Multi-Period Resilient Model for VSC-Based AC-DC HDS Considering Public-Safety Power Shutoff to Mitigate Wildfires

This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.

Cutting the Cake of the Emission Cap in the Peer-to-peer Multi-energy Sharing Market

With the development of communication technology and distributed energy resources,trading of carbon emission rights and peer-to-peer energy transactions have become popular research directions on the end-user side.Therefore,a cap-andtrade emission framework with peer-to-peer energy trading is employed in this paper.The emission cap decomposition problem is solved under the circumstances of a multi-energy peer-topeer energy trading market.First,the multi-energy system is introduced in the peer-to-peer energy sharing model.The interaction between the prosumers and the system operator is defined.Then,the total emission cap,set by the operator,is modeled as a constraint.The decomposition of the emission cap is modeled as a cake-cutting game.Finally,the existence and uniqueness of the cake-cutting solution is proven by modeling the game to an equivalent monotone variational inequality problem.The complementary characteristics of multi energy in the market can ensure the utility of prosumers while reducing the total cap.

Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Demand Response(DR)provides both operational and financial benefits to a variety of stakeholders in the power system.For example,in the deregulated market operated by the Electric Reliability Council of Texas(ERCOT),load serving entities(LSEs)usually purchase electricity from the wholesale market(either in day-ahead or real-time market)and sign fixed retail price contracts with their end-consumers.Therefore,incentivizing end-consumers’load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market.As the first-of-its-kind implementation of Coupon Incentive-based Demand Response(CIDR),the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements,individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets,as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts.A number of methodologies are developed for this special type of DR program including price/baseline prediction,individualized target setting and a lottery mechanism.This paper summarizes the methodologies,design,critical findings,as well as the potential generalization of such an experiment.Comparison of the EnergyCoupon with a conventional Time-of-Use(TOU)price-based DR program is also conducted.Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries,the effective cost for demand response providers in EnergyCoupon can be substantially reduced,while achieving a similar level of demand reduction as conventional DR programs.