Robust bidding and offering strategies of electricity retailer under multi-tariff pricing

In this paper, an electricity retailer seeks to determine selling price for end-user consumers under fixed pricing (FP), time-of-use pricing (TOU) and real-time pricing (RTP). Furthermore, in order to provide power exchange between the retailer and the power market, bidding and offering curves should be prepared to bid and offer to the day-ahead market. Therefore, this paper proposes a robust optimization approach (ROA) to obtain optimal bidding and offering strategies for the retailer. To achieve this, ROA is used for uncertainty modeling of power market prices in which the minimum and maximum limits of prices are considered for uncertainty modeling. Lower and upper bounds of price is consecutively subdivided into sequentially nested subintervals which allows formulating robust mixed-integer linear programming (RMIP) problem. The proposed RMIP model helps retailer to select a robust decision in the presence of market price uncertainty. Furthermore, the bidding and offering curves of the retailer are obtained from sufficient data through solving these problems. Meanwhile, the uncertainty of customers demand and variable climate condition are modeled based on stochastic programming. To validate the proposed robust optimization model, three case studies are evaluated and the results are compared.     

Optimal retailer bidding in a DA market - a new method considering risk and demand elasticity

This paper presents a new method to determine the optimal demand function for a retailer in power markets. It assumes that the retailer purchases the energy from either the day-ahead or the regulation market and sells it to the end users through fixed and/or real-time pricing contracts. The load is assumed to be price sensitive and the retailer to be price-taker. Through participation in the market and managing its risk, the retailer attempts to maximize its profit. The proposed method is tested on a typical power market.     

A real options evaluation model for the diffusion prospects of new renewable power generation technologies

This study presents a policy planning model that integrates learning curve information on renewable power generation technologies into a dynamic programming formulation featuring real options analysis. The model recursively evaluates a set of investment alternatives on a year-by-year basis, thereby taking into account that the flexibility to delay an irreversible investment expenditure can profoundly affect the diffusion prospects of renewable power generation technologies. Price uncertainty is introduced through stochastic processes for the average wholesale price of electricity and for input fuel prices. Demand for electricity is assumed to be increasingly price-sensitive, as the electricity market deregulation proceeds, reflecting new options of consumers to react to electricity price changes (such as time-of-use pricing, unbundled electricity services, and choice of supplier). The empirical analysis is based on data for the Turkish electricity supply industry. Apart from general implications for policy-making, it provides some interesting insights about the impact of uncertainty and technical change on the diffusion of various emerging renewable energy technologies.     

考虑源荷不确定性的分时电价动态修正机制研究

针对新型电力系统中可再生能源出力及负荷需求的不确定性造成源荷协调困难,导致难以制定合理的分时电价的问题,该文提出一种考虑源荷不确定性的分时电价动态修正机制。首先,根据可再生能源出力的波动性以及不确定性,建立新能源并网功率与并网电量偏差量化模型;其次,根据需求侧负荷的变化特征,结合可再生能源出力不确定性,通过多种不确定性因素影响条件的误差计算方法,建立电价概率密度模型。然后,根据负荷上报的用电量以及预报电价,建立考虑源荷不确定性的电力市场分时电价动态修正与优化模型,并采用粒子群算法进行模型求解。最后,通过实际运行数据仿真验证该文所提方法的有效性。     

Regulated and unregulated Nordic retail prices

Nordic residential electricity consumers can now choose among a number of contracts and suppliers. A large number of households have continued to purchase electricity from the incumbent supplier at default contract terms. In this paper, we compare the situation for such passive customers. Danish default prices are regulated whereas default prices in the other countries are unregulated. Systematic price differences exist among the Nordic countries. However, as wholesale prices sometimes differ the gross margin is a more relevant indicator. Regulated gross margins are lower in Denmark than in Sweden but higher than in Norway and Finland. Because of market design Norwegian default contracts are competitive whereas Swedish contracts provide the retailer with some market power. We interpret the low Finnish margins as a result of municipal retailers continuing traditional pricing from the monopoly period. Danish margins are higher than the competitive Norwegian margins but are earned from a much lower level of consumption. The annually margins earned per consumer are very close in the two countries, which indicates that the Danish regulation is achieving its objective of approaching competitive prices.     

售电市场环境下售电公司与电力用户双层博弈模型研究

售电市场放开是我国售电侧改革的发展方向,竞争性售电市场中用户选择权放开,用户选择结果影响售电公司的售电策略,售电公司售电策略又会直接影响用户选择。构建售电公司与电力用户间双层博弈模型,下层模型为用户层演化博弈,上层模型为售电公司间非合作博弈。首先分析影响用户选择售电公司的因素,建立用户效用模型,采用演化博弈理论构建不同类型用户群体选择售电公司的多群体动态演化模型。在构建用户选择模型的基础上,分析售电公司的购售电策略,计及售电公司面临的风险因素,建立售电公司和电力用户的双层博弈模型并给出了博弈均衡的求解算法。算例分析结果表明,所构建的模型和算法具有可行性和有效性。     

An exploratory analysis of California residential customer response to critical peak pricing of electricity

This paper summarizes the results from an exploratory analysis of residential customer response to a critical peak pricing (CPP) experiment in California, in which 15 times per year participating customers received high price signals dispatched by a local electricity distribution company. The high prices were about three times the on-peak price for the otherwise applicable time-of-use rate. Using hourly load data collected during the 15-month experiment, we find statistically significant load reduction for participants both with and without automated end-use control technologies. During 5-h critical peak periods, participants without control technology used up to 13% less energy than they did during normal peak periods. Participants equipped with programmable communicating thermostats used 25% and 41% less for 5 and 2 h critical events, respectively. Thus, this paper offers convincing evidence that the residential sector can provide substantial contributions to retail demand response, which is considered a potential tool for mitigating market power, stabilizing wholesale market prices, managing system reliability, and maintaining system resource adequacy.     

Trends in prices to commercial energy consumers in the competitive Texas electricity market

To date, the price of electricity to commercial or business energy consumers has generally increased at greater rates in the areas of Texas where retail competition has been introduced than in areas that do not enjoy competition. Trends in commercial competitive prices have largely mirrored trends in residential prices. Market restructuring has tended to increase the sensitivity of retail electricity prices to changes in the price of natural gas, the marginal fuel used for generation in Texas. Consequently, the rapid increases in the commodity price of natural gas following restructuring led to increases in competitive electric rates which exceeded the increases in areas not exposed to restructuring, where the fuel component of electric rates tend to reflect a weighted average of the utilities’ fuel costs. There is some evidence that pricing behavior by competitive retailers changed when the retailers affiliated with the incumbent utilities were permitted some pricing flexibility, resulting in a reduction in prices.     

A looming revolution: Implications of self-generation for the risk exposure of retailers

Managing the risk associated with uncertain load and prices has always been a challenge for retailers in electricity markets. While a number of standard derivatives contracts are available to hedge the price risk, managing the load variability used to be comparatively straightforward as this variability was largely predictable in the past, especially when aggregating a large number of consumers. In contrast, the increasing penetration of unpredictable, small-scale electricity generation by consumers, i.e. self-generation, constitutes a new volume risk that cannot be hedged through standard derivatives contracts. Using a DCC-GARCH approach and Monte Carlo simulations based on German historical loads and prices, the contribution of decentralized solar PV self-generation to the load, price and revenue risk of retailers is assessed. Our results reveal a significant revenue risk exposure of retailers arising from increasing levels of intermittent self-sufficiency, which is largely driven by the increasing load risk and to a lesser extent by the increasing price risk. Therefore, this analysis is relevant when considering distributed energy systems and peer-to-peer business models entailing a load forecasting challenge for traditional retailers, which will be crucial to address in the context of the transition towards power systems based on renewables.     

A stackelberg game approach for heterogeneous energy market in integrated energy system

With the increasing demand of energy and the growing intensity of energy crisis, various smart energy systems are developed on the distribution level, such as integrated energy system (IES). In this article, a trading mechanism among various energy retailers and consumers is designed under the open market environment. The trading problem is formulated as a multi‐leader and multi‐follower Stackelberg game, which is built with the strategy set of energy bidding price and purchasing pattern. In particular, consumer's demand is described with the price elasticity property of demand, and non‐cooperative competition behavior among retailers is analyzed mathematically. To implement the proposed game approach, a distributed algorithm is presented by combining particle swarm optimization (PSO) and interior point method (IPM). Finally, simulation results show that the proposed trading mechanism will contribute to the development of heterogeneous energy market and the overall profit of retailers in the traditional trading mechanism is 37.8% lower than the profit in the proposed mechanism.     

Optimal regulation of renewable energy: A comparison of Feed-in Tariffs and Tradable Green Certificates in the Spanish electricity system

Incentives for renewable energy based on Feed-in-Tariffs have succeeded in achieving high levels of renewable installed capacity. However, these incentives have not been responsive to market conditions or price signals, imposing in some cases a great financial burden on consumers when Renewable Energy Sources reached significant levels. A way out of this problem could be a market mechanism where incentives respond to the level of investment on renewables. We explore this issue comparing a regulatory system based on Tradable Green Certificates, able to react to market changes, to a Feed-in-Tariffs incentive scheme. We model the strategic interaction between participants in the electricity pool and the Tradable Green Certificates market and focus on the optimal regulation for the retailer segment, which generates the desired demand for green certificates as a decreasing function of the certificate price. We then calibrate our theoretical model with data from the Spanish electricity system for the period 2008–2013. Simulations show that a green certificate scheme could both achieve the 2020 targets for renewable electricity and reduce regulatory costs. However, the role of regulators is still important, since setting the right target for renewable electricity affects the cost burden of the system.     

Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers

To the extent that demand response represents an intentional electricity usage adjustment to price changes or incentive payments, consumers who exhibit more-variable load patterns on normal days may be capable of altering their loads more significantly in response to dynamic pricing plans. This study investigates the variation in the pre-enrollment load patterns of Korean commercial and industrial electricity customers and their impact on event-day loads during a critical peak pricing experiment in the winter of 2013. Contrary to conventional approaches to profiling electricity loads, this study proposes a new clustering technique based on variability indices that collectively represent the potential demand–response resource that these customers would supply. Our analysis reveals that variability in pre-enrollment load patterns does indeed have great predictive power for estimating their impact on demand–response loads. Customers in relatively low-variability clusters provided limited or no response, whereas customers in relatively high-variability clusters consistently presented large load impacts, accounting for most of the program-level peak reductions. This study suggests that dynamic pricing programs themselves may not offer adequate motivation for meaningful adjustments in load patterns, particularly for customers in low-variability clusters.     

Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines

Feed-in tariffs (FIT) are among the most important policy instruments to promote renewable electricity production. The fixed-price FIT (FFIT), which guarantee a fixed price for every unit of produced electricity and the premium based FIT (PFIT), which pay a premium on top of the market price are commonly implemented in the EU. Costs for balancing intermittent electricity production may be significantly higher with FFIT than with PFIT, and FFIT do not provide any incentive to produce electricity when marginal production costs are high. In contrast, PFIT do provide strong incentives to better match renewable power output with marginal production costs in the system. The purpose of this article is to assess the effects of the two tariff schemes on the choice of wind turbine locations. In an analytical model, we show that both the covariance between wind power supply and demand as well as between the different wind power locations matter for investors in a PFIT scheme. High covariance with other intermittent producers causes a decrease in market prices and consequently in revenues for wind power investors. They are therefore incentivized to diversify the locations of wind turbines to decrease the covariance between different wind power production locations. In an empirical optimization model, we analyze the effects of these two different schemes in a policy experiment for Austria. The numerical results show that under a PFIT scheme, (1) spatial diversification is incentivized, (2) the covariance of wind power production with marginal electricity production costs increases, and (3) the variances of the wind power output and of residual load decrease if wind power deployment attains 10% of total national electricity consumption.     

A new approach to congestion pricing in electricity markets: Improving user pays pricing incentives

Electricity pricing has traditionally been based on average cost pricing where consumers pay a ‘flat’ tariff based upon the average cost of production and transportation of electricity. The introduction of new ‘smart’ meters allows electricity providers to differentiate tariffs on the basis of time. Utilising congestion pricing theory, the energy industry has embraced ‘time-of-use’ (ToU) tariffs with a view to more efficiently pricing electricity. This paper demonstrates that pricing as a function of demand variability (reflecting capacity utilisation) is a more appropriate alternative to existing ToU tariffs for more efficiently allocating costs to end users. We call this new alternative pricing model ‘first derivative ratio’ FDR pricing. This new approach to congestion pricing could be applied to markets other than electricity, such as road transportation.     

The optimal fuel mix and redistribution of social surplus in the Korean power market

This paper investigates the difference between the optimal fuel mix incorporating a pre-installed generation capacity constraint and the actual fuel mix in the Korean power market. Since the restructuring of the market, the fuel mix has been determined partly by investors and partly by the Basic Plan for Long-Term Electricity Supply and Demand (BPE). Both the system marginal price (SMP), and the capacity payment (CP), which has been based on the fixed cost of a specific gas turbine generator, were intended to provide an investment incentive in the market; however, they did not bring about an optimal fuel mix in Korea. Under the circumstances of a shortage of base load generators, these generators may garner excessive profits due to a high SMP level. However, the adjustment scheme of profit between KEPCO and Gencos left scant profit for generators. This paper suggests that a contract is needed to create the appropriate profit and tax levels for these base load generators. The redistribution of profit improves equality between consumers and generators, and the proper margin creates incentives for base load technology investment in Korea.     

Pricing residential load shedding as a call option

Air-conditioner power-interruption programs are shown by simulation to reduce the peaks of a utility load profile. The value of this load-shifting capability is determined by a financial call option pricing model. The air-conditioner interruption option is determined to be worth about $0.65 per summer month to a representative utility; but this value varies widely with costs, volatility of demand, and the skill of implementation by utility managers. The interruption option is given an imputed value derived from the share prices of the utility. This imputed value approximates the value obtained by simulation.     

基于分时电价的水库调度图优化研究

以芹山水库为例,结合分时电价原理与水库优化调度理论,划分了分时电价的时段,建立了考虑电价的以水电站水库发电效益最大为目标、兼顾保证出力要求的优化调度模型,应用改进的遗传算法优化水库常规调度图.结果表明,考虑分时电价影响后平均出力变小,能多发峰电,增加发电效益.     

The efficiency of Ireland's Renewable Energy Feed-In Tariff (REFIT) for wind generation

Ireland's Renewable Energy Feed-In Tariff (REFIT) for wind generation has some unusual features making it different from other REFIT schemes around the world. By utilising an annual floor price element the scheme presents an option value to the contract holder, which to date has gone unnoticed or unvalued in the market. By employing an option pricing framework, this paper has quantified for the first time in the public domain the expected costs and value of the Irish REFIT support scheme for wind generation. While the cost of the REFIT scheme to the electricity consumer appears to be lower than the cost of schemes in other countries, significant inefficiencies exist as a result of the structure of the scheme. The Irish REFIT scheme is contrasted with a single Fixed Price support scheme and the analysis suggests that the Fixed Price scheme can provide a similar or greater incentive to the wind sector at half the cost to the end electricity consumer, and may also prove more compatible with consumers desire to reduce inter-year electricity portfolio cost volatility.     

基于多周期GARCH-M模型的短期电价预测

电价的分布特性是电力市场风险管理和电力金融产品定价的重要依据。建立了一个采用虚拟变量和正弦函数来刻画现货电价序列多周期性特征的GARCH-M模型。该模型易于定阶、待估参数少,可同时处理电价序列的趋势变化、多周期、异方差及其与负荷之间的非线性相关性,具有一定的实用价值。对PJM电力市场历史数据的分析表明,电价分布的异方差和负荷的平方对电价均值具有显著的影响,电价序列具有周、半月、月、季、半年等多重周期和明显的波动集聚性。