Decentralised demand response market model based on reinforcement learning

A new decentralised demand response (DR) model relying on bi-directional communications is developed in this study. In this model, each user is considered as an agent that submits its bids according to the consumption urgency and a set of parameters defined by a reinforcement learning algorithm called Q-learning. The bids are sent to a local DR market, which is responsible for communicating all bids to the wholesale market and the system operator (SO), reporting to the customers after determining the local DR market clearing price. From local markets’ viewpoint, the goal is to maximise social welfare. Four DR levels are considered to evaluate the effect of different DR portions in the cost of the electricity purchase. The outcomes are compared with the ones achieved from a centralised approach (aggregation-based model) as well as an uncontrolled method. Numerical studies prove that the proposed decentralised model remarkably drops the electricity cost compare to the uncontrolled method, being nearly as optimal as a centralised approach.© 2020 The Institution of Engineering and Technology. This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)fi=vertaisarvioitu|en=peerReviewed

A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks

In order to coordinate the economic desire of microgrid (MG) owners and the stability operation requirement of the distribution system operator (DSO), a multi-market participation framework is proposed to stimulate the energy transaction potential of MGs through distributed and centralized ways. Firstly, an MG equipped with storage can contribute to the stability improvement at special nodes of the distribution grid where the uncertain factors (such as intermittent renewable sources and electric vehicles) exist. The DSO is thus interested in encouraging specified MGs to provide voltage stability services by creating a distribution grid service market (DGSM), where the dynamic production-price auction is used to capture the competition of the distributed MGs. Moreover, an aggregator, serving as a broker and controller for MGs, is considered to participate in the day-ahead wholesale market. A Stackelberg game is modeled accordingly to solve the price and quantity package allocation between aggregator and MGs. Finally, the modified IEEE-33 bus distribution test system is used to demonstrate the applicability and effectiveness of the proposed multi-market mechanism. The results under this framework improve both MGs and utility

Review of the Proposed Reserve Markets in New England

ISO New England proposes reserve markets designed to improve the existing forward reserve market and improve pricing during real-time reserve shortages. We support all of the main elements of the proposal. For example, we agree that little is gained by allowing reserve availability bids in the day-ahead market. Doing so greatly increases the complexity of the market without the prospect of more efficient pricing. Rather, offline reserves are most efficiently priced and awarded well in advance, as is done by the improved forward reserve market.Auctions; Multiple Object Auctions; Electricity Auctions

Competitive Bidding Behavior in Uniform-Price Auction Markets

Profit-maximizing bidding in uniform price auction markets involves bidding above marginal cost. It therefore is not surprising that such behavior is observed in electricity markets. Common bidding behavior such as "hockey stick" bids easily are explained by suppliers determining their supply offers to maximize profits. This incentive to bid above marginal cost is not the result of coordinated action among the bidders. Rather, each bidder is independently selecting its bid to maximize profits based on its estimate of the residual demand curve it faces. Profit-maximizing bidding does not mean that "the sky’s the limit." Typically, bidders are limited in how high they want to bid. As prices increase, operators become increasingly concerned that their capacity will not be selected—that someone else will step in front of them in the merit order. Only when (1) demand does not respond to price, and (2) the largest unhedged block of capacity is essential to meet demand can the bidder holding this largest block profitably name any price. In all other cases, the supplier bids a price for its energy capacity to optimize its marginal tradeoff between higher prices and lower quantities. Price response from either demand or other suppliers prevents the supplier from raising its bid too much. Profit maximizing bidding should be expected and encouraged by regulators. It is precisely this profit maximizing behavior that guides the market toward long-run efficient outcomes.Auctions, Electricity Auctions, Market Design

Dynamic Pricing Problems Arising in the Adoption of Renewable Energy

There are two problems at the interface of electrical power and economics that are examined in this thesis. The first problem addresses the issue of optimally operating electric vehicle (EV) charging stations, where price as well as scheduling of purchasing, storing, and charging play key roles. The second problem addresses the challenge faced by electric power system operators who have to balance power generation and demand at all times, and are faced with the task of maximizing the social welfare of all affected entities comprised of producers, consumers and prosumers (e.g., homes with solar panels who may be producers at some times and consumers at other times). For the first problem, we have developed a layered decomposition approach that permits a holistic solution to solving the scheduling, storage and pricing problems of charging stations. The key idea is to decompose problems by time-scale. For the second problem, we have shown that for the special case of LQG agents, by careful construction of a sequence of layered VCG payments over time, the intertemporal effect of current bids on future payoffs can be decoupled, and truth-telling of dynamic states is guaranteed if system parameters are known and agents are rational. We have also shown that a modification of the VCG payments, called scaled-VCG payments, achieves Budget Balance and Individual Rationality for a range of scaling, under a certain identified Market Power Balance condition

Evaluating the Impact of Bilateral Contracts on the Offering Strategy of a Price Maker Wind Power Producer

Due to the high penetration of wind power generation in power systems and electricity markets, wind power plants (WPPs) can, in some scenarios, influence the market prices and exercise market power in the day-ahead (DA) market. In order to evaluate the capability of WPPs to directly act as price-maker, this article proposes the strategic offering of a WPP in the DA market by using a bilevel stochastic optimization approach. The primary objective of the proposed model is to maximize the WPP's expected profit by strategically offering in DA market while minimizing the energy deviations in the regulating market. Moreover, the WPP can also sign bilateral contracts with customers to supply their required energy. In the subproblem, the system operator tends to minimize the sum of the total generation costs minus the sum of the total demand benefits. The effect of bilateral contracts on the strategic offering of WPP in the DA market and its impact on the transmission margin are also investigated. Results on real cases show that when the WPP enters into a bilateral contract, it should consider the effect of such contracts on the offering strategy to the DA market. The effects of bilateral contracts on the regulating market are also examined.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets

Presents an overview and analysis of the possible approaches to bringing an active demand side into electricity markets. Part of a series of research reports that examines energy issues facing California