Electricity Markets, Regulation and Governance

Introduction

Electricity is economically distinctive because large-scale storage remains limited relative to system demand, supply and demand must be balanced continuously, power flows obey network physics, and uncontrolled shortages can propagate rapidly. Consequently, electricity cannot be governed solely as an ordinary commodity market. Competitive trading must operate within engineering constraints and under institutions responsible for reliability, consumer protection, investment adequacy and environmental objectives.

Restructured power systems commonly separate potentially competitive activities—generation, retail supply and flexibility—from natural-monopoly networks such as transmission and distribution. An independent system operator (ISO) or regional transmission organization (RTO) may coordinate dispatch and markets, while regulators oversee network tariffs, market conduct and service quality. Institutional arrangements differ among jurisdictions, but the underlying analytical questions are similar: How should scarce electrical energy be priced? How should reserves and capacity be valued? How should monopoly networks recover efficient costs? How can governance preserve reliability, fairness and investment incentives?

Learning Objectives

After studying this chapter, readers should be able to:

1. explain the economic and physical foundations of electricity markets;
2. distinguish energy, ancillary-service, capacity and financial markets;
3. formulate economic dispatch, network-constrained dispatch and reserve co-optimization;
4. interpret locational marginal prices and constraint shadow prices correctly;
5. evaluate unit-commitment nonconvexities and alternative pricing mechanisms;
6. calculate basic reliability indices and capacity accreditation;
7. derive regulated network revenue requirements and tariff rates;
8. assess market power, governance arrangements and regulatory risk; and
9. critically evaluate market reforms for low-carbon, digitalized power systems.

1. Why Electricity Markets Are Different

Electricity-market design reflects five physical and economic characteristics.

Continuous balance: At every instant, generation plus imports and storage discharge must equal demand, exports, storage charging and losses. Frequency deviations reveal short-term imbalance.

Network dependence: Power follows Kirchhoff’s laws rather than commercial contract paths. A transaction can load several transmission elements, creating congestion and externalities.

Inelastic short-run demand: Many consumers do not observe or respond immediately to wholesale prices. Scarcity can therefore produce high prices and opportunities for market power.

Nonconvex generation costs: Start-up costs, minimum stable output, minimum up/down times and discrete commitment decisions cannot be represented fully by smooth marginal-cost curves.

Reliability as a public-interest concern: An individual consumer generally cannot select a personal level of grid frequency or transmission security. Reliability therefore requires coordinated standards and procurement.

These characteristics justify a hybrid governance model: competition where feasible, regulated monopoly where necessary, and centralized technical coordination where unavoidable.

2. Industry Structure and Governance

A traditional vertically integrated utility owns generation, networks and retail supply. In a restructured model, these functions may be legally, functionally or financially separated.

Effective governance requires institutional independence, transparent rules, auditable data, reasoned decisions, appeal mechanisms and clearly allocated accountability. Formal independence alone is insufficient: regulators also require technical capability, stable funding and safeguards against political or industry capture.

2.1 Unbundling and network access

Unbundling reduces the ability of a network owner to discriminate in favor of affiliated generation or retail businesses. Third-party access rules normally specify connection procedures, congestion arrangements, tariff methodology and information disclosure. Ownership unbundling provides strong structural separation, whereas functional or accounting separation relies more heavily on monitoring and conduct rules.

2.2 Market time horizons

Figure: Coordinated electricity-market time horizons.

Long-term contracts and capacity mechanisms support investment and hedge risk. Day-ahead markets establish financially binding schedules. Intraday trading accommodates updated forecasts, while real-time markets balance deviations. Frequency-control services act over seconds to minutes. Efficient design aligns incentives across these horizons rather than treating each market independently.

3. Energy-Market Economics

3.1 Social-welfare maximization

For divisible bids in a competitive, convex market without intertemporal constraints, market clearing can be represented as:

subject to balance and operating constraints. Here, d_j is consumption by buyer j in MWh, U_j is gross benefit in currency per settlement interval, p_g is generator output in MWh, and C_g is production cost. If demand is fixed, maximizing welfare reduces to minimizing generation cost while serving that demand.

3.2 Economic dispatch and uniform pricing

For fixed demand D, lossless single-node economic dispatch is:

For generators operating strictly within their limits and differentiable convex costs, the Karush–Kuhn–Tucker conditions give:

The multiplier λ is the marginal cost of supplying one additional MWh. Under uniform marginal pricing, accepted suppliers receive the clearing price rather than their individual offers. This rewards low-cost production and supports recovery of fixed costs through inframarginal rents, although market power and nonconvexities complicate this interpretation.

Worked Example 1: Merit-order dispatch

Three generators submit constant offers:

For a one-hour demand of 100 MWh, dispatch is 50 MWh from G1, 40 MWh from G2 and 10 MWh from G3. The marginal price is $60/MWh. Total energy payment is 100 × 60 = $6,000. Offered production cost is:

The difference between market payment and offered variable cost is not automatically excess profit: it may contribute to start-up, fixed, financing and risk costs. Persistent margins caused by withholding rather than scarcity or efficiency warrant market-power investigation.

3.3 Scarcity pricing and demand response

When available supply approaches the reliability limit, the marginal value of energy may exceed the variable cost of the most expensive generator. Administrative scarcity pricing or an operating-reserve demand curve can reflect the expected reliability cost of further reserve depletion.

A conceptual upper benchmark is the value of lost load (VOLL), measured in $/MWh of unserved energy. VOLL is heterogeneous across customers and outage durations; therefore, a single system-wide estimate is an approximation. Price caps limit financial exposure and market power but, if set too low, can suppress efficient scarcity signals—the “missing-money” problem.

Price-responsive demand can reduce this problem. If customers can curtail when price exceeds their marginal benefit, scarcity is managed through voluntary response rather than involuntary load shedding.

4. Network-Constrained Dispatch and Locational Pricing

4.1 DC power-flow approximation and units

Under near-unity voltage magnitudes, small angle differences, negligible resistance and balanced steady-state operation, real-power flow on line ℓ connecting buses i and j is approximated by either of two unit-consistent forms:

or, when susceptance b_ℓ is expressed in per unit,

Here, θ_i and θ_j are voltage angles in radians, and S_base is the three-phase system power base in MW. Without multiplication by S_base, the second expression gives per-unit power, not MW. Sign depends on the selected line orientation.

The approximation is useful for market clearing but does not replace AC security analysis, which must consider reactive power, voltage limits and nonlinear losses.

4.2 Locational marginal prices

Let net nodal injection be x_i = p_i − d_i, and let H_ℓi be a power-transfer distribution factor for a specified reference bus. A lossless DC dispatch includes:

where F_ℓ is the line limit in MW. With the Lagrangian convention using the balance constraint ∑_i(d_i−p_i)=0, the nodal marginal price is:

Here, λ is the system energy multiplier and μ_ℓ^+, μ_ℓ^- are nonnegative multipliers on positive- and negative-direction line limits. Other sign conventions produce algebraically different-looking but economically equivalent expressions.

An LMP is the derivative of minimized operating cost with respect to an incremental MW of demand at a location, under the model’s assumptions. With marginal-loss modeling, an additional loss component appears.

4.3 Correct interpretation of a shadow price

Suppose a binding upper line constraint is f_ℓ ≤ F_ℓ with multiplier μ_ℓ^+ > 0. For a regular convex cost-minimization problem:

Thus, marginally relaxing the binding limit decreases—not increases—the optimized operating cost by approximately μ_ℓ^+ currency units per additional MW of limit. Tightening it has the opposite effect. This local interpretation applies while the active constraint set remains unchanged.

Congestion rents arise from nodal price differences. Financial transmission rights can hedge eligible congestion exposure, but their issuance must satisfy simultaneous-feasibility rules so that promised payouts are supportable by congestion revenues.

5. Ancillary Services and Reserve Co-optimization

Energy-only dispatch can be inefficient if reserve is procured separately because reserving headroom on a low-cost generator may require more expensive energy from another unit. Co-optimization selects energy and reserves simultaneously.

A simplified one-period formulation is:

subject to:

Here, r_g is reserve MW, R is the system requirement, O_g^R is the reserve-offer cost, u_g is commitment status, Ramp_g is the deliverable ramp rate in MW/min, and τ is the required response time in minutes. Additional constraints distinguish regulation, spinning, nonspinning and replacement reserves and verify zonal deliverability.

The reserve price is associated with the marginal cost of tightening the reserve requirement. It can include direct reserve-offer cost and opportunity cost: a resource withholding 1 MW from energy to provide reserve may forgo energy-market margin. Energy and reserve prices must therefore be interpreted jointly.

Security-constrained formulations represent credible contingencies. Deterministic N−1 criteria require the system to remain secure after any specified single contingency. Probabilistic procurement can additionally account for outage probabilities, forecast uncertainty and the consequences of shortage.

6. Unit Commitment, Nonconvexity and Pricing

Unit commitment determines which generators are online over multiple periods. A standard mixed-integer model includes binary commitment u_g,t, start-up y_g,t and shutdown z_g,t variables:

The objective includes variable, no-load, start-up and shutdown costs:

It is subject to balance, network, reserve, ramp-rate, minimum-output, minimum-up-time and minimum-down-time constraints. Binary decisions make the feasible set nonconvex. Consequently, a marginal energy price may not cover the as-bid cost of a committed unit.

6.1 Pricing approaches

Make-whole or uplift payment: Compensates an eligible resource when market revenues are below accepted operating costs. Uplift supports cost recovery but can weaken transparency and create incentives to alter offers.

Convex-hull pricing: Uses prices derived from a convex relaxation designed to minimize aggregate uplift under defined conditions. It can improve price signals but is computationally and institutionally complex.

Integer or extended LMP methods: Incorporate selected commitment effects into prices. Their design requires explicit rules because discrete costs do not have a unique marginal allocation.

Multi-part bids and side payments: Preserve detailed technical offers while settling energy at marginal prices and nonconvex costs separately.

No pricing method completely eliminates the tension between short-run dispatch efficiency, transparent prices, truthful bidding and fixed-cost recovery. Market governance must specify cost verification, uplift allocation and mitigation rules.

7. Resource Adequacy and Capacity Accreditation

Energy and operating-reserve markets address operational scarcity. Resource adequacy concerns whether sufficient deliverable capability will exist over longer horizons. Jurisdictions use capacity markets, strategic reserves, reliability options, bilateral obligations or energy-only designs with scarcity pricing.

7.1 Reliability measures

For period t, loss-of-load probability is:

where A_t is available capacity and D_t is demand. Loss-of-load expectation over T periods is:

LOLE is measured in expected shortage periods, commonly hours/year or days/year. Expected unserved energy is:

where ∆t is period duration. LOLE measures frequency or duration expectation, whereas EUE measures expected magnitude of unserved energy.

Worked Example 2: Correct reliability calculation

Two independent 50 MW generators each have availability 0.9 during a period. Demand is 75 MW. Both units must be available to provide 100 MW; if either unit is unavailable, available capacity is at most 50 MW and loss of load occurs.

If the same conditions apply in each of 100 periods:

Independence between the two generators within a period is required for multiplying their availabilities. Independence across time is not required to calculate the expected LOLE as a sum of period probabilities, although it matters for outage-duration distributions.

7.2 Capacity accreditation

Nameplate capacity is not equivalent to dependable capacity. Effective load-carrying capability (ELCC) measures the additional load that can be served after adding a resource while maintaining the original reliability criterion:

The starred demands are the maximum loads satisfying the same reliability target before and after addition. An accreditation ratio may be reported as:

For example, a 200 MW battery with an assessed ELCC of 140 MW has a 70% accreditation ratio. ELCC depends on duration, charging opportunity, outage behavior, demand shape, transmission deliverability and the existing resource portfolio. It is not an immutable technology constant. Marginal ELCC generally declines as similar weather-dependent resources become more prevalent because their output is correlated.

Capacity mechanisms must also control performance risk. Availability penalties, seasonal accreditation, testing and pay-for-performance provisions reduce the possibility that nominal capacity is unavailable during scarcity.

8. Regulation of Transmission and Distribution Networks

Networks exhibit economies of scale and scope; duplicating them is often inefficient. Economic regulation seeks to permit efficient cost recovery while preventing monopoly pricing and encouraging service quality.

8.1 Building-block revenue requirement

A simplified annual allowed-revenue equation is:

Here, ARR_t is allowed revenue, OPEX_t is efficient operating expenditure, DEP_t is regulatory depreciation, RAB_t is the regulatory asset base, r_t is the allowed weighted-average cost of capital, TAX_t is allowed tax, and OR_t is other regulated revenue. All quantities must use a consistent nominal/real and pre-tax/post-tax basis.

The nominal post-tax weighted-average cost of capital is commonly estimated as:

where E and D are market-value equity and debt, r_e is required equity return, r_d is debt cost, and T_c is the corporate tax rate. Regulatory applications may instead use real or pre-tax variants; mixing variants would double-count or omit inflation and tax.

Worked Example 3: Allowed revenue and tariff

Suppose a distributor has a $500 million regulatory asset base, allowed return of 8%, depreciation of $25 million, efficient operating expenditure of $60 million, allowed tax of $10 million and other revenue of $5 million:

If the entire revenue were recovered through 5,000 GWh of annual delivered energy, the illustrative volumetric tariff would be:

Actual tariffs generally divide revenue among customer classes and fixed, demand, capacity and volumetric charges using cost-allocation rules. A purely volumetric tariff can become unstable when distributed generation reduces metered energy without proportionally reducing network costs.

8.2 Price-cap and revenue-cap regulation

A simplified price-cap update is:

where π_t is inflation, X_t is the productivity factor, and Z_t represents permitted pass-through adjustments in compatible price units. Revenue caps apply an analogous adjustment to allowed revenue and can reduce volume risk.

Incentive regulation gives the utility temporary benefit from outperforming an efficiency benchmark. Poor calibration can, however, encourage underinvestment, quality deterioration or strategic cost classification. Service-quality incentives and engineering standards should therefore accompany cost incentives.

8.3 Tariff design principles

Efficient tariffs balance several objectives:

• cost causation: customers should face charges related to the costs they impose;
• revenue adequacy: expected revenue should recover efficient allowed costs;
• economic efficiency: marginal prices should signal losses, congestion and capacity costs;
• equity and affordability: vulnerable consumers require transparent policy support;
• stability and simplicity: bills should be understandable and not excessively volatile;
• technology neutrality: comparable services should face comparable rules.

Time-of-use rates use predetermined periods, while real-time pricing follows short-run wholesale conditions more closely. Demand charges can reflect local capacity requirements but may not align with coincident system peaks. Connection charges, deep or shallow network-upgrade charges, and locational tariffs materially affect investment decisions.

9. Market Power, Risk and Consumer Protection

9.1 Structural and behavioral market power

A generator has market power if it can profitably alter price or market outcomes from competitive levels. Physical withholding removes capacity; economic withholding offers it at inflated prices. A supplier may become pivotal when demand cannot be met without its capacity.

A common concentration measure is the Herfindahl–Hirschman Index:

where s_i is firm i’s percentage market share. If four equal firms each have 25%, HHI = 4(25²)=2,500. HHI is only a screening measure. Transmission constraints, contract positions, ramp capability and pivotal-supplier status can be more informative than system-wide concentration.

Mitigation tools include offer caps, cost-based reference levels, must-offer obligations, structural divestiture, virtual bidding, demand participation and ex post enforcement. Over-mitigation can suppress legitimate scarcity signals, so rules should distinguish market power from high prices caused by genuine scarcity.

9.2 Financial risk and hedging

Spot prices are volatile. Bilateral fixed-price contracts, futures, swaps, contracts for differences, options and financial transmission rights transfer price risk. Hedging does not eliminate underlying physical risk; it reallocates financial exposure and introduces counterparty, collateral and liquidity risks.

Retail consumer protection includes clear bills, switching rules, supplier-of-last-resort arrangements, data privacy, disconnection safeguards and truthful environmental claims. Cross-subsidies should be explicit because hidden subsidies can distort consumption and investment.

10. Applied Case: Designing a Low-Carbon Market for Asteria

This is an illustrative fictional case.

Background

Asteria operates a 6 GW peak system divided into three transmission zones. Wind supplies 30% of annual energy, but congestion frequently separates the northern wind zone from the southern load center. The existing gross-pool market uses one national price, procures reserves after energy dispatch and credits all resources at nameplate capacity.

Problem

The arrangement produces four weaknesses:

1. the national price conceals locational congestion;
2. sequential reserve procurement causes redispatch and avoidable cost;
3. nameplate accreditation overstates variable-resource adequacy;
4. distribution tariffs depend mainly on energy volume, although network peak costs are rising.

A dominant generator in the southern zone is also pivotal during major transmission outages.

Analysis and approach

The reform authority proposes:

Nodal day-ahead and real-time pricing. Security-constrained dispatch calculates LMPs using unit and network constraints. Financial transmission rights are allocated subject to simultaneous feasibility.

Energy-reserve co-optimization. Regulation, ten-minute spinning reserve and replacement reserve are jointly procured. Resource qualification reflects ramp rate, telemetry and zonal deliverability.

Reliability-based capacity accreditation. A proposed 200 MW four-hour battery receives an initial 70% accreditation, or 140 MW. A 300 MW solar project receives 20%, or 60 MW. Under the study assumptions their accredited contributions total 200 MW. Because portfolio ELCC is nonadditive in general, the system operator must repeat probabilistic studies as penetration and dependence change.

Performance-linked capacity obligation. Suppliers must procure accredited capacity, while resources face penalties for nonperformance during declared scarcity intervals.

Network tariff reform. Allowed revenue remains based on efficient building blocks, but recovery shifts toward a combination of fixed customer charges, coincident-peak demand charges and time-varying volumetric rates. Targeted public funding, rather than hidden tariff distortions, supports low-income consumers.

Market-power controls. The monitor applies pivotal-supplier tests in constrained zones. Offers from pivotal resources may be mitigated to verified reference levels, while genuine scarcity pricing remains available when competitive resources are exhausted.

Expected outcome

The reform should improve the visibility of congestion, coordinate energy and reserve opportunity costs, and align capacity payments with reliability contribution. It will not remove all difficulties: nodal-price volatility may face political resistance, battery accreditation will evolve, and local market-power mitigation must avoid suppressing investment signals.

Learning points

Market design is an integrated engineering-economic problem. Energy pricing, reserve procurement, capacity accreditation, transmission rights and retail tariffs cannot be optimized independently. Governance quality—transparent models, stakeholder consultation, independent monitoring and periodic review—is as important as the mathematical design.

11. Contemporary Developments

11.1 Distributed energy and flexibility

Distributed solar, batteries, electric vehicles and controllable demand increasingly participate through aggregators or virtual power plants. Regulation must define metering, baseline calculation, dispatch responsibility and coordination between transmission and distribution operators. Double compensation should be prevented where the same service is paid in multiple markets without delivering distinct value.

11.2 Artificial intelligence and digital markets

AI supports load and renewable forecasting, outage prediction, anomaly detection, bidding assistance and accelerated security assessment. Its use introduces model-risk and governance requirements: traceable training data, cybersecurity, performance monitoring, human override and auditability. Algorithms that autonomously learn bidding strategies may facilitate tacit coordination even without explicit communication; competition oversight must therefore consider algorithmic behavior.

11.3 Decarbonization and investment contracts

Carbon pricing internalizes emissions externalities when coverage and enforcement are credible. Renewable auctions, feed-in premiums and contracts for differences can reduce financing costs but may shift volume, basis and curtailment risk to consumers or governments. Long-term clean-energy contracts should preserve incentives to locate and operate resources where they provide system value.

11.4 Resilience and climate risk

Traditional adequacy analysis may underrepresent correlated extreme weather, fuel-supply disruption and common-mode infrastructure failure. Stress testing, scenario analysis, weather-dependent equipment ratings and interdependent gas-electric modeling are increasingly important. Resilience involves preparation, absorption, recovery and adaptation, not merely additional generation capacity.

12. Design Challenges and Best Practices

No market design perfectly reconciles affordability, reliability, sustainability and investment certainty. Models simplify physical behavior; regulatory forecasts are uncertain; policy interventions can alter prices and investor expectations. Jurisdictions also differ in network topology, resource mix, legal authority and social priorities.

Sound practice includes:

1. defining reliability and policy objectives before selecting instruments;
2. co-optimizing technically substitutable products where practical;
3. preserving unit consistency and publishing model assumptions;
4. using probabilistic, portfolio-sensitive capacity accreditation;
5. aligning real-time, day-ahead and long-term incentives;
6. separating competitive scarcity pricing from abuse of market power;
7. linking network incentives to cost, quality and resilience;
8. protecting consumers through transparent, targeted measures;
9. auditing settlement, algorithms and market data; and
10. reviewing rules periodically as technology and system conditions change.

Chapter Summary

Electricity markets coordinate decentralized commercial decisions within a tightly constrained physical system. Energy-market prices arise from marginal dispatch, while network congestion creates locational differences. A binding constraint’s shadow price measures the marginal cost reduction available from relaxing that constraint. Reserve co-optimization captures direct procurement and energy opportunity costs, whereas unit-commitment nonconvexities may require uplift or alternative pricing methods.

Resource adequacy requires probabilistic reliability analysis and capacity accreditation based on dependable contribution rather than nameplate rating. Monopoly networks are regulated through building-block revenue requirements, incentive mechanisms and tariffs designed to balance cost recovery, efficiency and equity. Market-power monitoring, risk management, consumer protection and institutional independence are essential governance functions. Decarbonization, distributed resources, climate risk and AI make coordinated, transparent and adaptive market governance increasingly important.

Key Terms

Ancillary services: Services supporting frequency, voltage, balancing and system security.

Capacity accreditation: The dependable capacity value assigned to a resource for adequacy purposes.

Convex-hull pricing: Pricing based on a convexified commitment problem, often intended to reduce uplift.

Economic dispatch: Allocation of generation to meet demand at minimum operating cost subject to constraints.

Effective load-carrying capability: Additional load supportable after adding a resource while preserving a reliability criterion.

Expected unserved energy: Expected quantity of demand not supplied over a specified period.

Financial transmission right: Financial instrument that hedges specified congestion-price differences.

Herfindahl–Hirschman Index: Sum of squared market shares used to screen market concentration.

Locational marginal price: Marginal cost of serving an additional unit of demand at a network location.

Loss-of-load expectation: Expected number or duration of periods in which available supply is insufficient.

Market power: Ability to profitably influence prices or market outcomes away from competitive levels.

Regulatory asset base: Recognized asset value on which a regulated utility may earn an allowed return.

Reserve co-optimization: Simultaneous procurement of energy and operating reserves.

Revenue requirement: Regulator-approved revenue needed to recover efficient costs and allowed return.

Scarcity pricing: Pricing that reflects the reliability value of limited energy or reserves.

Shadow price: Marginal change in optimized objective value associated with relaxing or tightening a constraint.

Unit commitment: Scheduling of generator start-up, operation and shutdown decisions over time.

Uplift payment: Additional payment used to recover eligible accepted costs not covered by market revenues.

Value of lost load: Estimated economic value consumers place on avoiding unserved electricity.

Review Questions

Short Answer Questions

1. Why does electricity require centralized real-time coordination?
2. Distinguish an energy market from a capacity mechanism.
3. What does a locational marginal price represent?
4. Why can reserve provision have an opportunity cost?
5. What is the purpose of a regulatory asset base?

Long Answer Questions

1. Explain how physical network constraints affect dispatch, prices and congestion rents.
2. Compare uplift payments, convex-hull pricing and marginal energy pricing for nonconvex generation costs.
3. Evaluate the advantages and risks of price-cap and revenue-cap network regulation.
4. Discuss how market monitoring can control market power without suppressing legitimate scarcity prices.
5. Explain how decarbonization and distributed energy resources challenge traditional electricity-market governance.

Analytical / Application Questions

1. Formulate a security-constrained co-optimization model for energy and two reserve products, identifying objective terms, coupling constraints and relevant shadow prices.
2. A regulator must redesign a distribution tariff for a system with falling delivered energy but rising coincident peak demand. Develop and justify an appropriate tariff structure.
3. Design a reliability-based accreditation framework for a portfolio containing wind, solar, batteries and demand response, explaining how dependence and transmission deliverability should be represented.

Multiple Choice Questions with Answers

Question 1

In a competitive convex single-node dispatch with no binding generator limits, what condition characterizes dispatched generators?

A. All generators have equal average cost

B. All generators have equal marginal cost

C. All generators receive their offered price

D. All generators operate at maximum output

Correct Answer: B. All generators have equal marginal cost

Question 2

A binding transmission upper limit has a shadow price of $15/MW in a regular cost-minimization model. What is the approximate local effect of increasing the limit by 1 MW?

A. Optimized cost decreases by $15

B. Optimized cost increases by $15

C. Optimized cost is unchanged

D. Market demand decreases by 15 MW

Correct Answer: A. Optimized cost decreases by $15

Question 3

If line susceptance is expressed in per unit and voltage angles are in radians, which expression gives DC line flow in MW?

A. f_ℓ=b_ℓ(θ_i−θ_j) without any power base

B. f_ℓ=S_baseb_ℓ(θ_i−θ_j)

C. f_ℓ=(θ_i−θ_j)/(S_baseb_ℓ)

D. f_ℓ=S_base/(θ_i−θ_j)

Correct Answer: B. f_ℓ=S_baseb_ℓ(θ_i−θ_j)

Question 4

Why can reserve provided by a low-cost generator have an opportunity cost?

A. Reserve always increases the generator's fuel efficiency

B. Holding headroom for reserve can displace profitable energy production

C. Reserve eliminates all start-up costs

D. Reserve makes transmission constraints irrelevant

Correct Answer: B. Holding headroom for reserve can displace profitable energy production

Question 5

Two independent 50 MW generators each have availability 0.9, and demand is 75 MW. When does loss of load occur?

A. Only when both generators are unavailable

B. When at least one generator is unavailable

C. Only when both generators are available

D. Loss of load cannot occur

Correct Answer: B. When at least one generator is unavailable

Question 6

For the two-generator system in the previous question, what is the LOLE over 100 identical periods?

A. 1 expected period

B. 10 expected periods

C. 19 expected periods

D. 81 expected periods

Correct Answer: C. 19 expected periods

Question 7

A network has OPEX of $60 million, depreciation of $25 million, a $500 million asset base earning 8%, tax allowance of $10 million and other revenue of $5 million. What is its annual allowed revenue?

A. $90 million

B. $120 million

C. $130 million

D. $140 million

Correct Answer: C. $130 million

Question 8

A 200 MW battery has an ELCC of 140 MW. What is its capacity accreditation ratio?

A. 30%

B. 60%

C. 70%

D. 140%

Correct Answer: C. 70%

Question 9

Four firms each hold 25% of a market. Using percentage market shares, what is the HHI?

A. 625

B. 1,000

C. 2,500

D. 10,000

Correct Answer: C. 2,500

Question 10

Why may a committed generator require an uplift payment?

A. Marginal energy revenue may not recover its accepted start-up and other nonconvex costs

B. Uplift is required whenever transmission losses are zero

C. Uniform pricing always pays less than variable cost

D. Uplift replaces all energy-market revenue

Correct Answer: A. Marginal energy revenue may not recover its accepted start-up and other nonconvex costs