Our recent survey of property developers indicates that decentralized investment in urban photovoltaics in a high-density city can be hindered by various economic barriers, including space constraints, high upfront capital cost, high operational cost, and uncertain profit. Private investment incentives can be boosted by integrative business models such as energy communities that pool resources and energy loads among property owners and users to exploit economies of scale and specialization. This chapter examines the potential efficiency gains from energy-community integration in a three-layer planning framework: (1) spatial planning to benefit from reducing the spatial mismatch between intermittent solar energy supply and demand load profile, (2) investment planning for the most profitable distributed energy resources investment strategies and for profit sharing to promote stakeholder participation incentives, and (3) operational planning for optimal energy system performance through internal dynamic pricing and demand-response management. These three planning layers can be integrated to maximize the benefit of urban photovoltaics investment. To demonstrate this, a spatial planning analysis of the one-north district in Singapore shows the potential for a 25% reduction in annual energy costs per gross floor area, an 8% increase in annual energy self-sufficiency, and a 26% reduction in hourly peak load in an energy community through urban land-use planning. An investment planning analysis for a university campus shows that an energy-community business model can reduce energy costs compared to no PV deployment, rooftop solar leasing, and private PV ownership by 32, 21, and 11%, respectively. And an operational planning analysis for the same campus shows substantial energy-cost savings from adopting an energy community for internal dynamic pricing. However, the cost savings vary among the participants depending on their contributions to solar electricity generation and their demand profiles.

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How to Plan: An Integrated Three-Layer Planning Framework to Overcome Economic Barriers

  • Jidong Kang,
  • Yuming Fu,
  • Tien Foo Sing

摘要

Our recent survey of property developers indicates that decentralized investment in urban photovoltaics in a high-density city can be hindered by various economic barriers, including space constraints, high upfront capital cost, high operational cost, and uncertain profit. Private investment incentives can be boosted by integrative business models such as energy communities that pool resources and energy loads among property owners and users to exploit economies of scale and specialization. This chapter examines the potential efficiency gains from energy-community integration in a three-layer planning framework: (1) spatial planning to benefit from reducing the spatial mismatch between intermittent solar energy supply and demand load profile, (2) investment planning for the most profitable distributed energy resources investment strategies and for profit sharing to promote stakeholder participation incentives, and (3) operational planning for optimal energy system performance through internal dynamic pricing and demand-response management. These three planning layers can be integrated to maximize the benefit of urban photovoltaics investment. To demonstrate this, a spatial planning analysis of the one-north district in Singapore shows the potential for a 25% reduction in annual energy costs per gross floor area, an 8% increase in annual energy self-sufficiency, and a 26% reduction in hourly peak load in an energy community through urban land-use planning. An investment planning analysis for a university campus shows that an energy-community business model can reduce energy costs compared to no PV deployment, rooftop solar leasing, and private PV ownership by 32, 21, and 11%, respectively. And an operational planning analysis for the same campus shows substantial energy-cost savings from adopting an energy community for internal dynamic pricing. However, the cost savings vary among the participants depending on their contributions to solar electricity generation and their demand profiles.