Electricity market design for generator revenue sufficiency with increased variable generation

We present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. The FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.     

An improved mechanism for capacity payment based on system dynamics modeling for investment planning in competitive electricity environment

Many countries have experienced restructuring in their electric utilities. This restructuring has presented the power industries with new challenges, the most important of which is long-term investment planning under uncertain conditions. This paper presents an improved mechanism for capacity payment. The mechanism has been investigated based on system dynamic modeling. In our proposed mechanism, generators will recover a part of their investment through capacity payment. While the payment for any plant remains constant during the operation period, it depends on the investment needed to build it. The main factors affecting long-term planning have been considered in our model. The approach can be used to investigate the effects of fixed as well as variable capacity payment in market investment. We used the probability density function of load as a new concept to calculate average market price. Delays in unit constructions, estimation of demand, and market capacity growth during construction periods have been included in the proposed algorithm as parameters, which affect the regulator's decision for changing capacity payment. The model can be used by regulators to investigate strategies that may affect the fluctuations in the market.     

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.     

The electricity generation adequacy problem: Assessing dynamic effects of capacity remuneration mechanisms

Following liberalization reforms, the ability of power markets to provide satisfactory incentives for capacity investments has become a major concern. In particular, current energy markets can exhibit a phenomenon of investment cycles, which generate phases of under and over-capacity, and hence additional costs and risks for generation adequacy. To cope with these issues, new mechanisms, called capacity remuneration mechanisms (CRM), have been (or will be) implemented. This paper assesses the dynamic effects of two CRMs, the capacity market and the strategic reserve mechanism, and studies to what extent they can reduce the investment cycles. Generation costs and shortage costs of both mechanisms are also compared to conclude on their effectivity and economic efficiency. A simulation model, based on system dynamics, is developed to study the functioning of both CRMs and the related investment decisions. The results highlight the benefits of deploying CRMs to solve the adequacy issue: shortages are strongly reduced compared to an energy-only market. Besides, the capacity market appears to be more beneficial, since it experiences fewer shortages and generation costs are lower. These comparisons can be used by policy makers (in particular in Europe, where these two CRMs are mainly debated) to determine which CRM to adopt.     

Enhancing power supply adequacy in Spain: Migrating from capacity payments to reliability options

There has been total unanimity about the vital importance of reliability of supply since the beginning of the electricity sector deregulation process. This paper describes the procedure proposed by Pérez-Arriaga et al. [2005. White paper for the reform of the regulatory scheme of the power generation in Spain. For the Ministry of Industry, Tourism and Trade of Spain (in Spanish)] to improve upon the current scheme to guarantee a reasonable reserve margin, the capacity payment mechanism. This alternative design introduces improvements aimed at guaranteeing at least a minimum capacity reserve margin, as well as at providing a strong incentive for generating units to be available when needed, namely, in situations when supply is likely to be insufficient to meet the total demand.     

Reactive power market management considering voltage control area reserve and system security

This paper presents a new algorithm to optimize reactive power procurement through commercial transactions considering system voltage security. The proposed algorithm minimizes reactive power provision and transmission loss costs in addition to maximizing system voltage security margin through a multiobjective function. In order to maintain the voltage profile of power system during sever contingencies or due to load uncertainty, all voltage control areas (VCA) of the system are detected and then optimal reactive power reserve is provided for each VCA during the market settlement. A four-stage multiobjective mathematical programming method is proposed to settle the reactive power market. The proposed algorithm has been applied on IEEE-RTS test system. The simulation results show the effectiveness of the proposed algorithm for reactive power market management.     

Willingness to pay for vehicle-to-grid (V2G) electric vehicles and their contract terms

Vehicle-to-grid (V2G) electric vehicles can return power stored in their batteries back to the power grid and be programmed to do so at times when the grid needs reserve power. Since providing this service can lead to payments to owners, it effectively reduces the life-cycle cost of owning an electric vehicle. Using data from a national stated preference survey, this paper presents a study of the potential consumer demand for V2G electric vehicles. In a choice experiment, 3029 respondents compared their preferred gasoline vehicle with two V2G electric vehicles. The V2G vehicles were described by a set of electric vehicle attributes and V2G contract requirements such as “required plug-in time” and “guaranteed minimum driving range”. The contract requirements specify a contract between drivers and a power aggregator for providing reserve power to the grid. Our findings suggest that the V2G concept is most likely to help EVs on the market if power aggregators operate either on pay-as-you-go basis (more pay for more service provided) or provide consumers with advanced cash payment (upfront discounts on the price of EVs), rather than imposing fixed requirements on participants.     

Welfare implications of capacity payments in a price-capped electricity sector: A case study of the Texas market (ERCOT)

The aim of this paper is to analyze the welfare consequences of introducing capacity compensation payments in restructured and liberalized electricity markets. For that purpose, we set up a two-stage framework in which two kinds of electricity generators, peak load and base load generators, choose their capacity investment levels first and then compete on the basis of bids in a centralized market to sell electricity to consumers. We use data from the Texas ERCOT to evaluate consumers' welfare. We find that the introduction of capacity payments has two countervailing effects. On the one hand, it increases the wholesale electricity price. On the other hand, it reduces price volatility and increases the reliability of the system. We find that capacity payments are more beneficial for consumers in a perfectly competitive market than in the presence of certain degree of market power.     

Incentives to invest in liberalised electricity industries in the North and South. Differences in the need for suitable institutional arrangements

The issue of investment is all too often underplayed in deregulation reforms focused on market rules and de-integration measures. This presentation criticises first the optimistic approach of the theory of investment incentives through market signals when it is applied to deregulated electricity industries. The greater part of the investment in base-load and peak equipment should be made profitable by income from very high prices during peak and extreme peak periods, that raises a problem of political acceptability. The problem is then addressed in the context of the mature electricity industries in the North. Given the maturity of markets there, a number of modifications to the pure market model could be envisaged to strengthen incentives to invest, but none of them is perfect. The main way is to focus on adaptation of market rules on the supply of power at peaks and extreme peaks by considering “capacity adequacy” as a public good (with three solutions: capacity payment, reserve obligations, centralised procurement by auctioning for peak capacity). Observation of reforms suggests also the validity of some other solutions based on a limitation of the competition by allowing long-term contracts and vertical integration between production and supply. Finally the question is extended to the specific problem of developing countries characterised by irregular growth. It is argued that reforms must be designed in view of the importance of the need for investment through long-term coordination and reduction of investment risks. Indeed experiences of Latin American liberalised industries show that they have to include a number of competition-based imperfections and to allow ongoing exercise of market power in order to allow prices to rise above competition prices. The single buyer model or some variants of it appear to be good alternatives if one wishes to avoid the twists and turns of the competition paradigm. The difficulty with this model arises from the institutional conditions necessary to make it efficient and not overcostly.     

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software.     

Stochastic reactive power market with volatility of wind power considering voltage security

While wind power generation is growing rapidly around the globe; its stochastic nature affects the system operation in many different aspects. In this paper, the impact of wind power volatility on the reactive power market is taken into account. The paper presents a novel stochastic method for optimal reactive power market clearing considering voltage security and volatile nature of the wind. The proposed optimization algorithm uses a multiobjective nonlinear programming technique to minimize market payment and simultaneously maximize voltage security margin. Considering a set of probable wind speeds, in the first stage, the proposed algorithm seeks to minimize expected system payment which is summation of reactive power payment and transmission loss cost. The object of the second stage is maximization of expected voltage security margin to increase the system loadability and security. Finally, in the last stage, a multiobjective function is presented to schedule the stochastic reactive power market using results of two previous stages. The proposed algorithm is applied to IEEE 14-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the actual market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved.     

Dynamic assessment of capacity investment in electricity market considering complementary capacity mechanisms

This paper proposes a decentralized market-based model for long-term capacity investment decisions in a liberalized electricity market. Investment decisions are fundamentally based on total revenues gained by investors. In most electricity markets, the complementary mechanisms are designed to ensure a desired level of reliability while covering investment costs of the suppliers. In such an environment, investment decisions are highly sensitive to expectation of price signals in both of energy market and capacity mechanisms. In this work, the system dynamics concepts are used to model the structural characteristics of electricity market such as, long-term firms’ behavior and relationships between variables, feedbacks, and time delays by appropriately bundling the energy market and capacity mechanisms. The market oriented capacity price as well as non-competitive capacity payments and a proposed hybrid capacity mechanism are linked with the energy market in the model. Such a decision model enables both the generation companies and the regulators gaining perfect insights into the possible consequences of different decisions they make under different policies and market conditions. In order to examine the performance of the electricity market with different capacity mechanisms, a case study is presented which exhibits the effectiveness of the proposed model.     

考虑需求侧响应的风电并网系统旋转备用优化

随着新能源的快速发展,风电并网的规模逐渐扩大,由于风电出力的不确定性,风电消纳已成为新能源发展的主要挑战。考虑常规机组同时参与主辅市场,并融入需求侧资源可中断负荷及用电激励参与辅助服务市场,建立源荷协调的双层优化模型。上层模型以发电成本和弃风成本最小为优化目标,确定常规机组出力和风电计划出力;在上层优化结果基础上,下层针对常规机组调峰能力不足导致的弃风和失负荷情况,考虑用电激励和可中断负荷为备用资源,建立以发电侧旋转备用成本、用电激励成本、可中断负荷成本及失负荷损失和弃风损失的条件价值风险最小为目标的优化模型,得到旋转备用容量优化购买量。以修正的IEEE 6机30节点系统进行算例研究,仿真结果表明所建模型能有效提高系统经济性及风电消纳水平。     

Supporting the externality of intermittency in policies for renewable energy

We analyse the joint problem of supporting renewables and resource adequacy in a liberalised electricity market and present a detailed model-based comparison of two alternative policies. We undertake this in the context of the British market. We show how, ceteris paribus, the progressive replacement of coal with wind imposes extra costs of reserve and evaluate alternative way to meet this, whether through capacity payments funded by customers, or a reliability requirement on wind generators with capital cost or energy feed-in subsidies. We consider the reality of market concentration and the extent to which pragmatic regulation could allow prices to rise above marginal cost to reduce the extent of direct subsidies and complex market designs. We also evaluate the implied cost of carbon reduction in a progressive replacement of coal with wind, when the security is maintained by extra peaking gas. We find that support through capital allowances rather than the energy market is more efficient.     

Double-sided auction mechanism design in electricity based on maximizing social welfare

An efficient electricity double-sided auction mechanism should control market power and enhance the social welfare of the electricity market. Based on this goal, the paper designs a new double-sided auction mechanism. In the new mechanism, the social welfare contribution of each participant plays a pivotal role, because this contribution is the critical factor in market clearing, payment settling, and transaction matching rules. In particular, each winner of the auction can gain transfer payments according to his contribution to social welfare in the electricity market, and this gives the mechanism the ability to control the market power of some participants. At the same time, this mechanism ensures that the market organizer balances his budget. We then conduct a theoretical and empirical analysis based on the Spanish electricity market. Both of the results show that compared to the uniform-pricing mechanism, the new mechanism can reduce market power of participants and enhance the social welfare of the electricity market.     

A scenario analysis of investment options for the Cuban power sector using the MARKAL model

The Cuban power sector faces a need for extensive investment in new generating capacity, under a large number of uncertainties regarding future conditions, including: rate of demand growth, fluctuations in fuel prices, access to imported fuel, and access to investment capital for construction of new power plants and development of fuel import infrastructure. To identify cost effective investment strategies under these uncertainties, a supply and power sector MARKAL model was assembled, following an extensive review of available data on the Cuban power system and resource potentials. Two scenarios were assessed, a business-as-usual (BAU) scenario assuming continued moderate electricity load growth and domestic fuel production growth, and a high growth (HI) scenario assuming rapid electricity demand growth, rapid increase in domestic fuel production, and a transition to market pricing of electricity. Within these two scenarios sets, sensitivity analyses were conducted on a number of variables. The implications of least-cost investment strategies for new capacity builds, investment spending requirements, electricity prices, fuel expenditures, and carbon dioxide emissions for each scenario were assessed. Natural gas was found to be the cost effective fuel for new generation across both scenarios and most sensitivity cases, suggesting that access to natural gas, through increased domestic production and LNG import, is a clear priority for further analysis in the Cuban context.     

电力市场下光伏上网定价模型研究

针对电力市场环境下现行的光伏固定上网统一电价忽略了电力系统为应对其出力波动性而增加的热备用容量成本的问题,为了合理体现光伏发电的真实价值,提出光伏竞价上网的电价模型,根据历史数据进行未来日的出力预测并参与竞价,而采用该竞价模型所产生的部分费用反补给常规发电机组,可减少购电总成本。进而基于果蝇优化算法,运用Matlab软件对一个仅包含2个常规发电机组和1座光伏电站的电力系统进行优化求解与仿真,数值结果验证了本文模型的正确性和有效性。     

Multiobjective clearing of reactive power market in deregulated power systems

This paper presents a day-ahead reactive power market which is cleared in the form of multiobjective context. Total payment function (TPF) of generators, representing the payment paid to the generators for their reactive power compensation, is considered as the main objective function of reactive power market. Besides that, voltage security margin, overload index, and also voltage drop index are the other objective functions of the optimal power flow (OPF) problem to clear the reactive power market. A Multiobjective Mathematical Programming (MMP) formulation is implemented to solve the problem of reactive power market clearing using a fuzzy approach to choose the best compromise solution according to the specific preference among various non-dominated (pareto optimal) solutions. The effectiveness of the proposed method is examined based on the IEEE 24-bus reliability test system (IEEE 24-bus RTS).     

From nuclear phase-out to renewable energies in the Swiss electricity market

Liberalisation and the ever larger share of variable renewable energies (VRES), e.g. photovoltaic (PV) and wind energy, affect security of supply (SoS). We develop a system dynamics model to analyse the impact of VRES on the investment decision process and to understand how SoS is affected. We focus on the Swiss electricity market, which is currently undergoing a liberalisation process, and simultaneously faces the encouragement of VRES and a nuclear phase out. Our results show that nuclear production is replaced mainly by PV and imports; the country becomes a net importer. This evolution points to a problem of capacity adequacy. The resulting price rise, together with the subsidies needed to support VRES, lead to a rise in tariffs. In the presence of a high share of hydro, the de-rated margin may give a misleading picture of the capacity adequacy. We thus propose a new metric, the annual energy margin, which considers the energy available from all sources, while acknowledging that hydro-storage can function as a battery. This measure shows a much less reassuring picture of the country’s capacity adequacy.     

Integrating wind output with bulk power operations and wholesale electricity markets

Wind farms have three characteristics that complicate their widespread application as an electricity resource: limited control, unpredictability and variability. Therefore the integration of wind output into bulk power electric systems is qualitatively different from that of other types of generators. The electric system operator must move other generators up or down to offset the time‐varying wind fluctuations. Such movements raise the costs of fuel and maintenance for these other generators. Not only is wind power different, it is new. The operators of bulk power systems have limited experience in integrating wind output into the larger system. As a consequence, market rules that treat wind fairly—neither subsidizing nor penalizing its operation—have not yet been developed. The lack of data and analytical methods encourages wind advocates and sceptics to rely primarily on their biases and beliefs in suggesting how wind should be integrated into bulk power systems. This project helps fill this data and analysis gap. Specifically, it develops and applies a quantitative method for the integration of a wind resource into a large electric system. The method permits wind to bid its output into a short‐term forward market (specifically, an hour‐ahead energy market) or to appear in real time and accept only intrahour and hourly imbalance payments for the unscheduled energy it delivers to the system. Finally, the method analyses the short‐term (minute‐to‐minute) variation in wind output to determine the regulation requirement the wind resource imposes on the electrical system. Copyright © 2002 John Wiley & Sons, Ltd.