Reserve Procurement Research Articles

Network constrained model for options based reserve procurement by wind generators using binomial tree

Wind energy is a key portion of most clean and green energy strategy. However, wind energy is intermittent and uncertain. This uncertainty poses a techno-economic challenge of sourcing the least costing load balancing service (reserve). This paper looks to develop solutions for this challenge.Currently the system unbalance caused by the wind power is handled by the real time balancing market, which is operated by the system operators for maintaining reliable operation of power systems. This method cannot always work reliably when the amount of wind penetration increases in the future. A future electricity market, with no subsidies, is assumed in this paper where wind generators have to compete with other generators to sell energy. It is assumed that wind generators are competitively scheduled a day-ahead and would suffer penalties for under production while receiving a poor compensation for over production. To overcome the uncertainty in wind production, an options based network constrained intra-day secondary reserve market is proposed in this research with a mathematical formulation that considers purchasing energy from several reserve providers. Reserves may be purchased by procuring options ahead of transactions by paying premiums and paying strike prices while transacting. The market equilibrium amongst participants will be reached with proposed optimization and the lambda (LaGrange) multiplier associated with power balance equation at each bus determines optimal values of both premiums and strike prices. The amount of required reserve is calculated by using a Cauchy-Lorentz distribution model. The reserves are positive for under production and negative for over production. Transmission network MVA limits are considered to ensure feasibility of options contracts. A 5-bus test system and a real Ontario (Canada) wind farm data with IEEE 118-bus system illustrate the merits of this research.

Energy Reserve Trade Optimization for Wind Generators Using Black and Scholes Options in Small-Size Power Systems

Tremendous attention has been paid to wind energy. This renewable source of clean energy has become very appealing to investors, engineers, and environmentalists. From the power system operations perspective, the uncertain nature of wind power poses serious challenges. To reduce the effect of wind power uncertainty, a reserve procurement methodology using financial derivative such as “Options” is very promising. This paper proposes a new optimization model to procure secondary reserves to overcome wind power uncertainty by using Black and Scholes financial options while estimating short-term wind energy forecast errors by using the Gaussian distribution function. The proposed model integrates power system security constraints. At the optimal solution, the lambda multiplier associated with real power balance equations provides option premiums and strike prices.

Reserve procurement and transmission capacity reservation in the Northern European power market

This paper provides the modeling approach and the associated results of determination of bidding prices for frequency restoration reserves (FRR) provision, and implications of cross-border transmission capacity reservation for FRR exchange. A model with three optimization blocks is developed. The FRR bidding price determination block uses an opportunity cost based approach to calculate the cost of providing FRR. For the FRR procurement, the transmission system operator (TSO) selects the cheapest bids with the possibility of cross-border exchange if transmission capacity is reserved for this purpose. In the day-ahead procurement block, optimal unit commitment and dispatch is determined, taking into account the reserve and transmission capacity allocations. A case study is done for the Northern European power system, consisting of the Nordic countries, Germany and the Netherlands. The results show how, among others, the FRR bidding prices are determined by the difference between the daily averaged sport price forecasts and the units’ marginal costs. The day-ahead and total reserve procurement costs are positively and negatively correlated to the system load respectively. As could be expected, costs are reduced in the FRR market when transmission capacity is reserved for this purpose. But a decrease in cost in the day-ahead market was also obtained for small transmission capacity reservations, caused by the increased flexibility in the FRR importing market. The total costs are the lowest for a transmission capacity reservation level of around 20%, illustrating that such reservation can be beneficial.

A coordinated dispatching strategy for wind power rapid ramp events in power systems with high wind power penetration

Abstract High wind power penetration poses a challenge for the dispatch of the power system when rapid ramp events occur. This paper proposes an optimal dispatching strategy against wind power rapid ramp events during peak load periods by coordinating generation units with different time intervals. Special attention is given to the definition of the wind power rapid ramp events considering operation conditions of the system. Then, the online prediction of wind power rapid ramp events and its influence on the spinning reserve procurement of the system is analyzed. Based on the principle of coordination among generation units with different time intervals, the optimal dispatch during peak load periods when wind power rapid ramp events occur is formulated as an optimization problem considering thermal generation units, the energy storage system, interruptible load and load shedding. To improve computational efficiency, the power output calculation of the generation units with different time intervals is decomposed. The results show that the proposed dispatching strategy is feasible for accommodating wind power rapid ramp events during peak load periods.

A stochastic, contingency-based security-constrained optimal power flow for the procurement of energy and distributed reserve

It is widely agreed that optimal procurement of reserves, with explicit consideration of system contingencies, can improve reliability and economic efficiency in power systems. With increasing penetration of uncertain generation resources, this optimal allocation is becoming even more crucial. Herein, a problem formulation is developed to solve the day-ahead energy and reserve market allocation and pricing problem that explicitly considers the redispatch set required by the occurrence of contingencies and the corresponding optimal power flow, static and dynamic security constraints. Costs and benefits, including those arising from eventual demand deviation and contingency-originated redispatch and shedding, are weighted by the contingency probabilities, resulting in a scheme that contracts the optimal amount of resources in a stochastic day-ahead procurement setting. Furthermore, the usual assumption that the day-ahead contracted quantities correspond to some base case dispatch is removed, resulting in an optimal procurement as opposed to an optimal dispatch. Inherent in the formulation are mechanisms for rescheduling and pricing dispatch deviations arising from realized demand fluctuations and contingencies. Because the formulation involves a single, one stage, comprehensive mathematical program, the Lagrange multipliers obtained at the solution are consistent with shadow prices and can be used to clear the day-ahead and spot markets of the different commodities involved.

Options based reserve procurement strategy for wind generators - Using binomial trees

Wind and solar PV are the most mature forms of renewable energy and are integral to our clean energy strategy. Their intermittency poses technical and economic challenges. Technical challenges are load balancing, frequency regulation, etc. Economic challenges include providing least costing load balancing (reserves) services to these intermittent generators. This paper considers a future electricity market situation wherein wind generators are required to forecast and bid to supply energy. The future electricity market treats wind generators similar to conventional generators penalizing for underproduction and pays poorly for overproduction. An intra-day ( 24 h) secondary market is proposed in this paper where a wind generator and a reserve provider can bilaterally trade in reserves. Reserves are traded in the market by purchasing options to buy reserves at predetermined strike prices by paying premiums. These reserves include call and put options to address underproduction and overproduction. A binomial tree approach for estimating possible deviation from the forecast value is used. A new optimization formulation is proposed that uses binomial tree option pricing technique to determine optimal values of strike prices and premiums for call and put options. Two examples illustrate the benefits of the proposed idea.

A Consideration of the Wind Power Benefits in Day-Ahead Scheduling of Wind-Coal Intensive Power Systems

This paper studies day-ahead unit commitment in wind-coal intensive power systems. Due to their long start up time, high start up cost, and high minimum stable output, coal-fired generators do not provide a favorable environment for accommodating variable wind generation. The reduced efficiencies resulting from the coal-fired generation side as measured in increased fuel consumption and CO2 emissions can greatly undermine the wind power benefits to the system if wind generation and coal-fired generation are not properly coordinated. Special attention in the study is given to the wind power benefits to the system in fuel savings and in reduction of CO2 emissions. Based on the wind power forecast, the stochastic nature of wind power is treated in two parts, i.e., wind power variability and wind power uncertainty. Unit commitment is studied using wind power variability and uncertainty separately in different wind power dispatch modes and using respectively different spinning reserve procurement strategies. System performance indices are then applied to determine the optimal wind power dispatch mode and optimal spinning reserve procurement strategy to capture optimal wind power benefits for the system. A simulation system characterized by typical wind-coal features is constructed to model and to conduct the studies. The results show that taking wind power curtailment as a control option and using wind as a reserve provider improve the wind power benefits to the system.

Balancing Market Integration in the Northern European Continent: A 2030 Case Study

Increased production flexibility will be needed for the operation of a future power system with more uncertainty due to an increased share of uncontrollable generation from renewable sources. Wind energy is expected to cover a large portion of the future renewable generation. In this paper, a comparison is carried out between two balancing market models, simulating a non- and fully-integrated northern European market in a future 2030 scenario. Wind power is modelled based on high resolution numerical weather prediction models and wind speed measurement for actual and forecasted wind power production. The day-ahead dispatch and balancing energy markets are settled separately. First, the day-ahead market is modelled with simultaneous reserve procurement for northern continental Europe. Available transmission capacity is taken into account in the reserve procurement phase. In a second step, the balancing energy market is modelled as a real-time power dispatch on the basis of the day-ahead market clearing results. The results show the benefit of balancing market integration for the handling of variable production. Cost savings are obtained from balancing market integration due to less activation of reserves resulting from imbalance netting and increased availability of cheaper balancing resources when integrating larger geographical areas.

Short-Term Energy Balancing With Increasing Levels of Wind Energy

Increasing levels of wind energy are adding to the uncertainty and variability inherent in electricity grids and are consequently driving changes. Here, some of the possible evolutions in optimal short-term energy balancing to better deal with wind energy uncertainty are investigated. The focus is mainly on managing reserves through changes in scheduling, in particular market structure (more regular and higher resolution scheduling), reserve procurement (dynamic as opposed to static), and improved operational planning (stochastic as opposed to deterministic). Infrastructure changes including flexible plant, increased demand side participation, more interconnection, transmission, larger balancing areas, and critically improved forecasting can also be significant and are dealt with in the discussion. The evolutions are tightly coupled, their impact is system-dependent and so no “best” set is identifiable but experience of system operators will be critical to future developments.

Balancing market integration in the Northern European continent

This paper analyses the integration of the balancing power markets in Northern Europe including the Nordic system, Germany and the Netherlands. Two cases of balancing market integration are analysed: the current state with individual balancing markets, and the full integration of these markets, where the day-ahead market and the balancing market are settled separately. First, the day-ahead market is modelled as a common market for the whole European continent, while a simultaneous reserve procurement modelling is done for the Northern Europe. Available transmission capacity is considered to be allocated implicitly for the exchange of balancing services based on a trade-off between day-ahead energy and balancing capacity exchange. Next, the balancing energy market is modelled as a real-time power dispatch on the basis of the day-ahead market clearing results and the simulated imbalances.Detailed results for two different weeks in winter and summer are presented. They illustrate the consequences of market integration between two synchronous areas on procured and activated reserve, generation dispatch and power flows. It is demonstrated that cost savings can be achieved due to the use of cheaper balancing resources and less activation of reserves caused by imbalance netting. Such savings are estimated for a whole year of operation, and amount to approximately 400M€per year.

Simultaneous Clearing of Energy and Reserves in Multi-Area Markets Under Mixed Pricing Rules

The integration of the spot electricity markets in Europe shall lead to multi-area power exchanges that will substitute the local markets. In such scheme, market prices are affected by physical (e.g., network) constraints, yet they should sometimes follow regulatory policy rules, which do not necessarily reflect or depend on physical characteristics. In some cases, complex pricing rules should be implemented, which impose price discrimination for supply and demand entities within the same area. The methodology presented in this paper enables the balancing of supply and demand in a multi-area market considering energy and reserve bids, under complex pricing rules, which mix energy and reserve prices. A demand bid corresponds to the whole cost a demand entity is willing to pay for its participation in the energy market, including the cost for the procurement of the necessary reserves. The approach attains price integration of energy and reserves markets, simultaneous settlement of energy and reserves, and significant decrease of the payments through the uplift accounts. The main principle is the formulation of a mixed complementarity problem for the system equilibrium conditions, in which supply and demand are associated to explicitly or implicitly defined prices, which may be different even in the same zone.

Expected security cost‐based FACTS device allocation using hybrid PSO

AbstractThis paper presents FACTS device allocation for market‐based power systems. The purpose of the FACTS installation is to provide benefit for all entities. Therefore, we use a concept of minimizing expected security cost (ESC), implying to maximize social welfare, to minimize operating reserve, and to minimize load interruption in annual basis. The FACTS device investment cost is also taken into account. The ESC considers operating cost under normal state and contingencies along with their associated probabilities to occur. Annual basis bid data is used to compute ESC as well as the cost data for load interruption and reserve procurement. This paper also considers control actions among multiple FACTS device to achieve minimum ESC. To solve the overall problem, particle swarm optimization is utilized to obtain optimal FACTS device allocation as main problem while sequential quadratic programing is used to solve optimal power flow as suboptimization problem. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Analysis of optimal spinning reserve procurement with demand response resources under social cost minimization

AbstractThis paper evaluates the effect of demand response (DR) resources that are utilized in the reserve market using an optimal probabilistic mixed integer programming (MIP)‐based spinning reserve scheduling method. In order to analyze the DR utilization effect from a theoric point of view, the objective of the adopted framwork is social cost minimization. To be consistent with the increasing reliability requirements of loads and considering increasing uncertainity in the generation side because of penetration of intermitent renewable resources, both single and double outage contingencies are considered. Furthremore, for reduction of the computational burden, a two‐level optimization method is developed. Roy‐Bilinton test system (RBTS) is used in numerical simulations and the results are presented. The numerical results show that increase in the uncertainty at supply side resources, increases the need for the DR resources. The numerical results also show the effectiveness of the developed optimization method in reducing the computational time. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market

Pollution emission reduction is becoming an inevitable global goal. Incorporating pollution reduction goals into power system operation affects several different aspects, such as unit scheduling and system reliability. At the same time, changes in the energy scheduling change the required optimal reserve amount. Optimal spinning reserve scheduling also affects the energy market scheduling. Optimal reserve allocation changes the energy scheduling, which affect the amount of pollution emission. Therefore, incorporating pollution emission reduction and optimal spinning reserve scheduling cannot be studied separately. Analysis of the system effects of pollution reduction should be performed considering the ancillary service market, specificity the optimal spinning reserve scheduling. This problem is addressed in this paper by incorporating optimal spinning reserve scheduling in a combined environment economic dispatch (CEED) in one objective function. The framework of this paper enables the study of the effect of optimal reserve scheduling and emission reduction as well as an analysis of the system effects of pollution reduction. With the increased AMI and smart grid realization, the reserve supplying demand response (RSDR) is becoming an important player in the reserve market, and thus, these resources are also taken into account. In this paper, the objective function is social cost minimization, including the costs associated with energy provision, reserve procurement, expected interruptions and environmental pollution. A MIP-based optimization method is developed, which reduces the computational burden considerably while maintaining the ability to reach to the optimal solution. The IEEE RTS 1996 is used as a test case for numerical simulations, and the results are presented. The numerical results show that optimal reserve scheduling and RSDR utilization resources have a considerable impact on environmental–economic cost characteristics.

Incorporating forecast uncertainties into EENS for wind turbine studies

The rapid increase in wind power generation around the world has stimulated the development of applicable technologies to model the uncertainties of wind power resulting from the stochastic nature of wind and fluctuations of demand for integration of wind turbine generators (WTGs). In this paper the load and wind power forecast errors are integrated into the expected energy not served (EENS) formulation through determination of probabilities using the normal distribution approach. The effects of forecast errors and wind energy penetration in the power system are traversed. The impact of wind energy penetration on system reliability, total cost for energy and reserve procurement is then studied for a conventional power system. The results show a degradation of system reliability with significant wind energy penetration in the generation system. This work provides a useful insight into system reliability and economics for the independent system operator (ISO) to deploy energy/reserve providers when WTGs are integrated into the existing power system.

Scheduling of Spinning Reserve Considering Customer Choice on Reliability

One of the main objectives of power system restructuring and deregulation is to allow customers to select their desired reliability. This paper proposes a new market model where the reserve capacity is scheduled based on the desired risk level of customers, that is recognized by the expected load not supplied (ELNS) index. The reliability constraint in the objective function of reserve procurement is formulated as a function of generation and reserve allocation among the generating units as well as their failure probability. The reserve requirement is determined regarding transmission constraints and load curtailments due to transmission congestion. Therefore, this method produces market-clearing results with the desired probabilistic characteristics. Moreover, it is shown that the load shedding procedure in contingency states affects the assessment of reserve. The Roy Billinton test system (RBTS) and the IEEE reliability test system (RTS) are analyzed to illustrate the technique.

Customer choice of reliability in spinning reserve procurement and cost allocation using well-being analysis

A novel pool-based market-clearing algorithm for spinning reserve (SR) procurement and the cost allocation associated with provision of spinning reserve among customers (DisCos) is developed in this paper. Rational buyer market model is used to clear energy and spinning reserve markets in the proposed algorithm. This market model gives DisCos the opportunity to declare their own energy requirement together with their desired reliability levels to the ISO and also they can participate in the SR market as a interruptible load. The DisCos’ desired reliability levels are selected from a hybrid deterministic/probabilistic framework designated as the system well-being model. Using the demand of each DisCo and its associated desired reliability level, the overall desired system reliability level is determined. The market operator then purchases spinning reserve commodity from the associated market such that the overall desired system reliability level is satisfied. A methodology is developed in this paper to fairly allocate the cost associated with providing spinning reserve among DisCos based on their demands and desired reliability levels. An algorithm is also presented in this paper for implementing the proposed approach. The effectiveness of the proposed technique is examined using the IEEE-RTS.

Strategic Generation Capacity Expansion Planning With Incomplete Information

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> To study the competitive behavior among individual generating companies (GENCOs), an incomplete information game model is proposed in this paper in which each GENCO is modeled as an agent. Each agent makes strategic generation capacity expansion decisions based on its incomplete information on other GENCOs. The formation of this game model falls into a bi-level optimization problem. The upper level of this problem is the GENCOs' own decision on optimal planning strategies and energy/reserve bidding strategies. The lower-level problem is the ISO's market clearing problem that minimizes the cost to supply the load, which yields price signals for GENCOs to calculate their own payoffs. A co-evolutionary algorithm combined with pattern search is proposed to optimize the search for the Nash equilibrium of the competition game with incomplete information. The Nash equilibrium is obtained if all GENCOs reach their maximum expected payoff assuming the planning strategies of other GENCOs' remain unchanged. The physical withholding of capacity is considered in the energy market and the Herfindahl–Hirschman Index is utilized to measure the market concentration. The competitive behaviors are analyzed in three policy scenarios based on different market rules for reserve procurement and compensation. </para>

Electricity and long-term capacity adequacy: The quest for regulatory mechanism compatible with electricity market

This paper deals with theoretical aspects of long-term electricity supply security. Market prices and contractual arrangements on the physical and financial electricity markets do not allow the creation of sufficient incentives to invest in adequate capacity for guaranteeing the appropriate level of supply in every circumstance. Long-term security of supply by capacity adequacy must be conceptualised as a public good. Alternative solutions to reach capacity adequacy having been adopted in different markets are successively considered: public procurement of strategic reserves, capacity payments, capacity obligations with tradable rights. Each presents theoretical limits and practical drawbacks when implemented in complex markets. That brings out the interest of a mechanism of centralised auctions for forward capacity contracts (or reliability options); it combines controls by quantity and by price while stabilising investment in peak power plants and is compatible with energy and reserves markets, which is not the case with the three other mechanisms.

Decentralized decision on operating reserve considering insurance and penalty policies

AbstractIn power markets, operating reserve procurement is usually centrally handled according to certain reliability rules and aiming at minimizing the total procurement cost. In this approach, there are no customer choices, no incentives for the independent system operator (ISO) to minimize the social cost or for reserve suppliers to commit promised reserve capacity. It may lead to inefficiency. In this paper, we propose a decentralized approach for operating reserve procurement. In the approach, gencos try to maximize their own expected profits and consumers try to minimize their own expected cost with certain market information announced by the ISO. Insurance theory is applied to the approach. With the insurance policy, consumers are able to transfer their financial risk of loss of supply to the ISO. The claim defined in the insurance policy induces incentive for the ISO to manage the reserve capacity in an efficient manner. A penalty system is introduced as well. Under the penalty system, a genco is required to pay a high penalty if it does not commit the reserve capacity provision, which enforces the liability of gencos to provide operating reserve. A detailed math model and a solution procedure are presented. It is shown that with a properly defined reserve market rule, the decentralized approach can yield same optimal solution as its centralized counterpart aiming at maximizing social welfare in reserve markets. Numerical test results illustrate the effectiveness of the suggested approach. Copyright © 2008 John Wiley &amp; Sons, Ltd.