Review of energy storage allocation in power distribution networks: applications, methods and future research

Zidar, Matija; Georgilakis, Pavlos S.; Hatziargyriou, Nikos D.; Capuder, Tomislav; Škrlec, Davor

doi:10.1049/iet-gtd.2015.0447

Cited by 245 publications

(119 citation statements)

References 72 publications

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“…The impact of the increased renewable energy on the volatility of the market prices and hence the value of ES is discussed in [7,8]. Further, the application of ES in distribution network is reviewed in [9]. The analysis in [10,11] shows the benefits of ES to increase the revenue for the non-firm distributed renewable generation.…”

Section: Introductionmentioning

confidence: 99%

Business cases for energy storage with multiple service provision

Teng

Štrbac

2016

J. Mod. Power Syst. Clean Energy

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Energy storage (ES) has been considered as the key source of flexibility to support the integration of renewable energy. Previous studies have demonstrated the substantial system cost savings by the deployment of ES, including both investment and operation of generation, transmission and distribution infrastructure. However, this societal benefit may not be realized if industry actors do not have a viable business case to appropriately capture these multiple value streams. In this context, this paper investigates the value that ES may deliver to its owner over two specific business cases in a 2030 UK system. Firstly, the application of large-scale ES in the wholesale market is analysed. It is demonstrated that the optimal allocation of ES to provide multiple services is the key element for ES to become competitive in the electricity market. In the second business case, this paper analyses the value of kilowattscale ES combined with roof photovoltaic (PV) system in the household and community level. The study shows that multiple service provision of ES through advanced pricing schemes, for example time-of-use (ToU) tariff and dynamic distribution use of system (DUoS), lead to higher value and the coordination in the community level could further justify the application of domestic ES.

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Section: Introductionmentioning

confidence: 99%

Business cases for energy storage with multiple service provision

Teng

Štrbac

2016

J. Mod. Power Syst. Clean Energy

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“…Storage and demand response (DR) technologies are considered valuable sources of flexiblility which can be valorized by intelligent energy management (IEM). Although multiple value propositions apply to these resources [1], the valorisation of flexibility is developing slowly. Since it is hard to match a value proposition to a flexible resource with specific parameters such as location, size and technology-specific parameters, no off-the-shelf solutions are available.…”

Section: Introductionmentioning

confidence: 99%

Computing the value of flexibility in electricity retail, ahead and balancing markets

Veen

Kaisers

2016

2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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Abstract-Renewable generation of energy is becoming more affordable, and is therefore increasingly adopted to match local demand. In addition, storage and demand response solutions have reached the market, which provides flexibility and thereby facilitates intelligent energy management. It has been suggested that this bottom-up flexibility should contribute to the balancing of the future smart grid, but financial incentives have so far been elusive. This article presents computations that assess the profitability of intelligent energy management for three different value propositions: increasing self-sufficiency under typical retail tariffs, or participating in ahead or balancing market price fluctuations, specifically in the Netherlands, Germany and Italy. First, an upper bound valuation of flexibility is computed from 2013 market data. Second, a technology-neutral profit analysis is proposed and demonstrated on selected technologies. Our simulations indicate the highest value for flexibility in the Dutch and German imbalance markets (7.7 & 9.4 ec/kWh) and the Dutch reserve market (10.4 ec/kWh), and for small prosumers in the German and Italian retail markets (12 & 10 ec/kWh). Results indicate that there is sufficient value in demand response if activation costs are sufficiently low, which innovative tariffs should exploit to provide incentives for bottom-up balancing of the future smart grid.

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“…The resolution of this highly dimensional non-convex problem has been successful with multiple mathematical techniques including analytical techniques, classical techniques, artificial intelligence techniques and other miscellaneous techniques [9]. In a different review of energy storage allocation, four main categories are defined to solve this highly dimensional non-convex problem: analytical methods, mathematical programming, exhaustive search and heuristics [10]. The different existing methods are of different complexity, some being simple, i.e.…”

Section: Introductionmentioning

confidence: 99%

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm. Applied Energy, Elsevier, 2018Elsevier, , 219, pp.385-393. <10.1016Elsevier, /j.apenergy.2017 .008>. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm Etta Grover-Silva 1,2 , Robin Girard 1 , George Kariniotakis 1 AbstractThe high variability and uncertainty introduced into modern electrical distribution systems due to decentralized renewable energy generators requires new solutions for grid management and power quality assurance. One of these possible solutions includes grid integrated energy storage. The appropriate size and placement of decentralized storage is highly dependent on purpose of the battery system and expected operational strategy. However, battery operational strategies are difficult to simulate simultaneously during a sizing and placement planning calculation. The motivation of this paper is to propose an algorithm that is capable of integrating sizing, placement and operational strategies of batteries into an Optimal Power Flow (OPF) distribution grid planning tool. The choice of the OPF approach permits to account for grid constraints which is more adapted for grid-connected storage devices compared to other approaches in the state of the art that are based only on an email balance analysis. This paper presents an alternating current (AC) multi-temporal OPF algorithm that uses a convex relaxation of the power flow equations to guarantee exact and optimal solutions with high algorithmic performance. The algorithm is unique and innovative due to the fact that it combines the simultaneous optimization of placement and sizing of storage devices taking into account load curves, photovoltaic (PV) production profiles, and distribution grid power quality constraints. The choice to invest in battery capacity is highly sensitive to the price of battery systems. The investment in battery systems solely for reducing losses an operational costs was proven not to be cost effective, however when battery systems are allowed to buy and sell electricity based on variable market prices they become cost effective. The assumptions used for this study shows that current battery system prices are too high to be cost effective even when allowing battery system market participation.Keywords: Optimal power flow, storage, smart grids, renewable energy, distribution grid planning Nomenclature Parameters η st Charging and discharging efficiency of the battery system P pv,j,t Ideal PV production for node j at time step t S pv,j,t PV maximum apparent power flow at node j V j Voltage maximum at node n V j Voltage minimum at node n c inv stInvestment costs of the battery system for the nominal capacity in e/MWh-day Operations and maintenance costs of using the battery system for the power use in e/MWh-day c e,tPrice of electricity at time step t I max Total capital cost limit of project P ld,j,t Active power load at n...

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Review of energy storage allocation in power distribution networks: applications, methods and future research

Cited by 245 publications

References 72 publications

Business cases for energy storage with multiple service provision

Business cases for energy storage with multiple service provision

Computing the value of flexibility in electricity retail, ahead and balancing markets

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

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