Since the NEMS began operating on 1 January 2003, the market has adopted an ex-ante pricing regime whereby the spot prices for energy, regulation and reserve are determined by the market clearing engine (MCE) just prior to the start of each half-hour dispatch period. This paper assesses the arguments for and against price revision, and draws comparison to two other ex-ante pricing markets, the Australia National Electricity Market (NEM) and the Argentina Wholesale Electricity Market (WEM). It then presents EMC’s recommendations, which strive to balance the interests among all NEMS stakeholders.

Among the three products that are traded in the National Electricity Market of Singapore (NEMS), namely energy, reserve, and regulation, the regulation market is seen as the most volatile. On 4 June 2005, a price spike ($2,299.95/MWh) was observed in the regulation market in Period 14 (06:30–07:00). A detailed investigation revealed that a high price was set by a generator’s regulation offer. Before we find the root cause of such volatility, first we must better understand what regulation is and how it works in the NEMS. This is the primary goal of this paper.

This paper traces the dispatch pattern of five co-optimised products in the NEMS. The study was triggered by a query from a market participant that observed that one of its generating units was not fully dispatched although the marginal price was much more than its offered price, whereas another unit was dispatched above the marginal price offer block. This paper reports the result of the investigation and makes some recommendations to market participants regarding such instances.

One of the most revolutionary changes in the electricity industry worldwide over the last 20 years is the progression of pricing from fixed, to time-of-use to place-of-use. Place-of-use or locational marginal price is used in both the US and in Singapore, among others. The NEMS models the transmission system at the circuit level and therefore naturally employs the nodal price regime. Nodal prices differ because of two key factors: transmission congestion and transmission loss. This paper focuses on the relationship between nodal prices and transmission loss.

Since the NEMS began operation on 1 Jan 2003, nodal price separation has been observed a few times. Nodal price seperation occurs when the price difference between two adjacent nodes is well above the normal range that is incurred from transmission loss. In most of these cases, the spring washer effect was the cause of the pricing anomaly. This paper explores the spring washer effect in detail and discusses its relationship with nodal prices.

This paper studies the reasons for non-physical loss handling in the NEMS and focuses on the instances where it is triggered by a negative marginal offer price. It describes how the NEMS approximates the quadratic loss function and follows the solution step by step. A case study of an actual negative price case on 6 October 2003 is included.

The Market Clearing Engine (MCE) of the NEMS is a computer model that uses theoretically tight methods to determine optimal schedules that maximise social welfare while meeting system demand and satisfying the limits of generators, loads and the transmission system. The MCE solves the constraints, limits and requirements as a set of simultaneous linear equations to find an energy, regulation and reserves schedule that maximises the objective function of the greatest social welfare. It simultaneously determines prices for all constraints, which reflect the marginal cost of satisfying those constraints. As the MCE aims to find an optimal solution for energy, regulation and reserves as a whole, these products are always co-optimised in the MCE. Due to the complex nature of the NEMS model, the co-optimisation may not be easy to comprehend. This paper endeavours to explore the co-optimisation aspect of the MCE, in a step-by-step approach.