Dynamic Analysis of Operating Reserve Demand Curve in Energy-Only Electricity Markets

2019 ◽  
Author(s):  
Sreelatha Aihloor Subramanyam ◽  
Xuewei Zhang ◽  
Jinjie Wu ◽  
Huihui Song
Keyword(s):  
Dynamic Analysis ◽  
Electricity Markets ◽  
Demand Curve ◽  
Reserve Demand

scholarly journals Don't Mess With Texas Solar

2021 ◽  
Vol 7 (3) ◽  
pp. 487-494
Author(s):  
Matthew A. Arth
Keyword(s):  
Demand Curve ◽  
Electric Power Industry ◽  
High Growth ◽  
High Growth Rate ◽  
Public Utility ◽  
Generating Capacity ◽  
Generation Capacity ◽  
Reserve Demand ◽  
Installed Capacity ◽  
Solar Generation

2020 was the year of the unexpected, but one constant in the energy industry remained the exponential growth of solar generation in Texas, which largely continued its expansion as predicted. Electric Reliability Council of Texas’s (“ERCOT”) 2019 State of the Grid Report noted that installed solar generation capacity in ERCOT stood at 2,281 megawatts (MW) at year-end 2019, with over 67,000 MW of further solar capacity under study, exceeding even the amount of wind generation capacity under study. By July 2020, installed capacity of solar generation increased by almost 1 gigawatt (GW) to a total of 3,275 MW, representing approximately 2.2% of generating capacity in ERCOT. Solar accounted for 43% of new installed capacity in 2020, the largest share among generation types. The Solar Energy Industries Association (“SEIA”) ranked Texas fifth among the states in installed solar generation capacity in 2019, but based on its high growth rate, Texas is projected to be second only to California within the next five years. Abundant land and consistent sun make Texas an obvious candidate for significant solar generation investment, but ERCOT’s energy-only market makes solar generation with its nonexistent fuel costs especially competitive. Adjustments to the Operating Reserve Demand Curve in 2019 by the Public Utility Commission of Texas have also increased scarcity pricing and made returns more lucrative for a resource that is at its apex when demand is highest on hot, sunny summer afternoons. As this Article was being finalized for publication, the ramifications to the electric power industry in Texas of Winter Storm Uri are not yet clear. However, a preliminary assessment by Pecan Street highlighted the benefits of solar generation in a such a crisis and may spur further interest both at the generation side and behind-the-meter.

scholarly journals Quasi-Stochastic Electricity Markets

2021 ◽  
Author(s):  
Jacob Mays
Keyword(s):  
Convex Hull ◽  
Electricity Markets ◽  
Real World ◽  
Theoretical Basis ◽  
Price Formation ◽  
Demand Curves ◽  
World Markets ◽  
Reserve Demand ◽  
Wholesale Electricity Markets

Summary of Contribution This article was inspired by price formation changes recently proposed and implemented in several U.S. wholesale electricity markets. The analysis draws from and contributes to three lines of literature. First, the paper specifies two mechanisms that lead to inefficient and inconsistent prices in real-world markets. Second, the article illustrates the importance of considering uncertainty in evaluating policies for pricing in nonconvex markets and observes that convex hull pricing, sometimes described as an ?ideal? due to its uplift-minimizing property in deterministic analyses, can perform poorly in settings with uncertainty. Lastly, the paper strengthens the theoretical basis for operating reserve demand curves by connecting their parameterization to outcomes expected in efficient stochastic markets.

scholarly journals Ranking Supply Function and Cournot Equilibria in a Differentiated Product Duopoly with Demand Uncertainty

Games ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 60 ◽  
Author(s):  
Ismail Saglam
Keyword(s):  
Electricity Markets ◽  
Demand Uncertainty ◽  
Critical Level ◽  
Demand Curve ◽  
Consumer Surplus ◽  
Supply Function ◽  
Product Substitution ◽  
Quantity Competition ◽  
Demand Fluctuations ◽  
Supply Function Competition

In this paper, we provide a welfare ranking for the equilibria of the supply function and quantity competitions in a differentiated product duopoly with demand uncertainty. We prove that the expected consumer surplus is always higher under the supply function competition, irrespective of whether the (duopolistic) products are substitutes, complements, or independent. Numerical simulations suggest that if the products are either complements or independent, or if they have an extremely low degree of substitution, then the supply function competition can always be Pareto superior to the quantity competition in terms of the producers’ and consumers’ welfares. Moreover, if the degree of product substitution is not extremely low, then the supply function competition can be Pareto superior to the quantity competition if and only if the size of the demand uncertainty is sufficiently large to exceed a critical level. We find that this critical level of demand uncertainty becomes higher when the duopolistic products are less differentiated. Additionally, this critical level is nonincreasing both in the marginal cost of producing a unit output and in the own-price sensitivity of each inverse demand curve when all other parameters are fixed. Our results imply that in electricity markets with differentiated products, the regulators should not intervene to impose the quantity competition in favor of the supply function competition unless the degree of product substitution is sufficiently high and the predicted demand fluctuations are sufficiently small.

scholarly journals The Uncertain Bidder Pays Principle and Its Implementation in a Simple Integrated Portfolio-Bidding Energy-Reserve Market Model

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2957 ◽  
Author(s):  
Dávid Csercsik ◽  
Ádám Sleisz ◽  
Péter Márk Sőrés
Keyword(s):  
Electricity Markets ◽  
Energy Reserve ◽  
Market Model ◽  
Computationally Efficient ◽  
Demand And Supply ◽  
System Operator ◽  
Reserve Demand ◽  
Reserve Market ◽  
Portfolio Shifts

One reason for the allocation of reserves in electricity markets is the uncertainty of demand and supply. If the bias of the generation portfolio shifts from controllable generators to renewable sources with significantly higher uncertainty, it is natural to assume that more reserve has to be allocated. The price of reserve allocation in European models is dominantly paid by the independent system operator in the form of long-term paid reserve capacities and reserve demand bids submitted to various reserve markets. However, if we consider a scenario where the significant part of generation is allocated in day-ahead auctions, the power mix is not known in advance, so the required reserves can not be efficiently curtailed for the ratio of renewables. In the current paper we analyze an integrated European-type, portfolio-bidding energy-reserve market model, which aims to (at least partially) put the burden of reserve allocation costs to the uncertain energy bidders who are partially responsible for the amount of reserves needed. The proposed method in addition proposes a more dynamic and adaptive reserve curtailment method compared to the current practice, while it is formulated in a computationally efficient way.

scholarly journals Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1261
Author(s):  
Neda Hajibandeh ◽  
Miadreza Shafie-khah ◽  
Sobhan Badakhshan ◽  
Jamshid Aghaei ◽  
Sílvio Mariano ◽  
...  
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Demand Response ◽  
Electricity Markets ◽  
Demand Curve ◽  
Mixed Integer ◽  
Programming Approach ◽  
Elastic Demand ◽  
Multi Objective ◽  
System Operator

Demand response (DR) is known as a key solution in modern power systems and electricity markets for mitigating wind power uncertainties. However, effective incorporation of DR into power system operation scheduling needs knowledge of the price–elastic demand curve that relies on several factors such as estimation of a customer’s elasticity as well as their participation level in DR programs. To overcome this challenge, this paper proposes a novel autonomous DR scheme without prediction of the price–elastic demand curve so that the DR providers apply their selected load profiles ranked in the high priority to the independent system operator (ISO). The energy and reserve markets clearing procedures have been run by using a multi-objective decision-making framework. In fact, its objective function includes the operation cost and the customer’s disutility based on the final individual load profile for each DR provider. A two-stage stochastic model is implemented to solve this scheduling problem, which is a mixed-integer linear programming approach. The presented approach is tested on a modified IEEE 24-bus system. The performance of the proposed model is successfully evaluated from economic, technical and wind power integration aspects from the ISO viewpoint.

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