Multi-Criteria Decision-Making Problem for Energy Storage Technology Selection for Different Grid Applications (original) (raw)
Related papers
Renewable and Sustainable Energy Reviews, 2019
Energy storage systems (ESS) are seen as one of the main pillars for a renewable-based energy system. Selecting the most suitable and sustainable ESS for a given project is a problem that involves multiple stakeholders with quite often diverging objectives that cannot all be fulfilled by a single technology. Several studies are available that tackle this problem applying multi-criteria decision analysis (MCDA). However, these use very different Multi-Attribute Decision Making (MADM) approaches, criteria and goals for decision support, why their results are difficult to compare or to reproduce. This work presents a review of existing MCDA-literature using MADM as a tool for sustainability evaluation of grid-tied ESS. Available studies are summarized, the goals, used MADM methods, and quantification of criteria are analyzed and discussed to provide tentative recommendations. The reviewed studies cover multiple technologies ranging from electrochemical, mechanical or electric ESS. Considered criteria are mainly structured around technology, economy, society, and environment, comprising a high number of individual sub-criteria. The aggregation of these criteria is mainly realized through the Analytic Hierarchy Process (AHP) in combination with a wide set of other methods. The quantification of various criteria is often based on different literature sources wherein context-free data for cost, and environmental impacts are used, leading in some cases to inconsistent comparisons in the assessments. Only in a few cases, assessments are linked to specific application requirements, which are decisive factors for the design of an ESS. A minority of the reviewed works include a representative set of decision-makers in their approaches, wherein the number or type of participants is often not communicated transparently. Therefore, most of the studies are considered to have a limited orientation towards practical decision making, but they provide valuable information regarding MADM method development.
Multiple Criteria Analysis for Energy Storage Selection
Energy and Power Engineering, 2011
In view of the current and predictable energy shortage and environmental concerns, the exploitation of renewable energy sources offers great potential to meet increasing energy demands and to decrease dependence on fossil fuels. However, introducing these sources will be more attractive provided they operate in conjunction with energy storage systems (ESS). Furthermore, effective energy storage management is essential to achieve a balance between power quality, efficiency, costs and environmental constraints. This paper presents a method based on the analytic hierarchy process and fuzzy multi-rules and multi-sets. By exploiting a multiple criteria analysis, the proposed methods evaluate the operation of storage energy systems such as: pumped hydro and compressed air energy storage, H 2 , flywheel, super-capacitors and lithium-ion storage as well as NaS advanced batteries and VRB flow battery. The main objective of the study is to find the most appropriate ESS consistent with a power quality priority. Several parameters are used for the investigation: efficiency, load management, technical maturity, costs, environmental impact and power quality.
Energy Technology
Herein, a multicriteria decision-making analysis (MCDA) of eight different utilityscale battery storage technologies for four different application areas, involving 72 relevant stakeholders from industry and academia for criteria selection and weighting, is presented. The assessment is conducted for economic, environmental, technological, and social criteria using a combination of the analytic hierarchy process and technique for order preference by similarity to ideal solution. It includes a full life-cycle costing and life-cycle assessment using current data. Indicative rankings show that most lithium-ion batteries can be recommended for all application areas. Lead-acid batteries achieve rather low scores depending on the viewed application, but including a recycling scenario for this technology might lead to significant changes in final scores and rankings. This is also true for the redox flow battery. Furthermore, the weights provided by the stakeholders are very dispersing, leading to a low consensus about the relevance of the used criteria. In particular, social criteria are not well differentiated in the current state and do not add significant distinguishing features between different battery technologies.
Clean Technologies and Environmental Policy, 2016
Power to gas (P2G)-methane, pumped hydroelectric storage (PHES) and compressed air energy storage (CAES) are three methods to store surplus electricity with high capacity and long discharge time. However, there is a few research included P2G-methane in comparing with other storage technologies in general and in terms of sustainability development. This paper explored and compared the cost, efficiency, position flexibility, storage capacity/ discharge time, energy carrier vector and environmental issues of those storage technologies in terms of single criterion and group multi-criteria analysis. The single criterion data of each technology was reviewed from literature and compared with each other. The data from single criterion were normalised then used as inputs of the linear additive model. The weights of criteria were determined by sending out the weighting assessment form to 10 researchers. The comparison in terms of cost and efficiency showed that PHES is better than P2G and CAES. And P2G has many benefits such as: conversion of energy vector from electricity to gas which is available for renewable thermal and transport energy; longest storage time; and minimal impact on the environment. From sustainable development strategy perspective, the evaluation results of P2G, PHES and CAES are 4.03, 2.46 and 2.16, respectively. Which means P2G was assessed as preferable. Keywords Power to gas (P2G) Á Pumped hydroelectric storage (PHES) Á Compressed air energy storage (CAES) Á Electricity storage Á Multi-criteria Á Sustainability Electronic supplementary material The online version of this article (
Brazilian Archives of Biology and Technology, 2021
The Brazilian Power Sector is preparing the introduction of battery energy storage in its distribution lines for energy quality control. The technical and financial viability of this new technology depends on several factors: battery technologies, geographical locations, environmental restrictions and the local regulation. One of the objectives of the present project was to create a methodology for helping technicians to choose the best battery technology for each particular application. The Analytic Hierarchy Process-AHP algorithm was selected to take into account all the above-mentioned factors. This methodology was applied to a case study considering four different commercially available battery energy storage systems (BESS) and the methodology was able to recommend the best choice by taking into account all the criteria and subcriteria considered. The second objective of the present project is to evaluate a real hybrid BESS operation composed of two different battery technologies. Up to the moment when this paper was submitted the BESS has not been installed yet. The installation place has already been selected, a feeder-line with 1,360 kW peak power, and monitored for energy quality. The BESS has been sized, a 250 kW/1 MWh flow battery together with a 250 kW/500 kWh lithium-ion battery and the purchase process has been initiated. Both battery technologies will work in separate and joint operations for power quality in on-grid and island cases. HIGHLIGHTS The Brazilian electricity regulatory agency calls for energy storage projects Electric utilities evaluate battery energy storage for power quality control The Analytic Hierarchy Process (AHP) algorithm for battery technology: a strategic choice • Environmental, Technological, Regulatory and Financial AHP criteria 2 Oening A.P.; et al.
International Journal of Engineering Research and Technology (IJERT), 2021
https://www.ijert.org/a-decision-support-system-for-ranking-the-different-battery-energy-storage-technologies-using-critic-and-edas-method https://www.ijert.org/research/a-decision-support-system-for-ranking-the-different-battery-energy-storage-technologies-using-critic-and-edas-method-IJERTCONV9IS11044.pdf Electric Power Distribution Utility Companies (EPDUC) performing in the deregulated energy market always strive to provide a stable as well as steady power supply to its consumers cost competitive price. One of the latest approach to achieve the objective of providing cost-competitive reliable power supply is to integrate Battery Energy Storage Systems (BESS) with grids at both micro and macro level. However, due to involvement of multiple stakeholders in a power business there arises a problem of decision making to choose from a plethora of BESS technologies. An automated condition monitoring system (CMS) of a modern EPDUC deploys a combination of Internet of Things (IoT), Cloud computing, and Big-Data Analytics (BDA) based Decision support system (DSS) to make a choice for most techno-commercially viable BESS suitable as per dynamics of the demand in its network. This paper presents a DSS applying a hybrid approach of two Multi criteria decision making (MCDM) strategies namely CRITIC and EDAS for selecting the most BESS technology available in the network.
Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach
Energies
This paper explores business models for community energy storage (CES) and examines their potential and feasibility at the local level. By leveraging Multi Criteria Decision Making (MCDM) approaches and real-world case studies in Europe and India, it presents insights into CES deployment opportunities, challenges, and best practices. Different business models, including community energy cooperatives, utility–community partnerships, demand response, energy services, and market mechanisms, are analyzed. The proposed method combines the MCDM method PROMETHEE II with the fuzzy set theory to obtain a complete CES business model ranking, addressing project uncertainties. The analysis emphasizes CES’s role in balancing local renewable energy supply and demand, facilitating energy sharing, and achieving energy independence. Findings prioritize models like Community Cooperative, Energy Arbitrage, and Energy Arbitrage Peak Shaving for CES with renewables. Environmental benefits include reduce...
Journal of Renewable and Sustainable Energy, 2020
Electrical energy storage is a promising solution to overcome the intermittency and demand-supply mismatch problem in hybrid renewable energy systems. The objective of the present study is to prioritize ten electrical energy storage systems by using an innovative ranking framework, considering different criteria. Further, a techno-economic study of a hybrid renewable energy system is performed for rural area electrification, where the present selection strategy of the storage system is incorporated in the system design. Due to the conflicting nature of these criteria, a fuzzy assisted Technique for Order of Preference by Similarity to Ideal Solution method based framework is employed for its prioritization. The effect of variation of the weights on the criteria is also investigated through a sensitivity analysis. The framework is used to design an optimum hybrid renewable energy system for a remote village in India using the Hybrid Optimization Model for Electric Renewables tool. The results of the ranking show that pumped hydro storage, compressed air energy storage, and lead-acid batteries are the top three electrical energy storage systems that present more benefits for renewable energy integration for the present case. Moreover, adopting a storage system selection strategy can further reduce the cost of energy of the system. Therefore, the present framework provides a systematic procedure of storage system selection for renewable energy integration by considering different conflicting criteria for case-specific application.
Distributed Generations (DG) are modular power generating technologies that are located near the load centers. DGs help avoid the expensive long distance transmission of power which is expensive and lossful while providing certain relief to the central power grid. They can be reliable and environmental friendly. DGs can prove beneficial for the local economies, enhance the energy independence, provides lowcost electricity at the same time providing access to liberalized generation markets for the concerned distribution utilities. There is wide range of DG options available. When presented with wide range of DG options selecting the correct one can prove to be daunting task. In this paper Multi-Criteria Decision Making (MCDM) technique which is increasingly popular is used for ranking DG systems. The DG systems considered in this paper are reciprocating engines (RE), micro turbine (MT), fuel cell (FC), solar PV (PV) and wind turbine (WT) while the criteria used for ranking are cost, minimum starting time, noise, emission level and continuity. The analysis is done with the aid of MCDM technique employing Fuzzy TOPSIS while weight values of the criteria are determined using the Interval Shannon's Entropy methodology. As per results obtained the first criterion in preference ranking of DG systems is PV, followed by FC, RE, MT and WT.