Least-cost Dispatch Research Articles

A wholesale electricity market design sans missing money and price manipulation

Using reliability differentiation via tolling agreements with diverse heat rates and fuel types, we propose an efficient wholesale electricity market design under demand and supply uncertainty. Mainly based on North America's market experience, our proposed design adopts an independent system operator's (ISO's) existing practice of least-cost dispatch of heterogeneous generation units, real-time energy price determination and capacity rationing. It solves the missing money problem of inadequate incentive for thermal generation investment, without requiring the ISO to operate centralized capacity auctions, make capacity payments, set high energy price caps, or subsidize market entry. It preempts independent power producers' price manipulation in the ISO's real-time market for energy, thus easing the ISO's burden of market monitoring. It suggests two-part pricing of end-use consumption and power demand of a load serving entity's retail customers, thus meaningfully linking the wholesale and retail markets. It is applicable to countries that have implemented wholesale competition or are in the process of doing so. Hence, its policy implication is that it should be considered in the ongoing debate of electricity reliability and market competition.

A Dynamic Analysis of Energy Storage With Renewable and Diesel Generation Using Volterra Equations

Energy storage systems will play a key role in the power system of the twenty first century considering the large penetrations of variable renewable energy, growth in transport electrification and decentralisation of heating loads. Therefore reliable real time methods to optimise energy storage, demand response and generation are vital for power system operations. This paper presents a concise review of battery energy storage and an example of battery modelling for renewable energy applications and second details an adaptive approach to solve this load levelling problem with storage. A dynamic evolutionary model based on the first kind Volterra integral equation is used in both cases. A direct regularised numerical method is employed to find the least-cost dispatch of the battery in terms of integral equation solution. Validation on real data shows that the proposed evolutionary Volterra model effectively generalises conventional discrete integral model taking into account both state of health and the availability of generation/storage.

A Wholesale Electricity Market Design Sans Missing Money and Price Manipulation

Using reliability differentiation via tolling agreements with diverse heat rates and fuel types, we propose an efficient wholesale electricity market design under demand and supply uncertainty. Mainly based on North America’s market experience, our proposed design adopts an independent system operator’s (ISO’s) existing practice of least-cost dispatch of heterogeneous generation units, real-time energy price determination and capacity rationing. It solves the missing money problem of inadequate incentive for generation investment, without requiring the ISO to operate centralized capacity auctions, make capacity payments, set high energy price caps, or subsidize market entry. It preempts independent power producers’ price manipulation in the ISO’s real-time market for energy, thus easing the ISO’s burden of market monitoring. It suggests two-part pricing of end-use consumption of a load serving entity’s retail customers, meaningfully linking the wholesale and retail markets. It is applicable to countries that have implemented wholesale competition or are in the process of doing so. Hence, its policy implication is that it should be considered in the ongoing debate of electricity reliability and market competition.

A Spatial Electricity Market Model for the Power System of Kazakhstan

Kazakhstan envisions a transition towards a green economy in the next decades which poses an immense challenge as the country heavily depends on (hydro-)carbon resources, for both its economy and its energy system. In this context, there is a lack of comprehensive and transparent planning tools to assess possible sustainable development pathways in regard to their technical, economic, and environmental implications. We present such a tool with a comprehensive techno-economic model of the Kazakh electricity system which determines the hourly least-cost generation dispatch based on publicly available data on the technical and economic characteristics of power plants and the transmission infrastructure. This modeling framework accounts for the particularities of the Kazakh electricity system: i) it has a detailed representation of combined heat and power, and ii) line losses are endogenously determined using a linear approximation. Model results are examined for a typical winter week (with annual peak load) and a typical summer week (with the hour of lowest annual load) presenting regionally and temporally disaggregated results for power generation, line utilization, and nodal prices. In an application to market design, the paper compares nodal and zonal pricing as two possible pricing schemes in Kazakhstan for the envisioned strengthening of the day-ahead market. In general, the model can be readily used to analyze the least-cost dispatch of the current Kazakh electricity system and can be easily expanded to assess the sector's development. Among others, possible applications include investment in transmission lines and in the aging power plant fleet, scenarios and policy assessment for emission reduction, and questions of market liberalization and market design.

Optimized Offers for Cascaded Hydroelectric Generators in a Market With Centralized Dispatch

We examine the problem of a generator offering generation and ancillary services from a set of cascaded hydroelectric units to a centrally dispatched market that does not account for watershed constraints. By modeling the least-cost dispatch problem and computing the resulting schedules and market prices, we formulate a stochastic bilevel optimization problem that maximizes the generator's expected profits under different demand and supply realizations. To account for potential infeasibilities in the resulting hydroelectric dispatch, we include penalties in the generator's objective function. We propose a simple technique that replaces the lower-level dispatch problem with its linearized Karush-Kuhn-Tucker optimality conditions to convert the problem to a single-level mixed-integer program. We use two numerical case studies, based on actual river systems, to demonstrate the benefits of the proposed model.

Electric Power Resource 'Shuffling' and Subnational Carbon Regulation: Looking Upstream for a Solution

“Resource shuffling,” a form of carbon leakage, occurs when different subnational approaches to carbon regulation create variations in the costs of production across jurisdictions. This Article addresses the “resource shuffling” problem presented by California’s cap-and-trade program and addresses the merits of its legal and regulatory solutions. The potential for “resource shuffling” — replacing cleaner sources of electric power with dirtier and cheaper sources of energy — is a major threat to California’s environmental goals given that about 30 percent of the electricity consumed in California is imported from other states. This imported electricity tends to come from disproportionately dirty sources (such as coal) and represents more than half of the carbon dioxide emitted as a result of California’s electricity demand. Part I of this Article describes resource shuffling and its significance for subnational efforts to regulate greenhouse gas emissions, such as California’s cap-and-trade program for carbon. Part II discusses the tension that California’s initial regulatory strategy presented with federal regulators who oversee wholesale electric power markets. Part III addresses ways to more effectively regulate resource shuffling. This Article argues that federal energy regulators could improve the efficacy of subnational efforts to address GHG emissions and produce greater certainty for power markets by addressing resource shuffling through a harmonized set of rules or guidelines articulating acceptable least-cost dispatch protocols for the operation of wholesale power markets. Absent this kind of upstream approach, resource shuffling will continue to occur, thwarting the ability of subnational regulation to achieve green house gas reduction goals, and uncertainty about shuffling will continue to plague interstate power markets.

Assessing Operating Regimes of CCS Power Plants in High Wind and Energy Storage Scenarios

Abstract This paper investigates the operating regimes of CCS power plants in future generation portfolios with large amounts of variable- output wind generation. An advanced electricity system dispatch model is developed and coupled with a Monte Carlo based energy storage optimization model to simulate the least-cost dispatch of an assumed thermal-energy storage generation portfolio with CCS. A historic high-resolution wind speed reanalysis dataset is employed and the proposed locations of future wind farms are used to produce plausible and internally consistent wind capacity deployment scenarios. The fundamental and structural changes that occur to CCS operating profiles and start-up/shut-down schedules are investigated for increasing levels of wind capacity, which creates seasonal and diurnal variations and potential flexibility implications. Non-linear interactions between flexible CCS power plants and other energy vectors are demonstrated for an illustrative case study example in Great Britain. This temporally explicit analysis of the short-term scheduling decisions of thermal plants with CCS highlights the asymmetric displacement of mid-merit thermal plants and the importance of using time-dependent start-up costs in wind-based unit commitment studies.

A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables

A new generator portfolio planning model is described that is capable of quantifying the carbon emissions associated with systems that include very high penetrations of variable renewables. The model combines a deterministic renewable portfolio planning module with a Monte Carlo simulation of system operation that determines the expected least-cost dispatch from each technology, the necessary reserve capacity, and the expected carbon emissions at each hour. Each system is designed to meet a maximum loss of load expectation requirement of 1 day in 10 years. The present study includes wind, centralized solar thermal, and rooftop photovoltaics, as well as hydroelectric, geothermal, and natural gas plants. The portfolios produced by the model take advantage of the aggregation of variable generators at multiple geographically disperse sites and the incorporation of meteorological and load forecasts. Results are presented from a model run of the continuous two-year period, 2005–2006 in the California ISO operating area. A low-carbon portfolio is produced for this system that is capable of achieving an 80% reduction in electric power sector carbon emissions from 2005 levels and supplying over 99% of the annual delivered load with non-carbon sources. A portfolio is also built for a projected 2050 system, which is capable of providing 96% of the delivered electricity from non-carbon sources, despite a projected doubling of the 2005 system peak load. The results suggest that further reductions in carbon emissions may be achieved with emerging technologies that can reliably provide large capacities without necessarily providing positive net annual energy generation. These technologies may include demand response, vehicle-to-grid systems, and large-scale energy storage.

Electric power planning for regulated and deregulated markets

Preface. Acknowledgments. Figure Citations. About the Author. 1. Overview. 1.1 The Power Delivery Chain in a Vertically Integrated Utility. 1.2 The Power Delivery Chain in a Market Environment. 2. Energy, Load, and Generation Technologies. 2.1 Energy, Power, and their Measurements. 2.2 Load. 2.3 Generation Technologies. 3. The Grid. 3.1 Fundamentals: Load, Generation, and Alternating Current. 3.2 Grid Equipment. 3.3 Grid Reliability and Contingency Requirements. 3.4 Grid Confi guration. 3.5 Grid Operations. 3.6 Blackout August 14, 2003. 4. Short-Term Utility Planning. 4.1 Planning and Execution of Dispatch: Day-Ahead Planning Through Real-Time Delivery. 4.2 Day-Ahead Demand Forecasting: Load and Ancillary Service Requirements. 4.3 Least-Cost Dispatch in a Single Control Area: A Simple Model. 4.4 A Solution Using Profi t Maximization. 4.5 Least-Cost Dispatch in a Single Control Area with Operating Constraints. 4.6 Least-Cost Dispatch in a Single Node with Spinning Reserve and Regulation. 4.7 Least-Cost Dispatch in a Network. 4.8 Real Time. 5. Long-Term Utility Planning. 5.1 Project Development. 5.2 The Planning Process. 5.3 Long-Term Load Forecasting. 5.4 A Simplifi ed Look at Generation Capacity Additions. 5.5 Generation Additions and Retirements Within a Single Control Area. 5.6 Generation Additions and Retirements with Transmission to a Single Control Area. 5.7 Generation Additions and Retirements and Transmission Additions Within a Network. 5.8 Reserve Reuqirements. 6. Midterm Utility Planning. 6.1 Informational Requirements. 6.2 Formulation of the Optimization Problem. 7. A Market Environment. 7.1 Principles and Architecture. 7.2 Short-Term Market Design: Day-Ahead Scheduling Through Real-Time Delivery. 7.3 Long-Term Market Design: No Clear Solutions. 7.4 Midterm Market Design. 8. Asset Management in Short-Term Markets. 8.1 Retailers. 8.2 Power Producers. 8.3 Integrated Energy Companies. 9. Investment Analysis: Long-Term Planning in a Market Environment. 9.1 Investment Setting in Utility and Market Environments. 9.2 Project Analysis for a Merchant Plant. 9.3 Power Purchase Agreements (Long-Term Contracts). 10. Risk Management in the Midterm Markets. 10.1 Retailer Risk. 10.2 Power Producer Risk. 10.3 A Quick Risk Primer in Statistics for Risk Management. 10.4 Risk Management in Midterm Markets: Retailers. 10.5 Risk Management in Midterm Markets: Power Producers. 10.6 Risk Management in Midterm Markets: Integrated Electricity Suppliers. 11. The California Experience. 11.1 Market Fundamentals. 11.2 Short-Term Market Structure: The CALPX, CAISO, and Other Market Participants. 11.3 Fatboy, Get Shorty, Ricochet, and Death Star. 11.4 Market Contrast: PJM and California. Bibliography. Index.

Calculating the marginal costs of a district-heating utility

District heating plays an important role in the Swedish heat-market. At the same time, the price of district heating varies considerably among different district-heating utilities. A case study is performed here in which a Swedish utility is analysed using three different methods for calculating the marginal costs of heat supply: a manual spreadsheet method, an optimising linear-programming model, and a least-cost dispatch simulation model. Calculated marginal-costs, obtained with the three methods, turn out to be similar. The calculated marginal-costs are also compared to the actual heat tariff in use by the utility. Using prices based on marginal costs should be able to bring about an efficient resource-allocation. It is found that the fixed rate the utility uses today should be replaced by a time-of-use rate, which would give a more accurate signal for customers to change their heat consumptions.

Exhaust gas treatment by an atmospheric pressure microwave plasma : Destefani, C. A. and Siores, E. Int. J. Environmental Technology and Management, 2002, 2, (4), 402–408

This paper investigates the operating regimes of CCS power plants in future generation portfolios with large amounts of variable- output wind generation. An advanced electricity system dispatch model is developed and coupled with a Monte Carlo based energy storage optimization model to simulate the least-cost dispatch of an assumed thermal-energy storage generation portfolio with CCS. A historic high-resolution wind speed reanalysis dataset is employed and the proposed locations of future wind farms are used to produce plausible and internally consistent wind capacity deployment scenarios. The fundamental and structural changes that occur to CCS operating profiles and start-up/shut-down schedules are investigated for increasing levels of wind capacity, which creates seasonal and diurnal variations and potential flexibility implications. Non-linear interactions between flexible CCS power plants and other energy vectors are demonstrated for an illustrative case study example in Great Britain. This temporally explicit analysis of the short-term scheduling decisions of thermal plants with CCS highlights the asymmetric displacement of mid-merit thermal plants and the importance of using time-dependent start-up costs in wind-based unit commitment studies.

Bid-Based Dispatch of Hydrothermal Systems in Competitive Markets

The objective of this work is to investigate possible hydro-scheduling inefficiencies under a bidding scheme. It will be shown that the market-based dispatch of hydro-plants, under a perfect competitive market, converges to its least-cost dispatch. Besides, it will be shown that the usual spot payment scheme does not provide the correct incentive for upstream reservoirs to regulate downstream production, thus causing an operating distortion. The implementation of a Wholesale Water Market is proposed for trading stored water and so to correct such distortion. Case studies will be presented, with data taken from the Brazilian System.

The Efficiency of Multi-Unit Electricity Auctions

Using a complete information game-theoretic model, we analyze the performance of different electricity auction structures in attaining efficiency (i. e., least-cost dispatch). We find that an auction structure where generators are allowed to bid for load "slices" outperforms an auction structure where generators submit bids for different hours in the day.