Block Bidding Research Articles

Optimization strategy of power purchase and sale for electricity retailers in a two-tier market

Against the backdrop of the gradual advancement of China's electricity market reform, the number of Power Trading Companies in China has been increasing year by year, and as of October 2022, the number has reached more than 10,000. As an important hub connecting the electricity market and users, electricity retailers face double risks from downstream user load fluctuations and electricity market price fluctuations. Therefore, a reasonable power purchase and sale strategy is very important for an electricity retailer. In this study, a block bidding mechanism is adopted to optimize the clearing of the medium-to long-term market and a DA-RBF neural network is established for spot electricity price forecasting model based on numerical feature similarity to improve the accuracy of electricity price forecasting. Furthermore, the model considers the differences in user demand responses and investigates the optimal power purchase and sale strategy, guided by differentiated time-of-use electricity pricing. The case study analysis demonstrated that the proposed power purchase and sale optimization strategy yields favorable results, improving profitability and enhancing the stability of the power system.

E&P Notes (October 2021)

E&P Notes (October 2021)

Optimising block bids of district heating operators to the day-ahead electricity market using stochastic programming

The wide spread of district heating in Denmark offers a massive potential for flexibility in an energy system with intermittent renewable energy production. To leverage this potential, a cost-efficient power market integration of combined heat and power (CHP) units in district heating systems is important. We propose a stochastic program optimising block bids to the day-ahead market for CHP units in district heating systems under uncertain power prices. Block bids allow the internalisation of start-up costs. Based on the stochastic program, we develop a solution approach based on sample average approximation (SAA) to solve the stochastic program for a large number of price scenarios. We present results for a case study from Middelfart, Denmark. The system consists of two sub-networks that have lately been connected. We analyse the block bidding behaviour with and without connection using real data from different seasons. The results show that the bidding varies significantly depending on seasons and the layout of the network. Furthermore, the results show that the solution approach based on SAA reduces computation time significantly while maintaining solution quality.

Fiscal and tax terms and economic evaluation methods for oil and gas projects in Abu Dhabi

The Middle East is the region with the lowest oil and gas production cost in the world and has always been the key area for investment by oil companies. With the large-scale bidding after the Iraq War, the number of bidding blocks provided annually in the Middle East has been greatly reduced, and the number of bidding blocks provided by the UAE government is relatively large. After the expiration of the existing contracts in 2014, the UAE government started block bidding and auction on a large scale, and offered favorable contract terms. The assets with great investment values attracted international oil giants. In this paper, based on the survey of bidding contracts of Abu Dhabi in recent years, fiscal and tax terms, demand markets, prices and costs to be focused on have been sorted out, an economic evaluation model for bidding blocks in Abu Dhabi has been established, and evaluation conclusions have been drawn through financial analysis and uncertainty analysis. Finally, the applicability of the economic evaluation analysis method and evaluation procedure has been verified through examples, so as to provide reference and enlightenment for international oil companies to participate in the new round of bidding of the UAE in the future.

Analysis on the preparation of construction cost business

The construction cost business mainly includes the preparation of bill of quantities, the preparation of the tender control price, settlement auditing, and the whole-process cost management. Specifically, bill of quantities is the basic document of the bidder’s unified quotation provided by the tenderer. The tender control price is the maximum construction cost limited by the bidder on the proposed construction project, which is also called block bid price, bid control price or the highest quotation. The settlement auditing refers to the process of the construction enterprises handling the project price settlement with the construction unit (owner) in accordance with the contract and the completed project quantities. Generally, the construction unit entrusts a consulting agency with appropriate qualifications to calculate and review the submitted settlement until all parties perform links such as confirming the amount. The whole-process cost management is the process of investment management for all or part of the construction project from decision-making to completion.

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.

An auction story: How simple bids struggle with uncertainty

Abstract Short-term electricity markets are key to an efficient production by generation units. We develop a two-period model to assess different bidding formats to determine for each bidding format the optimal bidding strategy of competitive generators facing price-uncertainty. We compare the results for simple bidding, block bidding and multi-part bidding. We find that even under optimal simple and block bidding, generators face the risk of ex-post suboptimal solutions, whereas in multi-part bidding these do not occur. This points to efficiency gains of multi-part bidding in the presence of uncertainty in electricity markets.

Optimal pricing strategy of power‐retailing companies considering demand response in block bidding markets

Block bidding market (BBM) is a new electricity market mode in the day-ahead market, which is in the stage of development and promotion in China. It is based on the idea that energy should have the same price according to the continuous duration of load. In this study, the authors propose an optimisation model of pricing and purchasing strategy for power-retailing companies in BBMs, based on bilateral contracts with customers and portfolio management of demand response resources. The model consists of an expected profit maximisation problem of supplying energy to end-customers, and a total cost minimisation problem concerning the dispatching of fixed loads and shiftable loads. The proposed model is formulated as a bi-level mixed-integer non-linear program. A load division method is proposed to get better division result by eliminating duration restrictions on divided blocks. The proposed approximate solving algorithm overcomes the diculties in linearisation and gets rid of the inuence of initial value. The strategy is applied to an actual case and is simulated based on real data. Simulation results show that the proposed model has great peak-shaving effects, and can effectively bring more profit to the power-retailing companies while reducing electricity bills of customers.

Algorithm design for European electricity market clearing with joint allocation of energy and control reserves

In order to enhance the liquidity and stability of ancillary service markets in Europe and to motivate the participation of renewable energy resources, the incorporation of control reserve procurement into day-ahead power exchanges (PXs) is proposed. The design of the corresponding clearing algorithm is presented in detail. The model allows the submission of combined energy-reserve orders and guarantees that opportunity costs of power producers are taken into account. It can also handle non-convex offers (e.g. block bids) and market coupling that are essential components of European PX designs. The formulated optimization problem can be classified as a convex Mixed Integer Quadratic Program; consequently, its solution can be found using readily available generic solvers. A numerical simulation is executed for the purpose of demonstration and also to make a comparison between joint and separated allocation of energy and reserves. The simple initial analysis suggests that the proposed integration approach is beneficial.

An Auction Story: How Simple Bids Struggle with Uncertainty

Short-term electricity markets are key to an efficient production by generation units. We develop a two-period model to assess different bidding formats to determine for each bidding format the optimal bidding strategy of competitive generators facing price-uncertainty. We compare the results for simple bidding, block bidding and multi-part bidding and find that even under optimal simple and block bidding generators face the risk of ex-post suboptimal solutions, whereas in multi-part bidding these do not occur. This points to efficiency gains of multi-part bidding in the presence of uncertainty in electricity markets.

On the efficiency of local electricity markets under decentralized and centralized designs: a multi-leader Stackelberg game analysis

In this paper, we analytically compare centralized and decentralized market designs involving a national and local market operators, strategic generators having market power and bidding sequentially in local markets, to determine which design is more efficient for the procurement of energy. In the centralized design, used as benchmark, the national market operator optimizes the exchanges between local markets and the generators’ block bids. In the decentralized design, generators act as Stackelberg leaders, anticipating the local market prices and the flows on the transmission lines. Clearing of the local markets can be either simultaneous or sequential. The resulting two-stage game with competitive leaders that are not price takers is formulated as a bilevel mathematical programming problem which is reformulated as a Nash–Cournot game, and conditions for existence and uniqueness of market equilibrium are studied. Imperfect information is also considered, resulting from the lack of incentives from the generators to share their RES-based generations. Through a case study, we determine that the decentralized design is as efficient as the centralized one with high share of renewables, using as performance measure the price of anarchy, and that imperfect information has a limited impact on the efficiency of the decentralized market design. Furthermore, we check numerically that there exists an upper-limit on the block bid length maximizing the social welfare under both centralized and decentralized designs.

Revisiting minimum profit conditions in uniform price day-ahead electricity auctions

We examine the problem of clearing day-ahead electricity market auctions where each bidder, whether a producer or consumer, can specify a minimum profit or maximum payment condition constraining the acceptance of a set of bid curves spanning multiple time periods in locations connected through a transmission network with linear constraints. Such types of conditions are for example considered in the Spanish and Portuguese day-ahead markets. This helps describing the recovery of start-up costs of a power plant, or analogously for a large consumer, utility reduced by a constant term. A new market model is proposed with a corresponding MILP formulation for uniform locational price day-ahead auctions, handling bids with a minimum profit or maximum payment condition in a uniform and computationally-efficient way. An exact decomposition procedure with sparse strengthened Benders cuts derived from the MILP formulation is also proposed. The MILP formulation and the decomposition procedure are similar to computationally-efficient approaches previously proposed to handle so-called block bids according to European market rules, though the clearing conditions could appear different at first sight. Both solving approaches are also valid to deal with both kinds of bids simultaneously, as block bids with a minimum acceptance ratio, generalizing fully indivisible block bids, are but a special case of the MP bids introduced here. We argue in favour of the MP bids by comparing them to previous models for minimum profit conditions proposed in the academic literature, and to the model for minimum income conditions used by the Spanish power exchange OMIE.

A MIP framework for non-convex uniform price day-ahead electricity auctions

It is well known that a market equilibrium with uniform prices often does not exist in non-convex day-ahead electricity auctions. We consider the case of the non-convex, uniform-price Pan-European day-ahead electricity market “PCR” (Price Coupling of Regions), with non-convexities arising from so-called complex and block orders. Extending previous results, we propose a new primal-dual framework for these auctions, which has applications in both economic analysis and algorithm design. The contribution here is threefold. First, from the algorithmic point of view, we give a non-trivial exact (i.e., not approximate) linearization of a non-convex ‘minimum income condition’ that must hold for complex orders arising from the Spanish market, avoiding the introduction of any auxiliary variables, and allowing us to solve market clearing instances involving most of the bidding products proposed in PCR using off-the-shelf MIP solvers. Second, from the economic analysis point of view, we give the first MILP formulations of optimization problems such as the maximization of the traded volume, or the minimization of opportunity costs of paradoxically rejected block bids. We first show on a toy example that these two objectives are distinct from maximizing welfare. Third, we provide numerical experiments on realistic large-scale instances. They illustrate the efficiency of the approach, as well as the economics trade-offs that may occur in practice.

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.

Proposal of Block Bidding for Large-Scale Wind Power Energy

It is necessary for power systems to provide flexible power to balance the fluctuation and intermittency of wind power. For the large-scale and central-integrated wind generation (such as that in China), the required flexible power may be very significant and expensive. In market environment, it is important to design a proper market mechanism and price signal which can promote conventional power and load demand to integrate wind power and gain corresponding profit. Firstly, the paper analyzes the current economy and dispatch policy for wind power in China. Then, a Block Bidding mode for wind power is presented. Unlike Timely Bidding mode that power is auctioned hourly by hourly, for Block Bidding the wind power energy is divided into different energy block. And these blocks are auctioned by conventional power resources and load demands. The Block Bidding mode has some advantages: 1) subdivides wind power by energy quality, and then the value of different parts can be revealed; 2) provides incentive for conventional power resource and load demand to integrate wind power; 3) is convenient for trading and dispatching wind power. Finally, a simple numerical case is given to illustrate the validity of Block Bidding mode.

Electricity trading in Indian restructured power market

In the past few years, most of the electricity industries around the world have been undergoing a movement from monopoly utilities to restructured competitive electricity markets. At present time, the operation of electricity markets all over the world varies from one country to another. Indian electricity market is trading with power transactions through power exchanges. Practically, Indian power market structure consists of the central generating station, state generation and power producers. This paper describes the methodology to utilise the central generating station and state owned generation in addition with the power procured from independent power producers to meet the daily load demand. Market clearing price for various load conditions has been analysed in both supply side and demand side bidding scenarios for block bid trading model.

Congestion management with generic load model in hybrid electricity markets with FACTS devices

The load variations during the entire day specially during the peak hours have substantial impact on the loading pattern of the transmission system. The voltage profile become poor during such situation of peak loading of the network and can lead to congestion during such events. This paper attempts congestion management considering the impact of constant impedance, current, and power (ZIP) load model along with the load variation pattern in a day-a-head hybrid electricity market. The main contribution of the proposed work is: (i) Optimal rescheduling based congestion management for a hybrid market model with three bid offer from generators, (ii) study of the impact of ZIP load model and load variations on rescheduling and congestion cost, (iii) impact of third generation FACTS devices on congestion management, (iv) comparison of results obtained for hybrid market model without and with ZIP load model. The generators offer three block bid structure to the ISO in a day-a-head market for congestion management. The base case economic load dispatch has been obtained for generators and is taken as base case generation output data during the congestion management to obtain new generation schedule. The three block bid structure submitted to the ISO has been modeled as a linear bid curve which is a function of increment/decrement (inc./dec.) of generation within the upper and lower bounds offered for congestion management. The results have been obtained for IEEE 24 bus test systems.

Adjustable Profile Blocks With Spatial Relations in the Day-Ahead Electricity Market

The concept of adjustable combinatorial products within the scope of the day-ahead electricity market is introduced in this paper. These adjustable products comprise simple and linked profile block offers/bids, with a variable energy quantity profile during the block periods. In the proposed formulation, these blocks can be partially cleared, namely, the indivisibility of the classical profile blocks that are present in European markets is relaxed. This flexibility allows the elimination of paradoxically accepted and rejected blocks and, thus, the elimination of iterative heuristic procedures for their handling. Such modeling is not possible as a mixed-integer linear programming problem, due to the inherent indivisibility denoted by the use of binary variables. Additionally, advanced profile bids are formulated for demand entities, called “joint demand profile block bids” in this paper, which involve not only inter-temporal relations, but also spatial relations with each other. This two-dimensional relation between demand profile blocks is novel and is deemed feasible with the model presented here. These advanced profile orders are incorporated in a day-ahead market problem, formulating a mixed complementarity problem model, which is solved using commercial solvers. The model is validated using the IEEE RTS-96 system; nevertheless, its scalability to large real-world power systems is straightforward.

Congestion management with FACTS devices in deregulated electricity markets ensuring loadability limit

This paper addresses an important issue of transmission system congestion management in a pool electricity market environment with the consideration of voltage stability as loadability limit. The optimal generators’ rescheduling has been obtained for three block bid structure submitted to the ISO in a day-a-head market. The base case economic load dispatch has been obtained for generators ensuring the loadability limits and is taken as base case generation output data during the congestion management to obtain new generation scheduling. The generation pattern has been obtained for three bid blocks taking load variation for 24h considering load scaling factor. The three block bid structure offered to the ISO has been modeled as a linear curve, function of up and down rescheduling within the upper and lower limits offered for congestion management. The impact of third generation FACTS devices has also been studied on the optimal rescheduling of generators’ outputs and thereby the congestion cost. The results have been obtained for IEEE 24 bus and IEEE 57 bus test systems.