System security control and optimal pricing of electricity

Optimal electricity spot pricing internalizes electricity transportation network costs and constraints. We extend spot pricing theory by including system security control issues in the model. The engineering and physics of system security control imposes a need for speed and precision of response. Traditionally this need has been met by central control of centrally owned equipment and little control of customer-owned equipment. We show that socially optimum prices exist which decentralize security control by internalizing its costs. These prices are robust and feasible to determine without unreasonable information requirements by the market maker. Families of optimal prices and price/quantity controls are determined and interpreted. Contingency planning and enhanced centre/market-maker roles are derived. Applications of immediate interest are also discussed, such as pricing of interruptible loads and assignment of power pool reserves. Symmetry between demand side and supply side security control is shown to be optimal.     

Electricity price forecasting using artificial neural networks

Electricity price forecasting in deregulated open power markets using neural networks is presented. Forecasting electricity price is a challenging task for on-line trading and e-commerce. Bidding competition is one of the main transaction approaches after deregulation. Forecasting the hourly market-clearing prices (MCP) in daily power markets is the most essential task and basis for any decision making in order to maximize the benefits. Artificial neural networks are found to be most suitable tool as they can map the complex interdependencies between electricity price, historical load and other factors. The neural network approach is used to predict the market behaviors based on the historical prices, quantities and other information to forecast the future prices and quantities. The basic idea is to use history and other estimated factors in the future to “fit” and “extrapolate” the prices and quantities. A neural network method to forecast the market-clearing prices (MCPs) for day-ahead energy markets is developed. The structure of the neural network is a three-layer back propagation (BP) network. The price forecasting results using the neural network model shows that the electricity price in the deregulated markets is dependent strongly on the trend in load demand and clearing price.     

Security constrained optimal bidding strategy of GenCos in day ahead oligopolistic power markets: a Cournot-based model

Restructured electricity markets may provide opportunities for producers to exercise market power, maintaining prices in excess of competitive levels. In this paper a Cournot equilibrium model is proposed to obtain generation companies’ (GenCos’) optimal bidding strategies in a day ahead oligopoly market, considering elasticity of demand, market power and transmission security constraints. In order to consider network constraints, a multiperiod auction framework is addressed to simulate market clearing mechanism by means of social welfare maximization, in which the behaviors of market participants are modeled through piecewise block curves. Impact of transmission security constraints on participants’ market power is presented. A mixed integer linear programming is employed to solve the problem, resulting supply-demand satisfaction as well as market clearing prices at each hour. A novel methodology is presented for security constrained optimal bidding strategy of GenCos through introducing heuristic effective-supply curves. Subsequently, impact of GenCos’ power exertion on market characteristics and corresponding payoffs is studied. A 9-bus IEEE test system is used to implement the proposed methodology while simulation results demonstrate the effectiveness of the framework.     

有功和AGC联合电力市场调度模型及定价分析

自动发电控制(AGC)作为一种主要用于有功调频和实时电力电量平衡的负荷备用容量,与有功电能交易的耦合性较强,在系统运行出现波动时,AGC容量的确定直接关系到电能市场的价格波动.为了防止在线机组事后(即在实时调度中需要AGC时)通过滞留容量来牟取暴利,电力市场环境下如何考虑有功和AGC联合电力市场的协调运作问题是一个值得研究的课题.文中对此进行了讨论,首先建立了有功和AGC协调运作的联合市场调度模型,使得购买有功和AGC容量的费用最小;然后重点就联合优化下的AGC机组进行了定价分析,特别针对其机会成本和滞留容量等问题进行了讨论,得到了一些有益的结论.最后,通过算例仿真说明了所建模型的基本特征.     

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.     

Energy and reserve pricing in security and network-constrained electricity markets

This paper analyzes some unresolved pricing issues in security-constrained electricity markets subject to transmission flow limits. Although the notion of separate reserve types as proposed by FERC can be precisely and unambiguously defined, when transmission constraints are active, the very existence of separate reserve prices and markets is open to question when the prices are based on marginal costs. Instead, we submit here that the only products whose marginal costs can be separately and uniquely defined and calculated are those of energy and security at each node. Thus, under marginal pricing, at any given network bus all scheduled reserve types should be priced not at separate rates but at a common rate equal to the marginal cost of security at that bus. Furthermore, we argue that nodal or area reserves cannot be prespecified but must be obtained as by-products of the market-clearing process. Simulations back up these conclusions.     

An Optimal Pricing Scheme in Electricity Markets Considering Voltage Security Cost

Optimal pricing in electricity markets has emerged as a multifunctional task for the grid managers as well as a major concern for the electricity providers and users. In this paper an optimal power flow problem is developed to take into account wider dimensions of the task by linking short-term and long-term performances of power systems via security pricing. The emphasis here is on the voltage stability phenomena as a security cost. The stochastic nature of power systems is taken into account to overcome the conservativeness associated with the severest single contingency approaches. This is done by inserting the approximated discrete processed risk data into the problem as a spline function to avoid lengthy iterative solutions. An effective combined offline and online procedure is then proposed to solve the optimization problem via the interior point method, preserving both the swiftness and precision of the solution. The effectiveness of the proposed problem definition and solution is confirmed through calculating locational marginal prices for a benchmark power system.     

基于节点电价的阻塞管理理论在华北电网的应用

介绍了以节点电价为基础的市场模型在我国区域电力市场设计中的初步应用成果。在建立华北电网模型及确定电厂竞价价格时引入了安全约束经济调度,并对华北电网节点电价市场进行了仿真计算。算例的设计模仿了中国电力市场改革逐步放开价格竞争的过程,对不同模式下的电网安全、节点电价、系统运行费用、系统阻塞费用进行了分析比较,研究了基于节点电价的阻塞管理理论在华北电网的应用效果。     

Congestion management with ex ante pricing for decentralized electricity markets

In this paper, the authors present a method and a model for managing transmission congestion based on ex ante congestion prices. Their method is influenced by the yield management approach widely used for airline reservation systems, and their model is built based on the relations between transmission congestion prices and electricity commodity prices that exist for an optimal solution. They formulate the congestion pricing problem as a master problem and the electricity commodity (energy and reserve) pricing as subproblems. Examples are presented to illustrate how a system operator can use this approach to compute ex ante congestion prices and how market operators can determine clearing prices and schedules of forward electric energy and reserve markets.     

中国电力中长期市场分时段交易价格形成机制及模型

电力中长期市场分时段交易是中国电力市场改革的重要举措之一。针对当前电力中长期市场分时段交易价格形成机制不合理、不完善的问题,提出了中国电力中长期市场分时段交易价格形成机制及其模型。首先,分析影响中国电力中长期分时段交易价格形成的因素,提出电力中长期交易的4种典型场景;然后,综合考虑生产成本和用户效用,探索性地提出适用于中长期分时段交易的系统平均成本定价、用户失负荷价值定价、系统边际成本定价和发电企业失负荷价值定价4种成本定价机制,构建了基于成本定价的分时段交易定价模型;最后,以某省实际数据为例进行测算,验证了模型的有效性。     

Pricing and procurement of operating reserves in competitive pool-based electricity markets

The changing structure of the electricity supply industry is bringing procuring and pricing of operating reserve into a new focus. The efficient rationing and pricing of operating reserve is an important issue to be dealt with in competitive electricity markets, as it is needed to maintain system reliability when economically efficient transactions are accommodated in the power system. This paper sets forth a comprehensive theory for procurement and pricing scheme for operating reserve. The theory is based on capacity–reliability correlation analysis and is compatible with electricity auction in the context of electricity supply industry deregulation. Considering various elements including available capacity of generator, outage cost, reliability index and so on, the capacity–reliability correlation analysis which reflects the equilibrium condition for procurement of operating reserve capacity is built based on an optimal pricing model. Value of capacity and energy of reserve can then be derived. Using the correlation analysis, a novel mechanism for monitoring the existence of participant's gaming behavior is also developed. The optimal pricing of the reserve capacity in a deregulated market is proposed to achieve social welfare-maximization. Simple case studies are carried out to demonstrate the efficiency and the validity of the proposed scheme.     

欧洲统一电力市场演变和日前市场出清模型

本文首先梳理了欧洲一体化电力市场的融合过程,介绍了用于计算电价及跨境容量的区域价格耦合项目;其次研究了泛欧混合电力市场集成算法,研究了节点边际电价、可用传输容量和基于潮流的市场耦合数学模型;最后总结了各种市场耦合模型的特点,并针对南方区域电力现货市场建设提出了建议。     

市场环境下分布式光伏协调售电交易机制及策略

推进分布式电源参与电力市场交易是能源发展与市场发展的必然要求,而分布式电源可通过售电公司代理的方式参与市场。在现货市场背景下,以分布式光伏为例,针对协调售电的模式,提出了以售电公司购电成本最小化为目标的交易决策模型。设计了代理双方“双价格”的合约定价机制,分别基于预测电价及实际电价确定优化决策价格和结算价格,前者用于模型优化,后者用于合约结算,从而实现代理双方的利益平衡,为售电公司代理并管理分布式光伏发电从而促进市场环境下分布式光伏的有效利用提供思路,也为售电公司在新的代理关系下参与现货市场申报提供依据。     

Analysis of a monthly auction for financial transmission rights and flow-gate rights

A monthly transmission rights (TR) auction issuing both point-to-point financial transmission rights (FTRs) and flow-gate rights (FGRs) is studied in this paper. Initially, a locational marginal pricing (LMP) based energy market is presented, in which the linear security constrained optimal power flow (SCOPF) problem is solved for each hour of system operation, determining the nodal prices, the transmission link capacity prices and the transmission congestion charges (TCCs) that should be collected by the ISO in case of congestion. A monthly auction is conducted in the TR market issuing FTR obligations, FTR options and FGRs to market players, building a link between all types of transmission rights under the same market structure. Combining the advantages of financial and physical rights, the market efficiency can be enhanced by offering a variety of choices for risk management to market players. The monthly TR auction is tested on several case studies using the IEEE three-area RTS96 and useful conclusions are drawn concerning the utility of the various types of transmission rights as compared to one another, in terms of the reimbursement they provide to their holders.     

Transmission pricing of distributed multilateral energy transactions to ensure system security and guide economic dispatch

In this paper, the authors provide a simulations-based demonstration of a hybrid electricity market that combines the distributed competitive advantages of decentralized markets with the system security guarantees of centralized markets. In this market, the transmission service provider (TSP) guides an electricity market toward the optimal power flow (OPF) solution, even when maximizing its own revenue. End users negotiate with each other to determine an energy price and then submit separate bids for transmission to the TSP. The TSP returns with prices for transmission, allowing end users to respond. In simulations, this hybrid-decentralized market approaches the near-optimal results of fully coordinated and constrained markets. Additionally, this market exhibits properties that remove incentives for the TSP to withhold capacity. This hybrid market leads a market toward the optimum while allowing the TSP and the end users to act out of self-interest.     

基于故障风险指标排序的安全约束最优潮流

安全约束最优潮流(SCOPF)是一种常用的电力系统运行调度方法,但由于需要考虑大量的预想事故,问题的求解十分困难。如何加快SCOPF的求解速度是现阶段研究的热点问题。在传统的基于故障严重度排序的安全约束最优潮流基础上进行改进,采用改进过载风险指标代替传统的严重度指标,并考虑电力网络实时的天气状况,提出了一种新型的基于故障过载风险指标排序的安全约束最优潮流算法。算例分析表明,该算法所采用的故障集更小,具有迭代速度快、安全性高和经济性好的特点,可为调度员的运行决策提供重要参考。     

A method for optimal pricing of electric supply including transmission system considerations

Determining real-time electricity rate structures is currently receiving a great deal of attention. In this paper, a strategy for pricing electricity supply is formulated and evaluated. Unlike other methods which use only the variation of fuel cost for generation to estimate the rate structures, the proposed pricing algorithm incorporates the optimal allocation of transmission system operating costs based on time-of-use pricing. The transmission costs are obtained by assigning a price k to each unit of power flow in the network. The assignment does not discriminate between participants located at differing parts of the network. The real-time pricing reflects the instantaneous cost of production and functions as a load management tool because this interacts with consumer behavior. The demand for power flows and transmission on an electricity supply system, like the demand for any bundle of economic goods depends upon the assigned transmission prices, together with the economic benefit to the consumer. It is assumed that there are no privately owned generating plants and that all plants and transmission lines are operated by the utility. The modeling scheme is applied to the IEEE standard 5, 14, 30 and 57 bus power systems and involves solving a modified optimal power flow problem (OPF) iteratively using the MINOS package. It is concluded that the method has a wide potential application in electricity supply pricing.     

Probabilistic reactive power procurement in hybrid electricity markets with uncertain loads

This paper presents a novel probabilistic algorithm for optimal reactive power provision in hybrid electricity markets. The proposed algorithm is a six-stage multiobjective nonlinear constrained optimization problem which takes into account load forecasting inaccuracies. Considering a set of probable forecasted loads, a three-component expected total market payment function is suggested being minimized as cost function of the first stage. Besides economic issues, expected voltage security margin, deviation from multilateral and pool based energy transactions, deviation from spinning reserve contracts, having adequate local reactive power reserve in each voltage control area of the system and transmission congestion probability are well thought out in stages 2-5 as technical aspects of the market. Finally, in the last stage, using different weighting factors to compromise between all objects, a probabilistic multiobjective function is presented to find the best reactive power market schedule. The proposed algorithm is applied on IEEE 24-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved.     

一种新的两部制无功定价方法

提出了一种新的两部制无功定价方法.其中以无功电量成本最优为目标函数,以潮流方程为等式约束,以运行及安全约束尾部等式约束.所建议的无功电价模型的核心想法为:一方面提出电力市场下无功源以电量成本参与竞争,以解决现有的一部制电价对无功的运行成本补偿不足的问题;另一方面提出一种新的无功容量电价分解方案解决现有的一部制电价对无功投资成本回收不明确的问题.电量电价加容量电价形成了一种新的两部制无功电价.IEEE-30母线系统算例验证了该无功价格模型的有效性和实用性.     

A Model for Efficient Consumer Pricing Schemes in Electricity Markets

Suppliers in competitive electricity markets regularly respond to prices that change hour by hour or even more frequently, but most consumers respond to price changes on a very different time scale, i.e., they observe and respond to changes in price as reflected on their monthly bills. In this paper, we examine mixed complementarity programming models of equilibrium that can bridge the speed of response gap between suppliers and consumers yet adhere to the principle of marginal cost pricing of electricity. We develop a computable equilibrium model to estimate ex ante time-of-use (TOU) prices for a retail electricity market. It is intended that the proposed models would be useful 1) for jurisdictions (e.g., Ontario) where consumers' prices are regulated, but suppliers offer into a competitive market, 2) for forecasting forward prices in unregulated markets, and 3) in evaluation and welfare analysis of the policies regarding regulated TOU pricing compared to regulated single pricing