ELECTRICITY DISPATCHING IN A LIBERALISED MARKET
T. Chandarasupsang, T. Siewierski, S. Galloway, G. Burt, J.R. McDonald Institute for Energy and Environment, University of Strathclyde, UK
ABSTRACT This paper will present a Power Exchange Simulator developed to allow the investigation of market based dispatching (or self-dispatching) of participants in the competitive market. Different types of matching graphs have been applied to evaluate this software. The application of the Power Exchange Simulator and results will be presented and discussed, and will show that it has the capability to study market behaviour in order to better understand the impact of strategies implemented by electricity market participants in new competitive environments.
designed competition assists new entrants in entering markets and consequently, keeping electricity prices at a reasonable level for both consumers and suppliers. Section 2 describes dispatching process in electricity market under the Electricity Pool of England & Wales and the New Electricity Trading Arrangements. Section 3 and 4 presents the Power Exchange Simulator developed to investigate the dispatching of participants in the competitive market. Conclusion is then given in Section 6. In the following section, examples of liberalised electricity markets will be described focusing upon the electricity market in England & Wales.
1. INTRODUCTION The electricity industry has undergone many changes since the introduction of the competitive market. These changes are based on the belief that generation and supply need not be operated as a monopoly. The introduction of competition in electricity generation and market mechanisms brings a new dimension to how generators dispatch their output. The dispatching process described in this paper is applied to a modern energy market. In the past monopolies had complete control of electricity supply industries. Hence, it is not difficult to envisage that the relatively high prices of electricity which resulted, could drive reforms. Liberalisation refers to the introduction of a new regulatory framework for companies within a power sector [1]. This new framework is typically less restrictive and could also imply deregulation, which is the modification of existing regulation. Deregulation in the power sector often involves unbundling of electric utility services. This means breaking its basic components into generation, transmission, distribution and supply, and subsequently introducing competition to each component. However, deregulation is not only involved in unbundling, but it is also involved in separating ownership and operation. In most cases, competition is introduced gradually from wholesale market to retail market [2]. Although these two markets are relatively important to each other, over the past twenty years more attention has been paid to the wholesale market, as ultimately bulk power trading has the most effect on consumer prices. Also properly
2. DISPATCHING IN LIBERALISED MARKETS Generally speaking, dispatching producers involves scheduling generation to meet demand as economically as possible while taking into account operational constraints (e.g. transmission constraints or constraints on generators). In this section, a brief explanation of the Electricity Pool of England & Wales, and the New Electricity Trading Arrangements (NETA) are given. More details can be found in [3,4,5]. 2.1 The England and Wales Pool The Pool was first implemented in 1990 and although no longer in operation many other countries have adopted variations of this model. It was a mandatory mechanism for bulk power trading that operated with a uniform price single-sided auction (only small numbers of demand side participants were allowed to bid into the Pool). At the day-ahead stage, generators submitted offers of electricity for each half-hour of the following day. These offers indicated the prices and volumes of electricity that generators were prepared to produce at. The National Grid Company (NGC), as the Independent System Operator (ISO), was responsible for scheduling and dispatching generators to meet demand as well as maintaining a certain level of reserve capacity and preparing for ancillary services. Generators had a limited involvement in dispatching processes as under the Pool a centralised dispatch was performed by the ISO.
The dispatching process was based on offers from generators and estimated demand. A suitable dispatch schedule was determined initially at the day-ahead stage (unconstrained & constrained) and subsequently revised within-day. Merit order was employed to rank the offers from lowest to highest until volumes of electricity met anticipated demand. The most expensive generator selected (in unconstrained schedule) set the System Marginal Price (SMP). Buy and sell prices associated with the market were subsequently determined from the SMP. These prices had additional components, which accounted for the operation and management of the network. More details concerning the Pool can be found in [3]. Although the Pool worked satisfactorily in some respects, it was reported to be ineffective in some areas and subject to manipulation by large generators [3]. As a result, new trading arrangements were developed and first introduced from March 27, 2001. 2.2 The New Electricity Trading Arrangements One of the main principles for NETA was to introduce demand side participation through the introduction of competition. This is in contrast to the Pool. Further, direct competition in the trading environment was expected to significantly influence prices and with suitable design devolve risk from the market to the participants themselves. NETA provides mechanisms as follows [4]: • Forward trading: the market allows participants to strike up bilateral contracts up to several years in advance. • Balancing Mechanism (BM): the ISO (NGC) accepts bids and offers to balance demand and supply near to real time. • Imbalance Settlement: price settled for differences between contractual position and actual position.
electricity was traded in the BM during the first three months of NETA operation [4]. However, this still represents a not insignificant volume of trades. Also, the ISO can call for ancillary services during this period from service providers who they have contracted [4]. In the Settlement Process, participants are paid and charged for electricity on the basis of differences between declared contractual position (FPN), modified by accepted bids and offers in the BM period, and the actual metered position [5]. 2.3 NETA Market Participation Under NETA, some plants or generating units find it difficult to participate because NETA mechanisms suit plants which are flexible and also have firm output [6]. For example, some renewable generators are not able to accurately predict their output far ahead (wind turbines) and consequently consider it risky to participate in the forward contracts market. Under NETA mechanisms, such uncertainty could lead to significant imbalance charges. It is therefore advantageous to understand the market behaviour in order to better participate in the opportunities that it provides. This is not only critical for non-firm generators, but is also to the advantage of all generators as it may influence their participation strategy and help in their self dispatch. This paper presents a simulator that supports this.
3. POWER EXCHANGE SIMULATION MODEL A Power Exchange Simulator (PXS) has been developed which accounts for both central and selfdispatching of generators. Different types of matching graphs are applied to evaluate this software allowing different bidding strategies to be compared.
Under NETA majority of energy is traded in the forward market [4]. Participants can freely negotiate and enter into bilateral contracts for electricity. The market outcome from these contracts is called the ‘Final Physical Notification’ (FPN) and must be notified to the ISO by Gate Closure (GC). The GC is set to be 3 ½ hours ahead of physical delivery. The FPN informs the ISO of net volume, counter-parties and delivery time. This information is then employed by the ISO when operating the BM. Generators participating in the forward market self-dispatch their generating units based on their contracted positions. The generators must also respond to accepted bids and offers which are selected centrally through the BM by the ISO.
In the following sub-sections, the matching procedures and evaluation of PXS will be outlined.
The BM is an optional market. It operates on a pay as bid basis, so an accepted offer (bid) receives (pays) its own offer (bid) price. The selection (dispatching) of BM bids and offers by the ISO is purely a centralised market issue, however this clearly influences the self-dispatch of market participants. It was reported that only 3% of
In Figure 1, volumes to the left of the crossing point are traded at the clearing (marginal) price. It also shows that there are still demands for electricity which are not met by the supply (right-hand side of the crossing point). As a result, there should always be another mechanism to compensate unmet demands.
3.1 Matching process Participants, who want to trade electricity in a Power Exchange, submit bids and offers to the ISO in keeping with market timescales. These bids and offers are ranked, typically in merit order, to create demand and supply curves. The point of intersection between these two curves gives the clearing price. The period of each trading interval in the market depends on the market rules that prevail. For example, the England & Wales operates with 48 half-hour trading periods. An example of a matching process is illustrated in Figure 1.
4.1 Case Study 1 In Case Study 1, five pairs of offers and four pairs of bids have been chosen to create supply and demand curves using the PXS. Figure 3 shows supply and demand curves generated from the submissions given in Table 1.
Supply curve
Price (£/MWhr) Market Clearing Price
Price (£/MWhr)
40 38 36
Demand curve Matched Energy
34 32
Volumes (MWhr)
30
Figure 1: Matching procedure
28 26
3.2 The Design of PXS Figure 2 shows an outline of the PXS. Different types of matching graphs have been created to check the operation of a PXS in basic price calculation as well as the volumes to be traded. Eleven different supply and demand curve structures are accounted for within the PXS. In particular, the focus is on how to deal with different types of supply and demand curve intersections. PXS Bid (Volume & Price)
Supply and demand curve
24 22 20
0
100
200
300
400
500
600
700
Volumes (MWhr)
Figure 3: Supply and demand curves for Case 1 Table 1: Market Participants Submission (MWhr) Participant Trader 1 Trader 2 Buyer 1 Buyer 2
£40/MW hr 70 80 20 30
Buy Submissions £35/MW £25/MW hr hr 30 40 40 50 40 30 40 30
£20/MW hr 50 50 50 50
Schedule Participant Adopted strategy
Figure 2: An outline of the PXS For the purposes of the investigation six market participants will be considered active within the PXS: two traders, two buyers and two sellers. Note that here traders are active as both buyers and sellers. Further, it is assumed that traders have the means to purchase power independently of the PXS. The characterised market mechanism is similar to that implemented under NETA and is based on a simple auction system. In the following section, example case studies are used to evaluate the PXS software.
Trader 1 Trader 2 Seller 1 Seller 2
£40/M Whr 10 20 30 40
Sell Submissions £35/M £30/M £25/M Whr Whr Whr 40 15 50 10 10 50 30 55 50 20 20 50
£20/M Whr 25 25 25 25
In Figure 3 there is a cross-point between generation and consumption and hence, a true SMP exists (£30/MWhr). Potentially several producers contribute to the supply (production) curve over the range [300,400] MWhr. The problem is how to decide fairly which generators generate and which do not. From the submission in Table 1 it can be obtained that the total output (as bid) by these participants is 100 MWhr: Trader 1, Trader 2, Seller 1 and Seller 2 have submitted the volumes 15 MWhr, 10 MWhr, 55 MWhr and 20 MWhr respectively at bid £30/MWhr.
4. EVALUATION OF PXS In this section a case study will be described and the results upon implementation of the PXS reported. The focus is mainly on how this program deals with the following four issues: • Bid acceptance and processing • Price calculation • Volumes to be traded • Volume reduction procedure
Since the demand curve crosses the supply curve at (350 MWhr, £30/MWhr) the required power at this price 50 MWhr (350-300 MWhr) must be allocated to either some or all of the producers who have bid £30/MWhr to the power exchange. Note here that the ordering of offers at the same price depends solely on the rules for that particular market place. Let us now assume that the PXS ordered these offers, say by submission time, as shown in Figure 4.
Price (£/MWhr)
Demand curve Supply curve
£30/MWhr
Trader Trader 2 1
Seller 1
Seller 2
4.2 Case Study 2 Five pairs of offers and three pairs of bids have been chosen to construct the supply and demand curves in Case Study 2. Figure 5 shows supply and demand curves generated from the submissions given in Table 3 to the PXS. Price 40 (£/MWhr) 38 36 34
300
315
325
350
380 400 Volume (MWhr)
32 30
Figure 4: Possible distribution of participants
28 26
Considering the distribution of generators shown in Figure 4, one way of dispatching would be as follows: • Trader 1 produces 15 MWhr • Trader 2 produces 10 MWhr • Seller 1 produces 25 MWhr • Seller 2 produces 0 MWhr
24 22 20
0
100
200
300
400
500
600
700
Volumes (MWhr)
Figure 5: Supply and demand curves for Case 2 Table 3: Market Participants Submission (MWhr)
However, by only considering the ordering of these four market participants as shown in Figure 4 Seller 1 and Seller 2 are discriminated against. In order to allow all participants to sell electricity, the equivalent way to resolve this issue is to share the dispatch proportionately between the four market participants. The demand curve bisects the supply curve, over the interval [300,400] MWhr, into two parts. As a percentage this division can be determined proportionately as follows: Length of subinterva l Length of wholeinter val
=
(350 − 300 ) [MWhr ] × 100% = 50% (400 − 300 ) [MWhr ]
Hence the production (as bid) of Trader 1, Trader 2, Seller 1 and Seller 2 will all be reduced by 50%. Thus, Table 2 shows the original bids and new production figures, together with the resulting totals. This new production is generated by the PXS taking into account volume reduction procedure. Table 2: Original bids and New production figures Participants Trader 1 Trader 2 Seller 1
Original 15 MWhr 10 MWhr 55 MWhr
New 7.5 MWhr 5 MWhr 27.5 MWhr
Seller 2 Total
20 MWhr 100MWhr
10 MWhr 50MWhr
Clearly, the reduced production levels allow all generators to generate. Note that there is no movement in the SMP, this remains at £30/MWhr. The simple proportionate reduction method described above is also employed in the adjustment of consumption case where the crossing point is on the flat line of demand curve.
Participant Trader 1 Trader 2 Buyer 1 Buyer 2
Participant Trader 1 Trader 2 Seller 1 Seller 2
£40/MWhr 75 75 75 75
£40/M Whr 30 10 40 20
Buy Submissions £32/MWhr 30 40 20 10
£25/MWhr 75 75 75 75
Sell Submissions £35/M £30/M £25/M Whr Whr Whr 70 40 50 60 30 50 50 20 50 20 10 50
£20/M Whr 10 20 30 40
In Figure 5 the consumption curve meets the generation curve at 400 MWhr. However, there are many possible prices that could be chosen to be the SMP. Genuine markets facing this condition would rely on the rules for different power exchanges to determine the procedure. For the PXS, the procedure adopted is to choose the cheapest price (maximising consumer welfare) to be the SMP. Thus, the SMP is set to be £30/MWhr (see Figure 5) 4.3 Results Matching graphs give us an opportunity to evaluate this software focusing on how it deals with the basic price calculation and volumes to be traded. Results received by running the PXS for simple problems have concurred with the results obtained by ‘hand calculation’. The PXS is being applied to larger problems involving many more market participants. As previously presented in this section, only a single period has been considered when evaluating this software. However, it is recognised that a more dynamic simulation over a number of dispatch periods will raise more complex planning issues with respect to dispatching (e.g. Start up cost and no load costs).
Results indicate that the software developed has the capability to investigate issues− alternative bidding strategies− arising in electricity markets and can be further extended to deal with work on other parts of the market. For example, this software (after further development) could be used to study ‘Block bids’ taking more account of constraints on generator (currently implemented in NordPool). This bidding type assists plants who want to participate in a power exchange, but need more than a single period according to their dynamic characteristics to ramp up their output to a target level.
5. CONCLUSION In this paper, a review of electricity markets focusing on the dispatching process has been described. Further, a brief explanation is given of how a power exchange operates in the competitive electricity market. This supports the need for participants to be able to simulate how their bids might be received by markets such as in a power exchange. A power exchange simulator which provides this capability has been presented and demonstrated for some simple examples. Results show that the PXS has the potential to become a powerful tool to study the impact of bidding strategies and consequently assist market participants adapt their bidding strategy. Key areas for future work include incorporating dynamic market behaviour, additional market mechanisms such as bilateral contracts, and future mechanisms such as block bids. REFERENCES 1.
2.
Yuen, Y.S.: “Deregulation of Electricity Utilities”, “Power System Restructuring and Deregulation”, Edited by L.L. Lai, John Wiley & Sons Ltd., 2001 Green, R.: “England and Wales- A Competitive Electricity Market? ”, Working Papers Series, University of California, September 1998. Web site available at www.ucei.berkeley.edu/ucei
3.
Sweeting, A.: “The Wholesale Market for Electricity in England & Wales: Recent Developments and Future Reforms, Department of Economics, Massachusetts Institute of Technology, Cambridge MA 02139, September 5, 2000
4.
The Office of Gas and Electricity Markets: “The New Electricity Trading Arrangement: three months review document”, August 2001. Web site available at www.ofgem.gov.uk
5.
The Office of Gas and Electricity Markets: “An Overview of the New Electricity Trading Arrangements: A high-level explanation”, May 31, 2000. Web site available at www.ofgem.gov.uk
6.
The Office of Gas and Electricity Markets: “Report to the DTI on the Review of the Initial Impact of NETA on Smaller Generators”, November 1, 2001. Web site available at www.ofgem.gov.uk
AUTHOR’S ADDRESS The first author can be contacted at: Institute for Energy & Environment, University of Strathclyde, Department of Electronic and Electrical Engineering, Royal College Building, 204 George Street, Glasgow, G1 1XW, UK Email:
[email protected]
BIOGRAPHIES Tirapot Chandarasupsang received his BEng degree in Electrical Engineering from King Mongkut’s Institute of Technologies Ladkrabang, Bangkok, Thailand in 2000. He is now studying to obtain a Ph.D. degree at the University of Strathclyde. His research is in the area of power system economics and energy markets. Dr Tomasz Siewierski received his M.Sc. in 1988 from the Technical University of Lodz in Electrical Engineering and his Ph.D. in 1996 from University of Pavia, Italy for his research dealing with the application of Direct Methods in the analysis of Power System Stability. Since 1999 he has focused on the theory and practice of open energy market operation and in 2001 he has been appointed research fellow at the University of Strathclyde, in the Centre for Electrical Power Engineering, working in the area of energy market modelling and simulation. Dr Stuart Galloway received his BSc(hons) degree in Mathematical Sciences from the University of Paisley, an MSc in the Mathematics of Non-Linear Modelling jointly from the Heriott Watt and Edinburgh Universities, and a PhD from the University of Edinburgh. His research interests include electricity market modeling, game theory, economic modeling and optimisation. Dr Graeme Burt received a BEng in Electrical and Electronic Engineering in 1988 and a PhD in 1992, both from the University of Strathclyde. He is currently Associate Director of the Rolls-Royce University Technology Centre in Power Engineering at the University of Strathclyde. His research interests lie in the areas of intelligent system applications in power engineering, optimisation and scheduling, power system & energy market modeling and simulation, embedded generation. Professor Jim McDonald holds the Rolls-Royce Chair in Power Engineering at the University of Strathclyde Professor James R. McDonald received his BSc and PhD degrees from the University of Strathclyde. He was appointed as the Manager of the Centre for Electrical Power Engineering at the University of Strathclyde in July 1990 and took up the position of the Rolls-Royce Chair in Power Engineering in February 1994. He has recently been appointed as the Director of the Institute for Energy & Environment. His research activities lie in the areas of: Power System Protection and Measurement; Expert System Applications in Power Engineering; Energy Management. He has published over 250 technical papers and three books.
