In this paper, the extent to which the integration of rooftop photovoltaic (PV) power with a community energy storage (CES) system can reduce energy cost and distribution network (DN) loss is explored. To this end, three energy trading systems (ETSs) are compared; first, an ETS where PV users exchange energy with the CES system in addition to the grid, second, an ETS where PV users merely exchange energy with the CES system, and third, an ETS where PV users only exchange energy with the grid. A multi-objective optimization framework, combined with a linear distribution network power flow model, is developed to study the trade-off between the energy cost and network power loss reductions while satisfying the DN voltage and current flow limits. Simulations, with real energy demand and PV power data, highlight that enabling the energy exchange between the users and the CES system can give a better trade-off between the DN power loss and energy cost reductions. Further, simulations demonstrate that all three ETSs deliver nearly 85% DN energy loss reduction with significantly increased revenues compared to an ETS without a CES system.
Heating, Ventilation, and Air Conditioning (HVAC) energy consumption accounts for a significant part of the total energy consumption of buildings and households. The ubiquitous adoption of distributed renewable energy and smart meters helps to decarbonize the HVAC energy consumption and improve energy efficiency. However, how to scale up HVAC energy management for a group of users while persevering users' privacy remains a big challenge. In this work, we utilize the concept of transactive energy to build a cooperative energy management system for independent HVAC units in a distributed manner.…
In smart grids, distributed energy resources (DERs) have penetrated residential zones to provide a new form of electricity supply, mainly from renewable energy. Residential households and commercial buildings with DERs have become prosumers in the local grids, since they can sell surplus power to others. Researches have been initiated to integrate and utilize DERs through better control and communication strategies. With the advances in the Internet of Things (IoT) technology, unprecedented coordination among DERs can be achieved to facilitate energy trading and transactive energy management. …
This paper studies the feasibility of integrating a community energy storage (CES) system with rooftop photovoltaic (PV) power generation for demand-side management of a neighbourhood while maintaining the distribution network voltages within allowed limits. To this end, we develop a decentralized energy trading system between a CES provider and users with rooftop PV systems. By leveraging a linearized branch flow model for radial distribution networks, a voltage-constrained leader-follower Stackelberg game is developed wherein the CES provider maximizes revenue and the users minimize their pe…
Future power grids will entail large fleets of storage devices capable of scheduling their charging/discharging profiles so as to achieve lower peak demand and reduce energy bills, by shifting absorption times in sync with the availability of renewable energy sources. Optimal management of such fleets entails large scale optimisation problems which are better dealt with in a hierarchical manner, by clustering together individual devices into fleets. Leveraging on recent results characterizing the set of aggregate demand profiles of a heterogeneous fleet of charging (or, respectively, dischargi…
Hydro storage system optimization is becoming one of the most challenging tasks in Energy Finance. While currently the state-of-the-art of the commercial software in the industry implements mainly linear models, we would like to introduce risk aversion and a generic utility function. At the same time, we aim to develop and implement a computational efficient algorithm, which is not affected by the curse of dimensionality and does not utilize subjective heuristics to prevent it. For the short term power market we propose a simultaneous solution for both dispatch and bidding problems. Following …
The increased market penetration of renewable energy sources and the rapid development of electric battery storage technologies yield a potential for reducing electricity price volatility while maintaining stability of the power grid. This work presents an algorithmic approach to control battery levels and forward positions to optimally manage power output fluctuations caused by intermittent renewable energy generation. This paper will also explore the effect of battery technology on the firm's optimal trading behaviour in the electricity spot market.
In this paper, we propose a model of decentralized energy storages, who serve as instruments to shift energy supply intertemporally. From storages' perspective, we investigate their optimal buying or selling decisions under market uncertainty. The goal of this paper is to understand the economic value of future market information, as energy storages mitigate market uncertainty by forward-looking strategies. At a system level, we evaluate different information management policies to coordinate storages' actions and improve their aggregate profitability: (1) providing a publicly available market…
There is a growing interest in the use of largescale battery storage systems for grid services. This technology has been deployed in several countries to increase transmission systems capabilities and reliability. In particular, large-scale battery storage systems could be used for congestion management and the French Transmission System Operator (RTE) is currently installing 3 large batteries for 2020 at the sub-transmission grid level for this purpose. The battery operation for congestion management does not require the full storage capacities at all times. Thus, the residual capacities can …
In future distribution grids, prosumers (i.e., energy consumers with storage and/or production capabilities) will trade energy with each other and with the main grid. To ensure an efficient and safe operation of energy trading, in this paper, we formulate a peer-to-peer energy market of prosumers as a generalized aggregative game, in which a network operator is only responsible for the operational constraints of the system. We design a distributed market-clearing mechanism with convergence guarantee to an economically-efficient and operationally-safe configuration (i.e., a variational generali…
As the distributed energy generation and storage technologies are becoming economically viable, energy trading is gradually becoming a profit making option for end-users. This trend is further supported by the regulators and the policy makers as it aids the efficiency of power grid operations, reduces power generation cost and the Green House Gas (GHG) emissions. To that end, in this paper we provide an overview of distributed energy trading concepts in smart grid. First, we identify the motivation and the desired outcomes of energy trading framework. Then we present the enabling technologies …
The French transmission system operator (RTE) needs to face a significant congestion increase in specific zones of the electrical network due to high integration of renewable energies. Network reconfiguration and renewable energy curtailment are currently employed to manage congestion and guarantee the system security and stability. In sensitive zones, however, stronger levers need to be developed. Large battery storage systems are receiving an increasing interest for their potential in congestion management. In this paper, a model for local congestion management mixing batteries and renewable…
In this paper, we consider the problem of optimal demand response and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic prog…
This paper presents an intelligent home energy management system integrated with dispatchable loads (e.g., clothes washers and dryers), distributed renewable generators (e.g., roof-top solar panels), and distributed energy storage devices (e.g., plug-in electric vehicles). The overall goal is to reduce the total operating costs and the carbon emissions for a future residential house, while satisfying the end-users comfort levels. This paper models a wide variety of home appliances and formulates the economic operation problem using mixed integer linear programming. Case studies are performed t…
Univ. of Minnesota（明尼苏达大学）；University of Virginia（弗吉尼亚大学）
Energy storage devices represent environmentally friendly candidates to cope with volatile renewable energy generation. Motivated by the increase in privately owned storage systems, this paper studies the problem of real-time control of a storage unit co-located with a renewable energy generator and an inelastic load. Unlike many approaches in the literature, no distributional assumptions are being made on the renewable energy generation or the real-time prices. Building on the deep Q-networks algorithm, a reinforcement learning approach utilizing a neural network is devised where the storage …
In this paper we provide non-simultaneous charging and discharging guarantees for a linear energy storage system (ESS) model for a model predictive control (MPC) based home energy management system (HEMS) algorithm. The HEMS optimally controls the residential load and residentially-owned power sources, such as photovoltaic (PV) power generation and energy storage, given residential customer preferences such as energy cost sensitivity and ESS lifetime. Under certain problem formulations with a linear ESS model, simultaneous charging and discharging can be observed as the optimal solution when t…
The fluctuations of electricity prices in demand response schemes and intermittency of renewable energy supplies necessitate the adoption of energy storage in microgrids. However, it is challenging to design effective real-time energy storage management strategies that can deliver assured optimality, without being hampered by the uncertainty of volatile electricity prices and renewable energy supplies. This paper presents a simple effective online algorithm for the charging and discharging decisions of energy storage that minimizes the electricity cost in the presence of electricity price fluc…
We study the optimal control of storage which is used for arbitrage, i.e. for buying a commodity when it is cheap and selling it when it is expensive. Our particular concern is with the management of energy systems, although the results are generally applicable. We consider a model which may account for nonlinear cost functions, market impact, input and output rate constraints and inefficiencies or losses in the storage process. We develop an algorithm which is maximally efficient in then sense that it incorporates the result that, at each point in time, the optimal management decision depends…
Incorporating Renewable Energy Sources (RES) incurs a high level of uncertainties to electric power systems. This level of uncertainties makes the conventional energy management methods inefficient and jeopardizes the security of distribution systems. In this connection, a scenario-based stochastic programming is introduced to harness uncertainties in the load, electricity price, and photovoltaic generation. Further, a hybrid evolutionary algorithm based on Grey Wolf Optimizer and Particle Swarm Optimisation algorithm is proposed to find the best operation cost, and Energy Not Supplied (ENS) a…
Wind integration in power grids is very difficult, essentially because of the uncertain nature of wind speed. Forecasting errors on output from wind turbines may have costly consequences. For instance, power might be bought at highest price to meet the load. On the other hand, in case of surplus, power may be wasted. Energy storage facility may provide some recourse against the uncertainty on wind generation. Because of the sequential nature of power scheduling problems, stochastic dynamic programming is often used as solution method. However, this scheme is limited to very small networks by t…
