Charge Scheduling of an Energy Storage System under Time-of-use Pricing and a Demand Charge

A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS, and by 8% compared to a scheduling algorithm based on net power.Comment: 13 pages, 2 figures, 5 table

Decentralized Demand Side Management with Rooftop PV in Residential Distribution Network

In the past extensive researches have been conducted on demand side management (DSM) program which aims at reducing peak loads and saving electricity cost. In this paper, we propose a framework to study decentralized household demand side management in a residential distribution network which consists of multiple smart homes with schedulable electrical appliances and some rooftop photovoltaic generation units. Each smart home makes individual appliance scheduling to optimize the electric energy cost according to the day-ahead forecast of electricity prices and its willingness for convenience sacrifice. Using the developed simulation model, we examine the performance of decentralized household DSM and study their impacts on the distribution network operation and renewable integration, in terms of utilization efficiency of rooftop PV generation, overall voltage deviation, real power loss, and possible reverse power flows.Comment: 5 pages, 7 figures, ISGT 2018 conferenc

Cooperative energy management for a cluster of households prosumers

© 2016 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 worksThe increment of electrical and electronic appliances for improving the lifestyle of residential consumers had led to a larger demand of energy. In order to supply their energy requirements, the consumers have changed the paradigm by integrating renewable energy sources to their power grid. Therefore, consumers become prosumers in which they internally generate and consume energy looking for an autonomous operation. This paper proposes an energy management system for coordinating the operation of distributed household prosumers. It was found that better performance is achieved when cooperative operation with other prosumers in a neighborhood environment is achieved. Simulation and experimental results validate the proposed strategy by comparing the performance of islanded prosumers with the operation in cooperative modePeer ReviewedPostprint (author's final draft

An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers

In energy systems with high shares of weather-driven renewable power sources, gas-fired power plants can serve as a back-up technology to ensure security of supply and provide short-term flexibility. Therefore, a tighter coordination between electricity and natural gas networks is foreseen. In this work, we examine different levels of coordination in terms of system integration and time coupling of trading floors. We propose an integrated operational model for electricity and natural gas systems under uncertain power supply by applying two-stage stochastic programming. This formulation co-optimizes day-ahead and real-time dispatch of both energy systems and aims at minimizing the total expected cost. Additionally, two deterministic models, one of an integrated energy system and one that treats the two systems independently, are presented. We utilize a formulation that considers the linepack of the natural gas system, while it results in a tractable mixed-integer linear programming (MILP) model. Our analysis demonstrates the effectiveness of the proposed model in accommodating high shares of renewables and the importance of proper natural gas system modeling in short-term operations to reveal valuable flexibility of the natural gas system. Moreover, we identify the coordination parameters between the two markets and show their impact on the system's operation and dispatch

Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively