Hourly Bids Research Articles

A Showcase for Resilient and Sustainable District Heating in Denmark

This presentation gives a description of the Danish district heating company, Hvide Sande District Heating, which has become independent of fossil fuels by using wind and solar energy. This has resulted in lower consumer heating prices in a time when other fossil fueled district heating plants are raising their heating prices due to higher fossil fuel prices.Besides participating in the Day-ahead market it also participates in the balancing markets.Hvide Sande is a small fishing town. The district heating plant provides heat to 1,700 consumers. From being a natural gas fired Combined Heat and Power plant, it has in recent years become more resilient by investing in a solar collector, wind turbines, a heat pump, an electrical boiler as well as more large thermal storages, and is now independent of natural gas.The two thermal storages of 2,000 m3 and 1,200 m3, respectively, can store around 200 MWh-heat, which allows flexible market-based productions of the different production units. The heat delivered to consumers can thus be produced many hours or days before delivery.Even in the Day-ahead market, the market-based productions are a challenge to plan. Because of the large thermal storages, the manager must look more days ahead as well as consider the heat amount in the thermal storages, when deciding the hourly bids for tomorrow. Biddings are based on forecasts more days ahead of wind velocity, solar radiation, ambient temperatures, and Day-ahead prices.Besides participating in the Day-ahead market it also participates in the balancing markets. However, to take advantage across more electricity markets of this flexibility, a vast digitalization of the plant using advanced bidding methods has been required. This presentation illustrates examples of the daily earnings the plant has had participating across more electricity markets. It is also important that the manager maintains a digital twin of the plant. The digital twin of the plant will in this presentation be used for simulating the resilience of the plant against large changes in electricity prices and fuel prices.

Comparison of flexible bidding and hourly bidding in the electricity market

Flexible bidding is an emerging electricity trading product in the Nordic spot market, which is different from hourly bidding and block bidding. It provides electricity generation enterprises and users with flexible and changeable electricity generation and consumption options and can reflect the electricity generation and demand-side behavior and habits of electricity generation and consumption, providing reference value for Chinese market participants to participate in the electricity market and demand-side response. This paper firstly introduces the two bidding models of hourly bidding and flexible block bidding; secondly, it introduces the market clearance model of flexible bidding; finally, it compares the differences between these two bidding approach.

Non-Cooperative Game in Block Bidding Markets Considering Demand Response

With the reform of electricity markets, demand response (DR) plays an important role in providing flexibility to the markets. Block bidding market is a new market mode, which is based on the concept of “the same quality, the same price”. The mechanism has great effects in reducing start-stop related costs. In this paper, we propose a double-sided non-cooperative game model in block bidding markets with a DR program. The model combines the advantages of block bidding and the simplicity of hourly bidding. In the model, one side is the non-cooperative game of supply-side power firms, and we propose a novel supply function bidding model based on block duration and load capacity to maximize each firm’s profit. The other side is the demand-side different types of customers, and we propose a DR model that combines hourly-various prices with the block bidding mechanism to maximize each customer’s payoff. The overall market optimization problem is solved by a distributed iterative algorithm, which has great convergence performance. We verify the proposed model on real data, and the results show that the demand load curve becomes flattened with DR, and the total generation costs decrease while the social welfare is significantly improved.

Two‐stage market‐based service restoration method in multi‐MGs distribution networks

The use of microgrids’ (MGs) surplus capacity is a valuable asset for distribution system operators (DSOs), which helps them to have better performance in an outage. In considering the private ownership of most MGs, it is necessary to provide proper mechanisms to compensate for the participation costs of MGs in service restoration programmes. In this study, a novel two-stage market-based framework is proposed to encourage MGs to share their surplus capacity during outages, in which the MGs will be paid proportionally to the amount of their exchanged energy with the distribution network. In the lower stage, MGs offer their hourly bids to the DSO in the form of price–quantity pairs, in which costs of their participation are calculated based on the AC optimal power flow equations. Thus, the operational constraints and power losses costs are incorporated. In the upper stage, for each hour, the DSO determines accepted bids considering technical and economic aspects. Some procedures are suggested to prevent MGs’ monopoly by offering overpriced bids. The advantages and validity of the proposed method are demonstrated in several numerical studies.

A Microgrid Energy Management System and Risk Management Under an Electricity Market Environment

This paper presents a novel energy-management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads. We assume that the microgrid takes part in a pool market and responds actively to the electricity price to maximize its profit by scheduling its controllable resources. To address various uncertainties, a risk-constrained scenario-based stochastic programming framework is proposed using the conditional value at risk method. The designed model is solved by two levels of stochastic optimization methods. One level of optimization is to submit optimal hourly bids to the day-ahead market under the forecast data. The other level of optimization is to determine the optimal scheduling using the scenario-based stochastic data of the uncertain resources. The proposed energy management system is not only beneficial for the microgrid and customers, but also applies the microgrid aggregator and virtual power plant. The results are shown to prove the validity of the proposed framework.

Risk-Constrained Bidding and Offering Strategy for a Merchant Compressed Air Energy Storage Plant

Electricity price forecasts are imperfect. Therefore, a merchant energy storage facility requires a bidding and offering strategy for purchasing and selling the electricity to manage the risk associated with price forecast errors. This paper proposes an information gap decision theory (IGDT)-based risk-constrained bidding/offering strategy for a merchant compressed air energy storage (CAES) plant that participates in the day-ahead energy markets considering price forecasting errors. Price uncertainty is modeled using IGDT. The IGDT-based self-scheduling formulation is then used to construct separate hourly bidding and offering curves. The theoretical approach to develop the proposed strategy is presented and validated using numerical simulations.

Market Power in Power Markets: An Analysis of Residual Demand Curves in California’s Day-ahead Energy Market (1998-2000)

2000, with a focus on its day-ahead energy market and its five non-utility thermal generating companies. Our goal is to assess whether the hourly bids of market participants, together with information on thermal unit characteristics and power output, suggest that the five suppliers were behaving in line with Nash supply function competition, bidding close to their marginal costs or restraining quantities relative to the Nash level. The analysis of residual demand inverse elasticities suggests that the five thermal generators had an incentive to exercise unilateral market power that was not always fully exploited. A comparison of market-clearing prices, estimated marginal costs and marginal revenues finds that firm conduct was broadly consistent with Nash supply function competition or more competitive than Nash behavior in most of our sample.

Risk-Constrained Profit Maximization for Microgrid Aggregators With Demand Response

In this paper, we consider the operation optimization for a microgrid (MG) aggregator, which can procure energy from various sources including the pool market and local distributed energy resources to serve MG customers. We assume that the MG aggregator sells electricity to customers at a predefined retail rate and it also offers customers various contracts for adjusting their loads. Our design objective is to determine the optimal hourly bids that the MG aggregator submits to the day-ahead market to maximize its profit. To deal with various uncertainties, a risk-constrained scenario-based stochastic programming framework is proposed where the MG aggregator's risk aversion is modeled using conditional value at risk method. The proposed formulation enables customers' demand response (DR) aggregation to be integrated into the operation of the MG aggregator via contractual agreements. This design is not only beneficial for both MG aggregator and customers, but also facilitates the operation of the system operator (SO), since a single entity (i.e., the MG aggregator) is visible to the SO instead of two separate entities (i.e., a MG aggregator and a DR aggregator). Extensive numerical results are shown to demonstrate the effectiveness of the proposed framework.

Design of a weekly hybrid power market in China facilitating connection of large-scale renewable generation

Summary In February 2002, the State Council of China published ‘Notice on Power Industry Reform’, which set out a clear road map for liberalising electricity industry in China. With the rapid development of large-scale renewable power and emergent surplus of generation capacity in major regional power systems, further market reform in China is necessary. This paper presents a weekly hybrid power market. The role of the administrative on-grid tariff system could be reduced and eventually withdrawn as the market matures and develops over time. This would eventually lead to a fully fledged power market. The competitive element of the hybrid market will initially be confined to coal-fired thermal units as they are by far the dominant generating source in China. The market is divided into two parts, block and hourly bidding. The block bidding is utilised in base load to reduce shutdown, and the hourly bidding is aimed at peak load to enhance flexibility. A linkage mechanism of settlement indirectly introduces grid companies and customers into the market. The simulation validates the well application of this hybrid power market to an actual large-scale power system. Rational results indicate the feasibility of this proposed market design. This design will provide some reference for other developing countries. Copyright © 2014 John Wiley & Sons, Ltd.

Measuring Market Power in Wholesale Electricity Italian Market

In the new deregulated competitive Italian electricity many interesting issues arise as the market complexity, the firm strategic behavior, the market power size, and so on. Effective competition in the electricity market is a necessary features of a successful supply industry restructuring. In this paper we examine the degree of competition in the Italian market during the period April 2004 to December 2004 in two principal ways. In the first one we estimate a very intuitive relation among the differences between the hourly equilibrium price (ph) and the individual hourly bids that the competitors offer around ph, and a large set of structural and behavioral variables. In the second one the aim is twofold. The first one is to build the residual demand for each Italian Generation Company. The construction of the residual demand curve system is the necessary condition to get the second aim which is to measure the unilateral market power for the Italian Generation Companies. Following Wolak (2003) approach the appropriate measure of the unilateral market power is the Lerner index based on the residual demand curve elasticity which is computed as arc elasticity. The expected results is a deeper understanding of the Wholesale Italian Electricity Markets and of its mechanism in order to enhance competition and to design appropriate market surveillance.

Hydrothermal self-scheduling problem in a day-ahead electricity market

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis.