The economic, political, strategic and cultural dynamism in Southeast Asia has gained added relevance in recent years with the spectacular rise of giant economies in East and South Asia. This has drawn greater attention to the region and to the enhanced role it now plays in international relations and global economics.

The sustained effort made by Southeast Asian nations since 1967 towards a peaceful and gradual integration of their economies has had indubitable success, and perhaps as a consequence of this, most of these countries are undergoing deep political and social changes domestically and are constructing innovative solutions to meet new international challenges. Big Power tensions continue to be played out in the neighbourhood despite the tradition of neutrality exercised by the Association of Southeast Asian Nations (ASEAN).

The Trends in Southeast Asia series acts as a platform for serious analyses by selected authors who are experts in their fields. It is aimed at encouraging policymakers and scholars to contemplate the diversity and dynamism of this exciting region.

INTRODUCTION

When the first Malaysian national automaker Proton sold a 49.99 per cent share to the Chinese auto firm Geely in 2017, former Prime Minister of Malaysia Mahathir Mohamad who considers the national car project his brainchild said the acquisition was akin to him “losing a child”. If the national car project is a lost child, then the national motorcycle project can be likened to an orphan. Key players including Mahathir himself were once enthusiastic about the prospects of a national motorcycle “helping the country to achieve a highly motorized population”, with grandiose aspirations of exporting the national motorcycle to ASEAN, South Asia, Latin America and Africa. However, the motorcycle became a forgotten child—following the Second Industrial Master Plan, subsequent automotive policies and industrial plans offered few concrete policies for developing the two-wheeler (2W) sector.

As will become clear in the next section, throughout the 1980s and 1990s, the dominant narrative was to develop domestic manufacturing capabilities in small engines and eventually a national motorcycle, supported by the “lucrative Malaysian market”, the “huge potential” of the export market, and an association between a highly motorized population and development. Outlined in the Second Industrial Master Plan (1996–2005), the first national motorcycle project, Modenas, was implemented to “shift the development strategy of the sector from assembly and component parts manufacturing for the domestic market, to become an integrated motorcycle manufacturing sector supplying products at competitive prices for the export market”. This shift included “having an own design motorcycle being manufactured locally”. As with the national car project, Malaysia's aspiration for a national motorcycle is not just about having it made in Malaysia (that is, assembly alone), but also being “locally designed” and “develop[ing] components with own design & brand”, for which investments in Research and Development (R&D) are crucial. This focus on increases in local value addition based on input from national producers and on national technical capabilities is the essence of what Doner, Noble and Ravenhill (2021) term intensive growth. It is opposed to extensive growth which focuses on vehicles and components assembly and in some cases exports, primarily under the aegis of foreign producers operating in global value chains.

This chapter defines the economic dispatch problem and analyzes the KKT conditions that characterize the optimal solution. We then define competitive markets, aggregate variable costs, aggregate marginal costs, aggregate benefit, and aggregate marginal benefit in order to characterize price and quantity adjustment in markets. This allows us to define competitive market equilibrium and competitive price. The equivalence between competitive equilibrium and the optimal solution of the economic dispatch problem is established using KKT conditions. This equivalence is generalized to the context of more general market models with multiple products, and the generalized result is used repeatedly throughout the textbook for establishing the equivalence between market models and centralized optimization problems, which is the cornerstone of the argued efficiency of competitive markets.

This chapter introduces topics that extend beyond the electricity market, and focuses in particular on oil, natural gas, and biofuels. Short- and long-term equilibriums are analyzed in the context of oil markets. Monopolies, cartels, and the model of the dominant firm are also analyzed in the context of the oil market. The tax incidence problem is formulated as an equivalent optimization problem and analyzed in the context of natural gas markets. One-way substitutability is analyzed in the context of biofuel markets, and the tortilla crisis is illustrated through an optimization model. Hotelling’s rule is stated and proven by considering a dynamic optimization model of a finite nonrenewable resource that is gradually depleted over time while satisfying a price-elastic demand.

This chapter discusses the application of operations research models in the energy industry. The applications that are covered include linear programming in the economic dispatch problem, mixed integer programming in unit commitment, nonlinear programming in the alternating current optimal power flow, stochastic programming in hydrothermal scheduling, and various other classes of mathematical programs. The capacity expansion problem is then analyzed through an analytical approach that relies on load duration curves and screening curves. The model is used to highlight the missing money problem in energy only markets with price caps, introduces the notion of competitive equilibrium, and discusses the distinction between short-term and long-term competitive equilibrium.

This chapter presents the direct current optimal power flow (DCOPF) problem, which is a linear approximation of the alternating current optimal power flow problem. Two equivalent formulations of the DCOPF are provided: one based on power transfer distribution factors (PTDFs), and one based on susceptances. The optimal solution of the DCOPF is characterized using the KKT conditions of the model. The optimal transmission switching and optimal transmission expansion problem are introduced. The nodal pricing or locational marginal pricing (LMP) mechanism is defined, and various properties of LMPs are characterized through examples and KKT conditions. Congestion rent and congestion cost are defined and compared. The equivalence of DCOPF to a competitive market model for transmission and energy is established using KKT conditions. A DCOPF with losses is introduced. Zonal pricing is defined, and the motivations of its origins are discussed. Two models of zonal pricing are analyzed, one based on a transportation network and one based on flow-based market coupling. Various notions of zonal pricing are defined, including available transfer capacities, loop flows, transit flows, critical branches, zone-to-line PTDFs, remaining available margin, and generation shift keys. Redispatch is defined and demonstrated through examples, and the INC-DEC gaming strategy is described.

This chapter described the intended audience of the book, summarizes the content of each chapter, describes the use of the material in courses, describes how exercises are used in the book, provides explanations about notation and terminology, and includes acknowledgements.

This chapter covers basic concepts in power system operations and electricity markets. Basic concepts of power generation include variable cost, marginal cost, fixed cost, investment cost, the weighted average cost of capital, and the definition of a natural monopoly. Basic concepts of transmission and distribution include a discussion of Ohm’s law, Kirchhoff’s laws, the power flow equations, and the direct current power flow. Basic concepts of consumption include the notion of valuation/marginal benefit, demand functions, demand elasticity, and the value of lost load. The actors of electricity markets are introduced, including transmission/independent system operators, distribution system operators, utilities, load serving entities, retailers, power exchanges, and transmission companies. Reserves and ancillary services are then introduced, and details about the forward-looking and rolling nature of power system operations are discussed. Exchanges and pools are informally defined, and the debate between uniform and pay-as-bid pricing is detailed. A blueprint of a typical electricity markets, with the participating actors and traded products and services, is introduced. The California and Central Western European markets are compared in order to introduce the debate between zonal and nodal pricing, as well as different approaches in pricing.

This chapter discusses various approaches to demand response, including time-of-use pricing, critical peak pricing, interruptible service, and priority service pricing. A quantitative model of time-of-use pricing is presented, and its properties are analyzed using the KKT conditions of the model. A model of priority service pricing is presented, whereby an aggregator offers different levels of reliability in power service at different prices. The model is described as a leader-follower interaction, where the leader is the aggregator that prices contracts and the followers are residential customers who select menu options.

This chapter introduces ancillary services, focusing specifically on reserves. Reserves are classified in terms of their response time between primary (frequency containment, automatic generation control, load frequency control, regulation), secondary (frequency restoration reserve, operating reserve, spinning reserve, non-spinning), and tertiary (or replacement reserve). Contingency reserve and flexible ramp products are also discussed. Interactions between reserves are discussed. A co-optimization model of energy and reserves is presented, and its optimal solution is characterized using KKT conditions. The security-constrained economic dispatch model and the N-1 reliability criterion are introduced. A centralized optimization model for simultaneous auctioning of energy and reserves is introduced, and its equivalence to a market equilibrium is established. The sequential clearing of energy and reserves is presented. Market models for multiple types of reserves are introduced, and the effect of substitutability is discussed. Operating reserve demand curves are introduced, and their effect on energy prices is discussed. ORDCs based on loss of load probability and value of lost load are discussed. Balancing markets are defined, and the notions of balancing service providers and balancing responsible parties are discussed in the context of the balancing model.

This chapter introduces the medium-term hydrothermal planning problem. Two-stage stochastic linear programs are introduced first, and subsequently generalized to multi-stage stochastic linear programs. Various representations of multi-stage stochastic linear programs are presented, including representations on scenario trees, representations on lattices (for Markov processes), as well as representations with stagewise independent uncertainty. These models are applied to a running example of hydrothermal planning, which is used as the basis for introducing the notion of dynamic programming value functions. The value of water is defined, and demonstrated on a hydrothermal planning problem. The chapter then proceeds to focus on the performance of stochastic programs. The wait-and-see and here-and-now value are introduced for two-stage stochastic programs. These are used to define the expected value of perfect information. The expected value solution is also defined, and used in order to introduce the value of the stochastic solution. Sampling is discussed briefly in the context of sample average approximation and importance sampling.

This chapter introduces some basic mathematical notions that are used throughout the book. Convex sets and functions, optimization problems, feasible solutions, and optimal solutions are first defined. The chapter then covers duality theory, including the definition of the Lagrangian function and the dual function, which are used to derive the duals of linear programs. Weak and strong duality are then defined and related to certain classes of optimization problems. The Karush–Kuhn–Tucker (KKT) conditions are defined, and their relation to the optimal solution of mathematical programs is discussed. KKT conditions are a fundamental concept used extensively in the book in order to understand the properties and economic interpretations of the various economic models encountered. Subgradients are subsequently defined in order to establish the relation between Lagrange multipliers and the sensitivity of an optimization model with respect to changes in the right-hand side parameters of its constraints. These sensitivity results are also used repeatedly in the book, for instance in order to derive locational marginal prices in chapter 5.