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换能在海洋能源开发中的技术创新一、海洋能源开发概述海洋能源，作为地球上最丰富的可再生能源之一，具有巨大的开发潜力。
随着全球对清洁能源需求的不断增长，海洋能源的开发利用受到了越来越多的关注。
海洋能源主要包括潮汐能、波浪能、海流能、海洋温差能和盐度梯度能等多种形式。
这些能源具有分布广泛、可再生性强、环境影响小等特点，是未来能源结构调整和能源安全的重要保障。
1.1 海洋能源开发的重要性海洋能源的开发利用对于缓解全球能源危机、减少温室气体排放、推动经济可持续发展具有重要意义。
海洋能源的大规模开发不仅可以提供稳定的能源供应，还能促进相关产业的发展，创造就业机会，带动地区经济增长。
1.2 海洋能源开发的现状与挑战当前，海洋能源的开发尚处于起步阶段，面临着技术、经济、环境等多方面的挑战。
技术层面上，海洋环境的复杂性给能源开发带来了诸多难题，如设备的耐腐蚀性、稳定性和维护问题。
经济层面上，海洋能源项目的成本高，回报周期长，风险较大。
环境层面上，如何减少对海洋生态系统的影响，实现可持续发展，也是需要解决的问题。
二、海洋能源开发的关键技术创新为了克服现有挑战，推动海洋能源的高效开发，技术创新显得尤为重要。
以下是一些关键的技术创新方向：2.1 高效能量转换技术海洋能源的高效转换是开发利用的核心技术。
通过不断的技术革新，提高能量转换效率，降低能量损失，是提升海洋能源开发经济性的关键。
例如，新型潮汐能发电技术、波浪能发电装置等，都在不断优化中。
2.2 智能监控与维护系统海洋环境的恶劣和设备的复杂性要求有一套完善的智能监控与维护系统。
利用物联网、大数据和技术，实现对海洋能源开发设备的实时监控、故障预警和智能维护，可以大大提高设备的运行效率和安全性。
2.3 海洋能源综合利用技术单一的海洋能源开发往往难以满足大规模能源需求。
通过技术创新，实现海洋能源的综合利用，如潮汐能与波浪能的联合开发，可以提高能源的利用效率，降低开发成本。
海洋能源开发及其环境影响评估一、现状分析1.1 海洋能源的发展现状海洋能源作为一种清洁、可再生的能源形式，受到越来越多国家和地区的重视和关注。
目前，主要的海洋能源开发形式包括海上风电、潮汐能、波浪能和海洋温差能等。
海上风电是目前最为成熟的海洋能源开发形式，已经在一些国家实现了较大规模的商业化应用。
而潮汐能、波浪能和海洋温差能在技术上尚处于起步阶段，但在不断进行研发和试验。
1.2 现有问题分析随着海洋能源开发的推进，也暴露出一些问题。
海洋能源开发对海洋生态环境造成一定的影响，如海上风电对海鸟迁徙和海洋生物的影响、波浪能发电装置对海洋生态系统的破坏等。
海洋能源开发还涉及到海域使用权、工程建设、国土资源保护等方面的问题，存在管理难度大、资源利用矛盾等困难。
1.3 因素分析影响的因素主要包括技术、、市场、环境等方面。
在技术方面，海洋能源开发需要具备先进的装备和技术支持；在方面，需要有明确的规划和支持；在市场方面，需要市场需求和投资回报的保障；在环境方面，需要充分考虑生态环境的可持续性和完整性。
二、存在问题2.1 海洋能源开发对环境的影响海洋能源开发可能导致海洋生态系统的破坏，影响海洋生物的生存和繁衍。
比如，海上风电可能对海鸟迁徙路线产生干扰，影响其迁徙和栖息。
波浪能和潮汐能的发电设备可能对海洋生态系统产生一定的干扰。
2.2 海洋能源开发存在的可持续性问题部分海洋能源开发项目缺乏合理规划和科学评估，可能导致资源浪费和环境破坏。
如果海洋能源开发不遵循可持续性原则，可能会造成能源资源丧失和环境破坏，影响未来的可持续发展。
2.3 海洋能源开发管理存在的问题海洋能源开发涉及多个部门和利益相关方，管理难度大。
在海域使用权、审批程序、环境监测等方面存在管理薄弱、执行力度不够、信息披露不透明等问题。
三、对策建议3.1 强化环境影响评估和监测对海洋能源开发项目进行全面的环境影响评估，对项目可能对生态环境造成的影响进行评估和预测，确保项目在实施过程中最大限度地减少对环境的影响。
海洋能源开发对环境的影响研究在当今世界，随着能源需求的不断增长和传统能源的逐渐枯竭，海洋能源的开发已成为全球关注的焦点。
海洋能源，如潮汐能、波浪能、海流能、温差能等，具有巨大的潜力和广阔的发展前景。
然而，如同任何一种能源开发活动一样，海洋能源开发也不可避免地会对环境产生影响。
海洋能源开发对海洋生态系统的影响是多方面的。
首先，在开发过程中，需要在海洋中建设大量的基础设施，如潮汐电站的大坝、波浪能发电装置等。
这些设施的建设可能会改变海洋的水流、波浪和潮汐等自然动力条件，从而影响海洋生物的栖息地和迁徙路线。
例如，一些鱼类可能会因为水流的改变而难以找到适宜的繁殖和觅食场所，导致其种群数量下降。
其次，海洋能源开发过程中的施工活动也可能会对海洋生物造成直接伤害。
施工过程中产生的噪音、振动和废弃物可能会干扰海洋生物的正常生活，甚至导致它们受伤或死亡。
此外，海洋能源开发设施在运行过程中也可能会对海洋生物产生影响。
比如，一些发电装置的旋转部件可能会对海洋生物造成碰撞伤害。
海洋能源开发还可能对海洋水质产生影响。
在建设和维护海洋能源设施时，可能会使用一些化学物质和材料，这些物质如果泄漏到海洋中，可能会造成海洋污染，影响海洋生态系统的健康。
同时，设施的运行也可能会导致局部海域的水温、盐度等物理化学参数发生变化，从而影响海洋生物的生存和繁殖。
除了对海洋生态系统的直接影响外，海洋能源开发还可能引发一些间接的环境问题。
例如，为了支持海洋能源开发项目，可能需要进行大规模的海岸带开发和基础设施建设，这可能会导致土地利用方式的改变、湿地的破坏以及海岸线的侵蚀等问题。
此外，海洋能源开发项目的建设和运营也需要消耗大量的资源和能源，从而产生一定的温室气体排放，对全球气候变化产生影响。
然而，我们不能因为海洋能源开发可能带来的环境影响而否定其发展的必要性。
相反，我们应该通过科学规划、合理布局和严格的环境监管，来最大程度地减少其对环境的不利影响，并实现海洋能源开发与环境保护的协调发展。
海洋能源开发的技术进展在当今全球能源需求不断增长，传统能源面临资源枯竭和环境压力的背景下，海洋能源作为一种潜力巨大、清洁可再生的能源形式，正日益受到人们的关注。
海洋能源主要包括潮汐能、波浪能、海流能、温差能和盐差能等，其开发利用不仅能够缓解能源危机，还有助于减少温室气体排放，保护生态环境。
近年来，随着科技的不断进步，海洋能源开发的技术取得了显著的进展。
潮汐能是海洋能源中最早被开发利用的形式之一。
潮汐发电的原理是利用潮汐的涨落产生的水位差来推动水轮机旋转，从而带动发电机发电。
目前，潮汐发电技术已经相对成熟，一些大型潮汐电站已经投入运行。
例如，法国的朗斯潮汐电站是世界上最大的潮汐电站之一，装机容量达到 240 兆瓦。
此外，我国也在浙江、福建等地建设了一些潮汐电站，为当地的电力供应做出了贡献。
然而，潮汐能开发也面临一些挑战。
潮汐电站的建设需要特定的地理条件，如海湾或河口，且工程规模较大，投资成本高。
此外，潮汐的周期性和不稳定性也给电力的稳定输出带来了一定的困难。
为了解决这些问题，科学家们正在不断探索新的技术和方法。
例如，采用新型的水轮机设计，提高能量转换效率；发展储能技术，以平衡潮汐能发电的不稳定性；利用智能化的控制系统，优化电站的运行和管理。
波浪能是另一种具有巨大潜力的海洋能源。
波浪能的获取方式多种多样，常见的有振荡水柱式、点头鸭式、筏式等。
振荡水柱式波浪能装置是通过波浪的上下运动推动空气在水柱内往复流动，从而驱动涡轮机发电。
点头鸭式装置则是利用装置在波浪作用下的俯仰运动来转化能量。
近年来，波浪能技术取得了不少突破。
一些新型的波浪能装置在能量转换效率和可靠性方面有了显著提高。
例如，英国的 Pelamis 波浪能装置采用了柔性的连接结构，能够更好地适应海洋环境，提高了发电效率。
然而，波浪能开发仍面临诸多难题。
波浪的能量分布不均匀，且受到海洋气候的影响较大，使得能量的收集和利用存在较大的不确定性。
此外，波浪能装置在恶劣的海洋环境中容易受到腐蚀和损坏，维护成本较高。
可再生能源利用上海电力2009 年第 1 期海洋能源的利用与开发Sonal Patel摘要:海洋蕴藏着巨大的能量,海洋能源不仅清洁环保,而且是一种取之不竭的可再生清洁能源。
文章介绍了多种海洋再生能源的前沿技术及其应用情况,并分析了海洋能发展的现状以及对环境影响的主要因素。
关键词:海洋再生能源;波浪能;潮汐能;潮流能;海水温差能;海水盐差能中图分类号: P743文献标识码: B随着人们日益关注环境、经济以及依赖化石能源引发的成本问题,开发利用可再生能源已逐渐成为当前行业的发展趋势。
在取得推广应用风能发电和太阳能发电圆满成功后,如何从覆盖地球面积70%以上的海洋中获取再生能源,成了能源行业关注的焦点。
目前,世界各大新能源开发商正在就此进行着积极的探索,并已经取得了初步的成果。
1海洋再生能源发展概况海洋中的可再生自然能源主要包括波浪能、潮汐能、潮流能(海流能)、海水温差能和海水盐差能。
据测算,海洋能的蕴藏总量高达 4 000 TW,开发潜力巨大。
海洋能源不仅清洁环保、可再生,更重要的是海洋能中的波浪能、潮汐能和潮流能还具有风能和太阳能无法比拟的优势,即可预测性。
由月球引力变化造成的潮汐可以提前好几年进行预报;而洋流图则可以通过卫星进行绘制。
可预测性有助于防范大规模的停电事故的发生。
此外,无论是海上涡轮机或是浸没式零排放涡轮机,因其处于人们看不到的地方而不具有视觉污染。
事实上,试图利用海洋能发电的想法早在100 年前便有之, 因当时技术和资金等问题, 其开发进程十分缓慢。
例如:在1912年,德国在北海海岸建造了世界上第一座潮汐电站布苏姆潮汐电站。
以加拿大的芬迪湾建造潮汐电站为例,其建设规划可追溯到1925年。
当时缅因州同意投资1 亿美元在该州帕萨马科迪湾( Passam aquo ddy Bay) 建立潮汐电站; 1935 年罗斯福总统也对该项目表示支持并拨款1 000万美元,但是该项目最终未能实现。
同时期的英国布里斯托尔海峡潮汐电32站计划,因不具有经济、可行性而被否决。
海上可再生能源国外研究发展趋势海上可再生能源是指利用海洋资源进行能源开发和利用的能源形式，主要包括海风能、海浪能、潮汐能和海洋温差能等。
近年来，海上可再生能源在国外得到了广泛的研究和发展。
本文将从海风能、海浪能、潮汐能和海洋温差能等方面介绍海上可再生能源的国外研究发展趋势。
一、海风能海风能是利用海洋上的风力进行能源转换的一种方式。
国外一些发达国家如丹麦、德国、英国等，已经在海上建设了大规模的海上风电场，并取得了显著的成果。
这些国家利用先进的风力发电技术，将风能转化为电能，为国家的电力供应做出了重要贡献。
同时，他们还致力于研发更高效的风力发电设备和系统，以提高海上风力发电的利用效率。
二、海浪能海浪能是指利用海洋上的波浪运动进行能源转换的一种方式。
近年来，国外一些国家对海浪能的研究和开发取得了一定的进展。
他们主要通过浮标、波浪能发电机等设备，将海浪能转化为电能。
目前，国外一些地区已经建立了一些小型的海浪能发电站，用以验证海浪能发电技术的可行性和效果。
未来，海浪能有望成为一种重要的可再生能源，在国外的研究和发展中具有重要的地位。
三、潮汐能潮汐能是指利用海洋上的潮汐运动进行能源转换的一种方式。
国外一些地区如法国、加拿大等，已经开始在海上建设潮汐能发电设施。
通过利用潮汐能发电机等设备，将潮汐能转化为电能，并注入电网供电。
潮汐能作为一种可再生能源，具有稳定、可预测的特点，因此在国外的研究和发展中备受关注。
然而，潮汐能发电技术的商业化仍然面临一些挑战，需要进一步的研究和改进。
四、海洋温差能海洋温差能是指利用海洋表面和深海之间的温差进行能源转换的一种方式。
国外一些国家如日本、韩国等，已经开始研究和开发海洋温差能。
他们主要通过海洋热能转换器等设备，将海洋温差能转化为电能，用于供电和其他用途。
海洋温差能具有巨大的潜力，可以提供稳定的、持续的能源供应。
但是，海洋温差能的开发仍然面临技术难题和经济成本等挑战，需要进一步的研究和改进。
欧洲国家的海洋能源利用与可持续发展欧洲国家一直以来致力于发展可持续能源，其中海洋能源是一个备受关注的领域。
海洋能源是指利用海洋中的自然能源来产生电力或其他形式的能源。
海洋能源的利用可以减少对传统化石燃料的依赖，减少对环境的污染，进一步推动可持续发展。
在欧洲国家中，风能是最受关注的海洋能源之一。
风能利用风力产生电力，具有无污染、可再生的特点。
欧洲国家的海岸线长而且风力丰富，使其成为风力发电的理想场所。
丹麦是欧洲领先的风能开发国家之一，其丰富的海风资源为国家电力供应做出了重要贡献。
与此同时，德国、英国等国家也逐渐发展起风力发电产业，通过各种政策和投资引导，加速了可再生能源市场的发展。
除了风能，潮汐能也是海洋能源的重要组成部分。
潮汐能指的是通过利用潮汐运动产生的动能来发电。
英国是世界上最大的潮汐能开发国家之一，其位于苏格兰海峡的潮汐能发电项目非常成功。
该项目利用潮汐能源为当地提供可再生的电力，减少了对传统能源的依赖，同时也降低了碳排放。
潮汐能是一种较为稳定的能源形式，相较于风能具有更高的可靠性。
此外，欧洲国家还在开发波浪能和温差能等海洋能源形式。
波浪能是指利用海洋波浪产生的机械能来产生电力，具有较高的能量密度。
葡萄牙是一个在波浪能开发方面取得重要成果的国家，其长达800多公里的海岸线提供了丰富的波浪能资源。
温差能是指利用海洋温差来产生电力，通过利用海水表面与深层水温度差异的热交换来产生能量。
挪威是一个在温差能开发方面具有潜力的国家，其海洋热能资源丰富。
海洋能源的利用不仅可以降低碳排放和减少对传统能源的依赖，还可以推动经济发展和增加就业机会。
海洋能源的开发过程需要大量的技术支持和工程建设，促进了相关产业的发展。
同时，海洋能源的利用也为当地创造了许多就业岗位，提升了就业率和经济水平。
然而，要实现海洋能源的可持续利用，还需要克服一些挑战。
首先，技术研发和成本降低依然是海洋能源发展的关键问题。
虽然欧洲国家在海洋能源技术方面取得了巨大进展，但是仍然需要不断创新和改进。
海洋能源开发对海洋生态系统的影响有哪些一、关键信息1、海洋能源开发类型：包括但不限于海上风电、潮汐能、波浪能、海洋温差能等。
2、海洋生态系统组成部分：海洋生物、海洋环境（水质、水温、盐度等）、海洋生态系统服务功能（如氧气产生、碳储存等）。
3、影响类型：直接影响（如对海洋生物栖息地的破坏）、间接影响（如噪声污染对海洋生物行为的改变）、长期影响（如生态系统结构和功能的变化）、短期影响（如施工期间的干扰）。
二、海洋能源开发概述1、海洋能源的潜力和发展趋势全球海洋能源资源的丰富性和分布特点。
海洋能源在未来能源结构中的重要地位和发展前景。
2、常见的海洋能源开发技术和方法海上风电的发电原理和设施建设。
潮汐能、波浪能、海洋温差能的开发原理和技术手段。
三、海洋生态系统简介1、海洋生态系统的结构和功能不同海洋生态系统类型（如浅海、深海、珊瑚礁等）的特点和生物多样性。
海洋生态系统在物质循环、能量流动和维持生态平衡方面的作用。
2、海洋生物的适应性和生态位海洋生物对环境变化的适应能力和生存策略。
各种海洋生物在生态系统中的地位和相互关系。
四、海洋能源开发对海洋生态系统的直接影响1、对海洋生物栖息地的破坏设施建设导致的海底地形改变和海洋底质破坏。
占用海洋生物的繁殖、觅食和栖息空间。
2、对海洋生物的伤害和死亡施工过程中的碰撞和碾压对海洋生物造成的直接伤亡。
能源开发设备运行对海洋生物的机械伤害。
五、海洋能源开发对海洋生态系统的间接影响1、噪声污染施工和设备运行产生的噪声对海洋生物听觉和行为的干扰。
噪声对海洋生物通讯、导航和繁殖行为的影响。
2、电磁场干扰电力传输和设备产生的电磁场对海洋生物生理和生态过程的影响。
电磁场对海洋生物洄游和定向行为的潜在影响。
六、海洋能源开发对海洋生态系统的长期影响1、生态系统结构和功能的变化物种组成和群落结构的改变。
食物链和食物网的重组。
2、生态系统服务功能的受损氧气产生、碳储存和水质净化等服务功能的下降。
海洋能技术的现状及前景分析随着世界能源需求的不断增长，传统能源资源已经开始紧缺，为了满足未来能源需求和环保的双重目标，人们开始挖掘更多的可再生能源，海洋能技术就是其中非常重要的一种。
本文将分析海洋能技术的现状及前景。
一、海洋能技术的定义及分类海洋能技术指的是利用海洋资源和海洋力量来生产能源的一种技术，包括潮汐能、浪能、温差能、盐度差能等。
潮汐能是指海洋潮汐的差异产生的能量；浪能是指海洋波浪的能量；温差能是指海洋不同温度层之间温差的能量；盐度差能是指海洋不同盐度层之间盐度差的能量。
二、海洋能技术的现状及应用目前，海洋能技术在世界范围内得到了广泛的应用。
2017年，全球潮汐能的装机容量已经达到了1.5GW，其中法国是最大的潮汐能生产国。
挪威、英国和加拿大等国家也在积极推进潮汐能、浪能、温差能等技术的开发和应用。
海洋能技术目前的应用领域主要集中在电力生产方面。
海上风力发电作为一种成熟的技术已经应用广泛，海洋潮汐发电、海浪发电等技术正在快速发展。
此外，海洋能技术也可以应用于海洋水深探测、海洋环境监测等领域。
三、海洋能技术的前景随着全球对可再生能源的需求不断增长，海洋能技术有望成为未来的一种主流能源。
目前海洋能技术还处于起步阶段，但是已经有许多国家和地区开始着手开发和应用这种新型能源技术。
未来，海洋能技术将面临许多挑战。
首先要解决的是技术问题，包括如何提高海洋能技术的转化效率、如何提高海洋能技术的稳定性等。
其次是海洋环境问题，如何保护和管理海洋生态环境，避免对海洋产生不可逆转的破坏。
总的来说，海洋能技术的前景是十分广阔的。
未来随着技术的进步和社会的推广，海洋能技术将有望成为可再生能源领域的重要组成部分，为人类的能源安全和可持续发展作出贡献。
Assessing the impacts of technology improvements on the deployment of marine energy in Europe with an energy system perspective*Alessandra Sgobbi*,Sofia G.Sim~o es1,Davide Magagna,Wouter NijsEuropean Commission,Joint Research Centre,Institute for Energy and Transport,Westerduinweg3,1755LE Petten,The Netherlandsa r t i c l e i n f oArticle history:Received13August2014 Received in revised form10March2015Accepted28November2015 Available online xxxKeywords:Marine energyOcean energyLow-carbonEnergy system modelTIMESEU28a b s t r a c tMarine energy could play a significant role in the long-term energy system in Europe,and substantial resources have been allocated to research and development in thisfield.The main objective of this paper is to assess how technology improvements affect the deployment of marine energy in the EU.To do so the linear optimization,technology-rich model JRC-EU-TIMES is used.A sensitivity analysis is performed, varying technology costs and conversion efficiency under two different carbon-emissions paths for Europe:a current policy initiative scenario and a scenario with long-term overall CO2emission re-ductions.We conclude that,within the range of technology improvements explored,wave energy does not become cost-competitive in the modelled horizon.For tidal energy,although costs are important in determining its deployment,conversion efficiency also plays a crucial role.Ensuring the cost-effectiveness of tidal power by2030requires efficiency improvements by40%above current expecta-tions or cost reductions by50%.High carbon prices are also needed to improve the competitiveness of marine energy.Finally,our results indicate that investing0.1e1.1BEuro2010per year in R&D and inno-vation for the marine power industry could be cost-effective in the EU,if leading to cost reduction or efficiency improvements in the range explored.©2015The Authors.Published by Elsevier Ltd.This is an open access article under the CC BY-NC-NDlicense(/licenses/by-nc-nd/4.0/).1.IntroductionClimate change and energy policies are strongly interlinked: energy-related greenhouse gases(GHG)emissions in the EU272 accounted for almost80%of the total in2011([1]and[2]).More-over,40%of2010GHG emissions could be attributed to energy industries alone(electricity and refineries mainly)[3].To address the challenge,the EU is defining a new set of energy policies that will provide additional impetus to the decarbonisation of the power system.In Refs.[4],the European Commission addresses energy and climate change policies in concert,with a view to reaching a reduction of GHG emissions of40%in2030with respect to1990levels.It recognises that the rapid development of renew-able energy sources poses new challenges to the energy system, notably the integration of decentralised and variable production in the electricity system.The Communication also highlights the need to ramp up research and development(R&D)and innovation in-vestments beyond2020,while at the same time setting priorities to accelerate cost reduction and market uptake of key low-carbon technologies.The power sector has a critical role to play in ensuring meeting short and long-term energy and climate objectives in the EU. Marine energy encompasses a group of low-carbon technologies that could play a significant role in the transition of the power sector in Europe,contributing to energy security as well as to the reduction in emissions of greenhouse gases.As indicated in Refs.[5],the sector could also generate40,000jobs by2035.It is thus important to better understand how key parameters affect investment decisions in marine technologies in an energy system perspective.*The views expressed are purely those of the authors and may not in any cir-cumstances be regarded as stating an official position of the European Commission. *Corresponding author.E-mail address:alessandra.sgobbi@ec.europa.eu(A.Sgobbi).1Currently at CENSE e Center for Environmental and Sustainability Research, Departamento de Ci^e ncias e Engenharia do Ambiente,Faculdade de Ci^e ncias e Tecnologia,Universidade NOVA de Lisboa,2829-516Caparica,Portugal2Austria,Belgium,Bulgaria,Cyprus,Czech Republic,Denmark,Estonia,Finland, France,Germany,Greece,Hungary,Ireland,Italy,Latvia,Lithuania,Luxembourg, Malta,Netherlands,Poland,Portugal,Romania,Slovakia,Slovenia,Spain,Sweden, and UnitedKingdom.Contents lists available at ScienceDirectRenewable Energyjournal h omepage:w/locate/renene/10.1016/j.renene.2015.11.0760960-1481/©2015The Authors.Published by Elsevier Ltd.This is an open access article under the CC BY-NC-ND license(/licenses/by-nc-nd/4.0/).Renewable Energy89(2016)515e525The main objective of this paper is therefore to assess,within a systematic and coherent energy system framework,how technol-ogy cost and conversion ef ficiency affect the competiveness and deployment of marine energy technologies in the EU.Such analysis is intended to provide insights on priorities for R &D and innovation to accelerate the market readiness of marine technologies.To the best of our knowledge,no comprehensive assessment has yet been carried out exploring the role of marine energy for the medium and long term decarbonisation of the European energy system within an energy system perspective,though country-level studies adopting similar approaches do exist,for instance,for the United Kingdom [6].A similar approach was used to determine the po-tential contribution of wave energy in the US energy system by using the NREL Re-EDS model as shown in Refs.[7],whilst the EIA [8]considered the potential contribution of wave and tidal tech-nologies at global level,albeit showing limited contributions up to 2040.The remainder of the paper is organised as follows.Section 2brie fly summarises the state of play of marine energy in the EU28,3and highlights the expected developments in the medium and long term.Section 3outlines the key elements of the JRC-EU-TIMES model,describes the policy assumptions underlying the two decarbonisation pathways explored in the paper,and sum-marises the sensitivity analyses performed.Section 4presents the main results,focussing on the impacts of marine technologies im-provements on its deployment.Section 5concludes the paper.2.Marine energy:state of playWave and tidal energy technologies are the two forms of marine energy expected to provide signi ficant contribution to the EU en-ergy system in the next few decades [9].Several European coun-tries,in particular those located on the Atlantic Arc of the continent,bene fit from vast resources and have a signi ficant potential for the development of marine energy technologies.The United Kingdom,for example,has an estimated tidal energy economic potential of 18TWh/year,while 50TWh/year could become economically viable for wave ([10]and [11]).According to Ocean Energy Europe,wave and tidal technologies could reach up to 100GW of installed ca-pacity by 2050,with over 260TWh delivered to the grid [12].However,in the past few years,2020projections have been signi ficantly reduced from 3GW of expected capacity [13,14]to 240MW [15],with forecasts for the UK alone reducing from 1.95GW [16]to 140MW [17].Despite reduced targets,Europe maintains a leadership position in the development of the marine energy sector and many Euro-pean countries are at the forefront of innovation [18].The United Kingdom,Ireland,France and Norway present hubs for both tech-nology development and market mechanisms to facilitate the deployment of full-scale prototypes and devices,such as MEAD in the UK,4and the newly launched Offshore Energy Renewable En-ergy plan in Ireland [19].A number of technologies are moving from prototype demon-stration towards pre-commercial pilot arrays in order to prove reliability,survivability and affordability;however the high costs associated with ocean energy and technological fragmentation are currently hindering both access to finance and market uptake.As shown in Fig.1,tidal technologies appear closer to commerciali-sation presenting a greater design convergence,having proved operation generating signi ficant electricity supplied to the grid andwith a series of array demonstration projects in the pipeline.On the other hand,wave technologies have yet to show the same level of reliability,and the current lack of design consensus is delaying the engagement with the manufacturing and supply chain to provide substantial cost-reduction and favour their market uptake [7].While the performance of marine energy technologies is ex-pected to improve steadily over time,their market-readiness and competitiveness will depend on whether such improvements lead to suf ficient cost reductions and/or ef ficiency gains.The currently observed trends show the development of the sector to be below initial expectations.According to a recent report by the Strategic Initiative for Ocean Energy [20],cost of energy predictions for marine energy indicate that tidal technology could be competitive with other renewable energy sources (RES)when a cumulative capacity of 2.5e 5GW is reached,whilst wave requires 5e 10GW to ensure competiveness.There is therefore the need for stepping up efforts in innovation,R &D and demonstration to accelerate learning and cost reduction,thus enabling marine energy to play its role in the medium and long-term decarbonisation of Europe.Consolidating Europe's position as the leading centre for innovation is therefore critical.3.Methodology and approach 3.1.The JRC-EU-TIMES modelThis section brie fly describes the key characteristics of the JRC-EU-TIMES model,its main inputs and outputs.Special attention is devoted to how the modelling framework addresses marine energy technologies.An extensive description of the model can be found in Ref.[21].The JRC-EU-TIMES model is a linear optimization,bottom-up,technology-rich model generated with the TIMES model gener-ator from ETSAP (Energy Technology Systems Analysis Program),an implementing agreement of the International Energy Agency ([22],[23]).It represents the energy system of the EU28plus Switzerland,Iceland and Norway (EU28þ)from 2005to 2050,with each country constituting one region of the model.Each year is divided in 12time-slices that represent an average of day,night and peak de-mand for every season of the year.The equilibrium is driven by the maximization (via linear pro-gramming)of welfare,de fined as the discounted present value of the sum of producers and consumers surplus.The maximization is subject to several constraints,including:upper limits on the supply of primary resources;constraints governing technology deploy-ment;balance constraints for energy and emissions;and the satisfaction of energy services demands in the modelled sectors of the economy (primary energy supply;electricity generation;in-dustry;residential;commercial;agriculture;and transport).The most relevant model outputs are:the annual stock and activity of energy supply and demand technologies for each region and period;the associated energy and material flows,including emissions to air and fuel consumption for each energy carrier;operation and maintenance costs,investment costs,energy and materials commodities prices.The main drivers and exogenous inputs are summarised in Fig.2.3.1.1.Energy services and materials demandThe materials and energy demand projections for each country are differentiated by economic sector and end-use energy service,using as a start point historical 2005data and macroeconomic projections from the GEM-E3model [25]as detailed in Refs.[21],and in line with the values considered in the EU Energy Roadmap 2050reference scenario [26].From 2005till 2050the exogenous3As in,2plus Croatia.4https:///innovation-funding-for-low-carbon-technologies-opportunities-for-bidders#the-marine-energy-array-demonstrator-mead-scheme .A.Sgobbi et al./Renewable Energy 89(2016)515e 525516useful energy services demand grows 32%for agriculture,56%for commercial buildings,28%for other industry,24%for passenger mobility and almost doubles (97%)for freight mobility.On the other hand,the exogenous useful energy services demand for residential buildings is 12%lower in 2050than in 2005due to the assumptions on improving the building stock's thermal characteristics.3.1.2.Energy supply and demandCountry and sector-speci fic energy balances are derived from energy consumption data from Eurostat,determining the energy technology pro files for supply and demand technologies in the base year.Beyond the base year,new energy supply and demand tech-nologies are compiled in an extensive database with detailed technical and economic characteristics.The electricity production sector is divided in accordance toproducer types and generating plant types.Main Activity Producers generate electricity and/or heat for sale to third parties,through the public grid,as their primary activity.Autoproducers generate electricity and/or heat,wholly or partly for their own use.Both types of producers may be privately or publicly owned.The types of plants are classi fied according to fuel input,technology group and whether the plant is electricity only or Combined Heat and Power (CHP).The categories of the plants follow closely the RES2020[27]and Energy 2050Roadmap [26]nomenclature.The most relevant source of the database for electricity generation technologies is [14],and the detailed figures,including technology costs,can be found in Ref.[21].The technology-speci fic discount rates are aligned with the values considered in the PRIMES model as in Ref.[26].The social discount rate is set at 5%.76%16%4%2%2%Tidal energy conceptsHorizontal axis turbine (76%)Other Designs (16%)Enclosed Tips (4%)Oscilla Ɵng Hydrofoil (2%)Ver Ɵcal axis turbine (2%)40%23%19%7%7%3%1%Wave energy conceptsPoint absorber (40%)A Ʃenuator (23%)Oscilla Ɵng Wave Surge Converter (19%) Oscilla Ɵng water column (7%) Rota Ɵng mass (7%) Other (2%)Bulge wave (1%)Fig.1.Technology fragmentation in wave and tidal energy technology (Source:[18]).Fig.2.The JRC-EU-TIMES model structure.(Source:[24]).A.Sgobbi et al./Renewable Energy 89(2016)515e 5255173.1.3.Primary energy potentials and costsThe JRC-EU-TIMES model considers country-specific,current and future potentials and costs of primary energy(renewable and fossils),both imported and endogenous.Fossil primary energy import prices are exogenous,and aligned to the values considered in Ref.[26].The extraction and conversion of primary energy re-sources are modelled explicitly.The prices of these commodities are endogenous,and depend on country-specific resource extrac-tion and conversion costs.At this moment unconventional gas in Europe is not considered.Bioenergy is also modelled explicitly.Moreover,in addition to production in the modelled regions,forestry residues can be im-ported.Bioenergy conversion pathways includefirst,second and third generation biorefineries.The direct use of ligno-cellulosic biomass is also envisaged.Finally,a number of assumptions and sources are adopted to derive the renewable energy(RES)potentials in the EU28for wind, solar,geothermal,marine and hydro(Table1).3.2.Marine energy in JRC-EU-TIMES and modelled scenariosTwo,aggregate,marine energy technologies are modelled explicitly:wave and tidal(without differentiating tidal stream and range).Their baseline techno-economic parameters are detailed in Table2and Table3.These values have been elaborated based on a literature review and expert assumptions,and are aligned to the assumptions underlying[14].The maximum electricity production of marine energy technologies in JRC-EU-TIMES is determined by their capacity/efficiency(or availability)factor.This aggregate fac-tor represents both the hours of the year in which the renewable resources is available(e.g.waves or tides),and the necessary stops for maintenance[29].For marine plants we consider in JRC-EU-TIMES a generic efficiency modelled as a capacity factor appli-cable to each country where marine energy is possible,as in Table3, based on JRC own expert assessment.Fig.3depicts the maximum generated electricity per year at the regional level in2050.Predicting the evolution of techno-economic parameters for technologies is a challenging task.Learning curves are often pro-posed in the literature,as a means of estimating expected im-provements of techno-economic parameters via learning-by-research and/or learning-by-doing(see,for instance[34],and [35]for energy technologies).Marine energy presents however specific challenges:the sector is still in its infancy,there is no active market yet,and the lack of convergence in the design,as well as the limited current installed capacity beyond the pilot level,make it difficult to estimate learning curves,either based on research or deployment or both.For this reasons,a learning rate of12%was adopted,in accordance to bottom-up estimates provided by the Carbon Trust and SI Ocean report[36].In addition,we did not model learning curves endogenously for several reasons:i)we perfom a partial study for only one group of energy technologies, whereas endogenous learning would have to apply to all technol-ogies in an energy system model;ii)our model represents only EU, whereas technology learning is a global phenomenon,and iii)our model has perfect foresight and including endogenous learning curves,without additional assumptions on system inertia,could lead to over-investment in the early stages as this would lower their cost significantly in later periods.Two different climate policy scenarios are considered,as sum-marised in Table4.The Current Policy Initiatives scenario(CPI) includes the20e20e20policy targets([30][31][32],and[33]).The CAP scenario is consistent with the medium and long-term CO2 emissions reduction underlying[4],reaching a CO2reduction of 80%below1990values in2050.The two scenarios have the following assumptions in common: i)No consideration of the specific policy incentives to RES(e.g. feed-in tariffs,green certificates);ii)a maximum of50%electricity can be generated from variable solar and wind,to account for concerns related to system adequacy and variable RES.Moreover, wind and solar PV cannot operate during the winter peak time slice;and iii)countries without nuclear power plants will not have these in the future(Austria,Portugal,Greece,Cyprus,Malta,Italy, Denmark and Croatia).Nuclear power plants in Germany and Belgium are not operating after2020and2025respectively.For each scenario,we vary technology costs and capacity factor in turn.Technology costs are assumed to decrease in5%step in-tervals with respect to the baseline levels from2015onwards (Table2).The original evolution of the efficiency for both tidal and wave energy technologies implies an improvement of5%every decade:for the sensitivity analysis,this rate of improvement isTable1Overview of the technical RES potential considered in JRC-EU-TIMES.RES Methods Main data sources Assumed maximum possible technical potentialcapacity/activity for EU28Wind onshore Maximum activity and capacityrestrictions disaggregated for differenttypes of wind onshore technologies,considering different wind speedcategories [27]until2020followed by expert-basedown assumptions205GW in2020and283GW in2050Wind offshore Maximum activity and capacityrestrictions disaggregated for differenttypes of wind offshore technologies,considering different wind speedcategories [27]until2020followed by expert-basedown assumptions52GW in2020and158GW in2050PV and CSP Maximum activity and capacityrestrictions disaggregated for differenttypes of PV and for CSP Adaptation from JRC-IET of[27]115GW and1970TWh in2020and1288GWin2050for PV;9GW in2020and10GW in2050for CSPGeothermalelectricity Maximum capacity restriction in GW,aggregated for both EGS andhydrothermal withflash power plants[27]until2020followed by expert-basedown assumptions1.6GW in2020and2.9GW in2050for hotdry rock;1.5GW in2020and1.9GW in2050for dry steam&flash plants.301TWh generatedin2020and447TWh in2050Marine Maximum activity restriction in TWh,aggregated for both tidal and wave [27]until2020followed by JRC-IET expert-basedown assumptions117TWh in2020and170TWh in2050Hydro Maximum capacity restriction in GW,disaggregated for run-of-river and lakeplants[28]22GW in2020and40GW in2050for run-of-river.197GW in2020and2050for lake.449TWhgenerated in2020and462TWh in2050A.Sgobbi et al./Renewable Energy89(2016)515e525518assumed to increase in 5%steps up to the maximum ef ficiency indicated in Table 3.Within each policy scenario,we then compare the changes in the energy system brought about by the variations in either the technological costs or the capacity factor with respect to the baseline results of each of the two policy scenarios in turn.Before the results we would like to point out that such long-term modelling approaches as of the JRC-EU-TIMES model inher-ently have signi ficant uncertainties.These are not only depending on expectations on the future development of energy technologies,as well as their respective RES potentials,but also on macroeco-nomic evolution,willingness to invest in RES or CO 2mitigationpolicies.Naturally,long-term modelling should not be used to forecast the future,rather to support energy planners and policy makers in envisioning possible alternatives with the best available information.In our model,the detailed assumptions on future techno-economic parameters for energy technologies in Europe are derived from expert opinion and/or available evidence and sectoral studies.These implicit assumptions are important drivers of the results e therefore providing further arguments for the sensitivity analysis approach adopted in this paper.4.Results and discussionNew marine energy technologies do not become competitive by 2050with the baseline cost and ef ficiency assumptions,unless a long-term mitigation cap is imposed (CAP scenario).Meeting the long-term CO 2emission target calls in our model for the deploy-ment of the full portfolio of low-carbon power technologies,including marine.In the CAP scenario in the EU28,67.4GW of new tidal energy capacity is installed in 2050,generating 155TWh (Table 5).The total generated electricity is close to the maximum technical potential of 170TWh.In our model,with current estimates for techno-economic pa-rameters,the CO 2emission cap is met through two decarbonisation paths.Firstly,the electri fication of the energy system.The share of electricity in final energy consumption increases from 20%in 2010Table 2Economic characteristics of marine energy technologies (EUR2010/kW).YearWave energyTidal energySpeci fic investments costs (overnight)Fixed operation and maintenance costs Speci fic investments costs (overnight)Fixed operation and maintenance costs Ref.Min.Ref.Min.Ref.Min Ref.Min 2020407020357638328516436231203033501675673329601480592920403062153157282700135050252050220011004723220011004723Ref.:cost assumptions in the baseline case.Min.:cost assumptions in the most optimistic case (50%cost reduction).Table 3Technical characteristics of marine energy technologies.YearCapacity factor Technical lifetimeWave energy Tidal energy Ref.Maximum Ref.Maximum 20200.220.350.220.453020300.230.470.230.473020400.240.500.240.473020500.250.500.250.5030Ref.:capacity factor assumptions in the baseline case.Min.:capacity factor assumptions in the most optimistic case (50%increase in ca-pacityfactor).Fig.3.Maximum possible generated electricity from marine energy considering the maximum possible technical potential and generic capacity factor.A.Sgobbi et al./Renewable Energy 89(2016)515e 525519to35%in2050in the capped scenario,as opposed to21%in the CPI scenario.Secondly,the large scale deployment of renewable energy sources electricity(RES-e)(Table6).The share of RES-e increases from25%in2010to49%in2030,and66%in2050.Electricity generated from solar and wind is the main source for the increase. In the CAP scenario,the share of wind and solar generated elec-tricity increases from6%in2010to22%in2030and49%in2050.In comparison,the contribution of electricity generated from marine,which is considered more predictable than solar and wind,is substantially smaller,with only3%of total generated electricity in 2050.In the remainder of this section we explore the level of cost reduction of efficiency improvements that could bring about a large scale deployment of tidal energy,and assess the implication on the whole energy system.For this purpose,we define large scale deployment as a minimum of half of the maximum achievable potential,i.e.59TWh in2020and85TWh in2050.4.1.Deployment of marine energy technologies and implications at the EU levelAt the outset,it is important to highlight that,in the current analysis,wave energy technologies never become competitive in the range of efficiency improvements or cost reductions explored. Tidal and wave technologies are perfect substitutes:they compete for the same marine resource,and provide the same output e low-carbon electricity e in the same countries.As in our scenarios,tidal energy is always cheaper than wave energy(with the exception of 2050,see Table2),the potential for wave energy is not realised.The result is therefore driven by the underlying assumptions:an improved representation of the potentials for wave and tidal,taking into account the fact that the two are not always competing for the same marine energy nor are available in the same countries at the same level,could lead to different results.Baseline assumptions on the evolution over time of techno-economic parameters of other, low-carbon technologies also play a role in the relative competi-tiveness of wave energy,which is always more expensive than the marginal technology(tidal energy).With the modelling assump-tions adopted in this research,wave energy would only become competitive for cost reductions higher than60%of the reference technology costs in2030under a long term decarbonisation cap (CAP scenario),and assuming that the cost of tidal energy tech-nologies does not improve beyond50%.In the CPI scenario,the cost reduction needed to make wave energy competitive in2030are even higher e80%of the reference cost in that year.The remainder of the paper will focus on tidal energy technol-ogies.Fig.4shows the impact of changes from the baseline in in-vestment and O&M costs and in the capacity factor on tidal energy generated electricity(Fig.4)(a)and deployment(Fig.4)(b)in2030 (top)and2050(bottom)for the two scenarios.Firstly,tidal energy technologies become cost-effective in the EU28already in2030in the presence of a long termÀ80%CO2cap (CAP scenario)coupled with technological improvements.In the CAP scenario,tidal energy is deployed in2030starting from15% efficiency improvements(CAPEFF)or cost reduction(CAPCOST). The deployment remains however limited:only cost reductions above30%or efficiency improvements above25%would lead to a total generated electricity of at least half the maximum potential. On the other hand,bringing forward the deployment of tidal energy to2030in the absence of a long-term CO2cap(CPI scenario)re-quires significant technological improvements(halving of the costs or at least45%efficiency improvements)e but in all cases at levels well below50%of the total generating potential.Secondly,over the long-run(2050),tidal energy technologies would become competitive even in the absence of a long-term CO2 cap for more modest technological improvements:with a mid-term CO2cap,cost reductions and efficiency improvements above 25%(CPICOST)and10%(CPIEFF)would be sufficient.In all of these cases,though,generated electricity is well below half of the maximum potential of tidal energy e0.9TWh in the CPI scenario. Only for cost reductions of at least45%(CPI)and efficiency im-provements of15%(CPI)would tidal energy generate more than half of its technical potential.Thirdly,in the absence of a long-term CO2cap(CPI),improving efficiency beyond25%does not have significant additional impacts on the level of deployment in the long-term compared with the baseline with a mid-term CO2target(CPIEFF).It is important to point out that,as the maximum capacity for Europe is defined on the activity rather than on the installed ca-pacity,electricity generation can never exceed170TWh in2050. This level of activity is however achieved with very different installed capacities in the case of capacity factor improvements (Fig.4)(b).Changes in the deployment of marine energy impact the overall electricity generation mix,and this impact is stronger in2030than it is in2050,in particular in the CAP scenario(Fig.5).This is becauseTable4Policy scenarios modelled in JRC-EU-TIMES.Scenario name20e20e20targets aLong term CO2cap Other assumptionsCurrent PoliciesInitiatives(CPI)Yes,ETS till2050No Until2025the only new NPPs to be deployed in EU28are the ones being built in FI and FR and underdiscussion in BG,CZ,SK,RO and UK.b After2025all plants under discussion can be deployed but no other.Current Policieswith CAP(CAP)As CPI80%less CO2emissions in2050than1990levels cAs in CPIa The EU ETS target is assumed to continue until2050.The national RES targets are implemented for2020and2030(the target for2030is the same as in2020).There are no such targets after2030.The minimum share of biofuels in transport is implemented from2020and maintained constant until2050.b This corresponds to the following plants:in Bulgaria(Belene-1,Belene-2);Czech Republic(Temelin-3,Temelin-4),Finland(Olkiluoto-3),France(Flamanville-3,Penly-3), Hungary(Paks-5,Paks-6),Romania(Cernavoda-3,Cernavoda-4),Slovakia(Mochovce-3,Mochovce-4)and UK(Hinkleypoint-C1,Hinkleypoint-C2,Sizewell-C1,Sizewell-C2).c The80%cap includes CO2emissions from international aviation and navigation.Table5Tidal energy generated electricity(TWh)considering the baseline efficiency and costs.'2010'2020'2030'2040'2050CPI0.630.630.630.630.63 CAP0.630.630.630.87155.10Table6Share of RES-e and solar&wind electricity(shown in brackets)in total electricity generation.20302050CPI42%(17%)44%(23%) CAP49%(22%)66%(49%)A.Sgobbi et al./Renewable Energy89(2016)515e525 520。
