential for market power in transmission-constrained electricity markets. Here, we use the complementarity approach to simulate the interaction of pollution permit markets with electricity markets, considering forward contracts and the operating reserve market. Because some power producers are relatively large consumers of permits, there could be interaction between market power in the permits and energy markets. Market power in the energy market is modeled using a Cournot game, while a conjectured price response model is used in the permits market. An illustrative application is made to Pennsylvania-New Jersey-Maryland Interconnection (PJM), which we represent by a 14-node dc load-flow model, and the USEPA Ozone Transport Commission NO/sub x/ Budget Program. The results show that forward contracts effectively mitigate market power in PJM energy market and both simulated solutions of perfect and Cournot (oligopoly) competition are a good approximation to actual prices in 2000, except that the Cournot model yielded higher peak prices. The NO/sub x/ market influences the Cournot energy market in several ways. One is that Cournot competition lowers the price of NO/sub x/ permits, which in turn affects on low- and high-emission producers differently. In general, because pollution permits are an important cost, high concentration in the market for such permits can exacerbate the effects of market power in energy markets.     

完全开放的双边电力市场中供需双方叫价拍卖的贝叶斯博弈模型

随着我国进行电力体制改革和建立发电侧竞争市场，需求方很快也会引入竞争，并建立完全开放的双边电力市场。研究供给侧和需求侧如何建立有效的报价策略具有十分重要的理论和实践价值。作者将所有发电公司看成供给方，把所有买电代理商看成需求方，将供给方和需求方的报价问题看成是他们向市场的投标问题，并根据市场确定的规则，总需求电量将在某一价格下完成交易，因而它是供给方和需求方的双方叫价拍卖问题。通过对双方叫价拍卖的交易规则进行描述，针对供给方的生产成本和需求方的估价是私有信息的情况，建立了完全开放的双边电力市场中供给和需求双方叫价拍卖的不完全信息贝叶斯博弈模型，并求解贝叶斯纳什均衡，给出供给方和需求方的均衡报价策略。