Today's quickly changing world forces society to deal with uncertainties that produce high levels of environmental, social, and economic risks, thereby jeopardizing sustainable development. Portfolio optimisation is an effective tool for formally dealing with such uncertainties, because the social and private optimum is not found by analysing cost/returns and risks of individual assets, projects, actions or plans, but rather requires analysing them all together in the form of a portfolio. This paper presents a review of portfolio optimisation applications from the perspective of energy regulation in an attempt to guide the electricity sector towards sustainable development. Liberalized electricity markets have different sources of uncertainties, ranging from the traditional (e.g. fuel prices, electricity demand, and resource availability, etc.) to the latest sources of risks linked to a society that is more concerned about sustainability. We have found multiple research opportunities, especially in spatial modelling, transmission, and renewable generation, as well as others related to new social and environmental impacts and risks. The portfolio literature available to date excessively simplifies the power system. Supply, demand, and transmission modelling in portfolio analysis are not consistent with planning models, and therefore produce conflicting results. Additionally, despite abundant literature that analyses renewable complementarity, actual portfolio optimisation models ignore this effect, which leads to suboptimum portfolios. Environmental and social costs and risks, such as air and water pollution, land use, community values, and public opposition, among others, have also been ignored.

当今瞬息万变的世界迫使社会应对造成高水平环境，社会和经济风险的不确定性，从而危及可持续发展。投资组合优化是正式处理此类不确定性的有效工具，因为无法通过分析单个资产，项目，行动或计划的成本/收益和风险来找到社会和私人最优，而是需要以投资组合。本文从能源监管的角度对投资组合优化应用进行了综述，以试图指导电力部门实现可持续发展。自由化的电力市场具有多种不确定性来源，包括传统的不确定性（例如燃料价格，电力需求和资源可用性等）。）到与更关注可持续性的社会相关的最新风险来源。我们发现了多种研究机会，尤其是在空间建模，传输和可再生能源发电方面，以及与新的社会和环境影响及风险相关的其他研究机会。迄今可获得的投资组合文献极大地简化了电源系统。项目组合分析中的供应，需求和传输模型与计划模型不一致，因此产生矛盾的结果。此外，尽管有大量文献分析了可再生的互补性，但实际的投资组合优化模型却忽略了这种影响，从而导致了次优投资组合。环境和社会成本和风险，例如空气和水污染，土地使用，社区价值以及公众的反对，