Engineering—Economic analysis of electric power systems

This state-of-the art paper sets out recent developments in the engineering-economic analysis of electric power systems, especially the formulation of optimal investment and pricing policies. The basic economic principle is that electricity services should be provided in a manner which maximizes the net benefits of consumption of society as a whole. In investment policy, this principle may often be reduced to the simpler rule of minimizing total costs subject to specific constraints. In pricing policy, rates should reflect the marginal costs of supply, thus ensuring that economic efficiency criteria are satisfied. However, these marginal costs must be systematically adjusted to yield a practical tariff structure that meets other policy objectives. Several case studies are provided which illustrate the practical application of the methodology to optimize investment planning and reliability, system losses, and tariffs.     

Study on Theory and Methods of Telecommunication Tariff

Study on Theory and Methods of Telecommunication Tariff     

竞争中的电信资费策略——选择资费

本文介绍了选择资费的概念，理论基础，产生背景及其特点，认为选择资费是竞争环境下较为有利的一种电信资费方式。文章还通过对国外实际资费方案的分析，对我国现有资费管理体制提出了相关建议。     

OFDMA上行链路中基于博弈论的子载波和功率分配算法

传统OFDMA上行链路资源分配算法中一般以最大化各用户速率或最小化发射功率为依据对子载波和功率进行分配,而对于各用户的功率效率问题并没有加以考虑。针对这一问题,该文提出了一种基于功率效率最优的联合子载波功率分配算法。首先给出了在各用户峰值功率约束条件下达到收益函数最优的必要条件并证明了算法纳什均衡的存在及唯一性,然后给出了子载波功率分配算法。仿真表明:相比最大边界速率子载波和功率分配算法(MaxRt+WF)和固定子载波和功率分配算法(MaxFA+WF),该文算法能大幅度提高各用户的功率效率。同时如果合理地选择代价参数,算法获得的和功率效率能够达到更大。     

Investigation on Active and Reactive Combined Spot Price Integrated with Wind Farm

An active and reactive combined spot price model and the corresponding algorithm are introduced in this paper based on the theory of optimal power flow. Different from the traditional economic dispatch in the field of spot price, the objective function is to minimize generation costs based on pricing reactive power. Then considering the characteristics of wind turbines, processing methods of wind farms in optimal power flow is discussed. Finally, the feasibility of the model and the algorithm is verified through the simulation results of IEEE 30 system.     

Biased choice of a mobile telephony tariff type:: Exploring usage boundary perceptions as a cognitive cause in choosing between a use-based or a flat rate plan

Most mobile network operators provide newly acquired or existing customers with the possibility to choose between a monthly flat rate for unlimited voice calls and pay-per-minute price schemes. Consumers who maximize their utility should select the tariff type that leads to the lowest invoice amount given their anticipated service usage volume. However, previous research looking at users of fixed network telephony, broadband Internet access and other services suggests that a significant share of consumers prefers a flat rate to use-dependent price plans even though their invoice will be higher. One cognitive explanation for such biased choices is that consumers consider the ratio of the likelihood of calling enough to justify a flat rate to the probability of not calling enough to save money with a fixed price (= “ratio rule”) when choosing between the two tariff types. In this assessment they overestimate the first likelihood in proportion to the second one. Drawing on a sample of 203 mobile telephony customers in Germany the present study shows that mobile users are biased in favor of a flat rate because they overestimate their future call usage and behave in line with the “ratio rule” when choosing a tariff type. Correlates of cognitively biased tariff choices are explored. With regard to pricing practices it is concluded that managers should not follow the temptation to exploit the overestimation bias in designing pricing and advertising policies pushing customers into fixed price schemes, which do not fit their actual calling patterns.     

Tarification,discrimination et contournement

This paper illustrates on an example the optimal (nonlinear) pricing policy by a monopolistic operator of a local telecommunications network facing competition in the market for access to long distance carriers (bypass). We start by providing a brief overview of the literature on non-linear pricing and on bypass. As a benchmark, we consider a monopoly facing no threat of competition and having access to two distinct technologies: the network technology and the bypass technology, which is more efficient for reaching large individual customers. We then study competition between bypassors and the original network operator. We characterize the optimal tariff, analyze the resulting allocation and provide comparative statics.     

A scalable network resource allocation mechanism with bounded efficiency loss

The design of pricing mechanisms for network resource allocation has two important objectives: 1) a simple and scalable end-to-end implementation and 2) efficiency of the resulting equilibria. Both objectives are met by certain recently proposed mechanisms when users are price taking, but not when users can anticipate the effects of their actions on the resulting prices. In this paper, we partially close this gap, by demonstrating an alternative resource allocation mechanism which is scalable and guarantees a fully efficient allocation when users are price taking. In addition, when links have affine marginal cost, this mechanism has efficiency loss bounded by 1/3 when users are price anticipating. These results are derived by studying Cournot games, and in the process we derive the first nontrivial constant factor bounds on efficiency loss in these well-studied economic models.     

A blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social internet of vehicles

Social Internet of Vehicles (SIoV) falls under the umbrella of social Internet of Things (IoT), where vehicles are socially connected to other vehicles and roadside units that can reliably share information and services with other social entities by leveraging the capabilities of 5G technology, which brings new opportunities and challenges, e.g., collaborative power trading can address the mileage anxiety of electric vehicles. However, it relies on a trusted central party for scheduling, which introduces performance bottlenecks and cannot be set up in a distributed network, in addition, the lack of transparency in state-of-the-art Vehicle-to-Vehicle (V2V) power trading schemes can introduce further trust issues. In this paper, we propose a blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social vehicular networks that uses a distributed market mechanism to introduce trusted power trading and avoids the dependence on a centralized dispatch center. Based on the game theory, we design the pricing and trading matching mechanism for V2V power trading to obtain maximum social welfare. We use blockchain to record power trading data for trusted pricing and use smart contracts for transaction matching. The simulation results verify the effectiveness of the proposed scheme in improving social welfare and reducing the load on the grid.     

Efficient power control via pricing in wireless data networks

A major challenge in the operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With the increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash (1951) equilibrium that is inefficient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e., to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system     

Influence de la tarification horaire sur le trafic téléphonique

As the evening peakload of trunk traffic became higher than the morning one, a new time-of-day pricing was initiated in France on June 1985. The effects of this tariff change on the traffic profile and the telephone revenues were previously estimated, using an econometric model, fitted from traffic observations provided by similar experiments carried out in Germany and Switzerland. This model, based on probabilistic choice theory, uses the Logit formulation adapted to the case of a continuous set of options (times-of-day), and provides simulations of traffic trade-offs due to changes in the time-of-day pricing. Data collected since June 1984 enable us to measure the actual effects of the new tariffication. Compared with the model forecasts, these observations show a good fitting for the 6 p.m. to 8.30 p.m. period (the 8 p.m. peak-load decrease is consistent with the forecast); in the late evening however, traffic is higher than expected. These new data allowed us to improve the formulation and the fitting of the model; these recent developments are presented here.     

Pricing Multicast Communication: A Cost-Based Approach

Multicast and unicast traffic share and compete for network resources. A cost-based approach to multicast pricing, based on accurate characterization of multicast scalability, will facilitate the efficient and equitable resource allocation between traffic types. Through the quantification of link usage, this paper establishes a multicast scaling relationship: the cost of a multicast distribution tree varies at the 0.8 power of the multicast group size. This result is validated with both real and generated networks, and is robust across topological styles and network sizes. Since multicast cost can be accurately predicted given the membership size, there is strong motivation to price multicast according to membership size. Furthermore, a price ceiling should be set to account for the effect of tree saturation. This tariff structure is superior to either a purely membership-based or a flat-rate pricing scheme, since it reflects the actual tree cost at all group membership levels.     

Impact of electricity tariffs on optimal orientation of photovoltaic modules

Maximum revenue (or cost saving) from non‐tracking photovoltaic (PV) modules used for distributed generation can be achieved by a module orientation that depends on how the electricity tariff varies with time of day and time of year. Many jurisdictions have real‐time market prices of electricity for large customers, time‐dependent tariffs or tariffs that depend on peak demand. This paper quantifies the impact of such tariffs on the optimal orientation of non‐tracking PV modules using example tariffs from California, Nevada and Ontario, and concludes that modules should be oriented to the west of south by 28°, 46° and 54° respectively. In order to focus on the impact of tariff, the results are based on simulations of a constant‐efficiency PV system operating under year‐round clear‐sky conditions. A generalized relationship between optimal azimuth and the on‐ to off‐peak ratio of time‐dependent tariffs is also presented. The paper quantifies the sensitivity of the dollar value of the power generated to non‐optimal orientation of the modules. Compared to conventional south facing modules tilted at an angle just under the latitude, the paper demonstrates that optimal orientation adds 4–19% to the revenue/cost savings, potentially affecting the economic viability of a PV installation. The peak demand components of the Ontario tariff have a much more substantial effect on the optimization and resultant revenues (cost savings) than variations in the real‐time market price of electricity. Copyright © 2015 John Wiley & Sons, Ltd.     

一种基于计费的WCDMA功率控制方法

在第三代移动通信系统中,为了有效地提高系统容量和通信质量,需要对无线资源如发射功率作合理的动态分配。该文通过研究 WCDMA系统中上行链路的干扰情况,推导得出 WCDMA系统的容量与业务性能指标的关系。通过定义网络资源份额,将功率控制问题转换为总量小于1的网络资源份额的分配问题。然后利用统一价格拍卖对网络资源份额进行最优配置,使得发射功率这一重要无线资源合理地分配给对其评价最高的用户业务。最后给出了上述算法的数值仿真。     

Competition in generation: the economic foundations

This paper sets out the economic foundations that underlie competitive markets in electricity generation. It moves from a general formulation of a competitive market to discuss traditional models of optimal electricity pricing. It shows how an auction market can produce the same results and discusses the option of bilateral trading. Models of market power, which can lead to higher process and reduced efficiency, are then discussed. The final part of the paper deals with network effects     

Pricing and power control in a multicell wireless data network

We consider distributed power control in a multicell wireless data system and study the effect of pricing transmit power. Drawing on the earlier work of Goodman and Mandayam (see IEEE Personal Commun. Mag., vol.7, p.48-54, 2000), we formulate the QoS of a data user via a utility function measured in bits per Joule. We consider distributed power control, modeled as a noncooperative game, where users maximize their utilities in a multicell system. Base station assignment based on received signal strength as well as received signal-to-interference ratio (SIR) are considered jointly with power control. Our results indicate that for both assignment schemes, such a procedure results in an inefficient operating point (Nash equilibrium) for the entire system. We introduce pricing of transmit power as a mechanism for influencing data user behavior and our results show that the distributed power control based on maximizing the net utility (utility minus the price) results in improving the Pareto efficiency of the resulting operating point. Variations of pricing based on global and local loading in cells are considered as a means of improving the efficiency of wireless data networks. Finally, we discuss the improvement in utilities through a centralized scheme where each base station (BS) calculates the best SIR to be targeted by the terminals it is assigned     

Non-Cooperative Power Control for Wireless Ad Hoc Networks with Repeated Games

One of the distinctive features in a wireless ad hoc network is lack of any central controller or single point of authority, in which each node/link then makes its own decisions independently. Therefore, fully cooperative behaviors, such as cooperation for increasing system capacity, mitigating interference for each other, or honestly revealing private information, might not be directly applied. It has been shown that power control is an efficient approach to achieve quality of service (QoS) requirement in ad hoc networks. However, the existing work has largely relied on cooperation among different nodes/links or a pricing mechanism that often needs a third-party involvement. In this paper, we aim to design a non-cooperative power control algorithm without pricing mechanism for ad hoc networks. We view the interaction among the users' decision for power level as a repeated game. With the theory of stochastic fictitious play (SFP), we propose a reinforcement learning algorithm to schedule each user's power level. There are three distinctive features in our proposed scheme. First, the user's decision at each stage is self-incentive with myopic best response correspondence. Second, the dynamics arising from our proposed algorithm eventually converges to pure Nash equilibrium (NE). Third, our scheme does not need any information exchange or to observe the opponents' private information. Therefore, this proposed algorithm can safely run in a fully selfish environment without any additional pricing and secure mechanism. Simulation study demonstrates the effectiveness of our proposed scheme.     

合理的资费管制是电信竞争的基础

资费管制与其他方面的管制有着密切的关系,合理的资费管制是开展电信竞争的前提。对我国目前的电信资费现状,各方存在很大的分歧。事实上,现在电信领域尚没有完善的定价机制,在某些方面还存在交叉补贴,资费体系也不符合WTO的要求。未来资费改革分两个阶段:第一阶段的基本目标是初步确立基于成本的价格体系和促进市场竞争的价格管制体系;第二阶段是建立高效率的资费体系。     

认知小蜂窝网络中基于干扰温度限制的下行能效资源分配算法

为最大化认知小蜂窝基站的能量效率,本文基于博弈论模型分析了下行联合频谱资源块和功率分配行为.在干扰受限环境下,多个基站采用分布式结构共享空闲频谱资源.为避免累加干扰损害主用户的通信,算法中引入了功率和干扰温度限制.由于具有耦合限制的分数形式的能量效用函数是非凸最优的,通过将其转化为等价的减数形式进行迭代求解.给定频谱资源块分配策略后,主博弈模型可被重新建模为便于求解发射功率的等价子博弈模型,并通过代价的形势解除耦合限制.仿真结果表明,本文所提算法能够收敛到纳什均衡,并有效提高了系统资源利用率和能量效率.     

An overview of pricing concepts for broadband IP networks

In this article we provide an overview of pricing concepts for broadband multiservice networks. We review the notions of flat pricing, priority pricing, Paris-Metro pricing, smart-market pricing, responsive pricing, expected capacity pricing, edge pricing, and effective bandwidth pricing. We use numerous evaluation criteria, including network, economic, and social efficiency, as well as their suitability in using pricing as a means for congestion control. Some of the schemes are based on best-effort networks, and are thus unable to provide the user with quality of service (QoS) guarantees. Others build on networks with connection admission control functions and are thus able to provide individual QoS guarantees. We particularly investigate the relevant time frame over which pricing schemes are assumed to operate. The majority of the schemes work on short time frames (on the order of minutes), which makes them applicable to use pricing as an additional means for controlling congestion. We also consider technical aspects such as compliance with existing networking technologies or computational overheads associated with billing and accounting.