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National modeling by Lawrence Berkeley National Laboratory (LBNL) found that least-cost, operationally feasible pathways for India’s power sector through 2030 consist primarily of investments in renewable energy and flexible resources (with limited additions to coal capacity), including: renewable generation (450-530 GWDC solar and wind, 15 GW other RE), energy storage (60-85 GW), load shifting (60 GW), interstate transmission (140 GW), more flexible operation of existing natural gas generation (25 GW), and development of a more liquid national electricity market. The LBNL national study illustrates that with increases in power system flexibility, India can meet — or even exceed — Prime Minister Modi’s announced target of 450 GW of installed renewable energy capacity by 2030, while reducing costs and increasing power system reliability. While the modeling study provides a long-term vision, policy and regulatory changes would be needed to achieve that vision, and our recommendations focus on three main areas: resource adequacy (RA), state resource planning and procurement, and short-term markets and system operations. Well-designed system planning and RA frameworks, coordinated with state-level resource planning and procurement and supported by electricity markets, are critical to scaling renewables deployment with less curtailment and less financial and operational stress on conventional assets. System planning and RA frameworks can help facilitate generation capacity sharing among states, increasing utilization of existing generation assets. They also ensure that electricity supply remains reliable and resilient in response to extreme weather events (e.g., heat and cold waves) and as higher capacities of variable renewable generation are added to the Indian electricity system. Enhancing state-level resource planning and procurement practices would enable states/Discoms to construct least-cost portfolios of renewable, thermal, and storage resources that meet national RA requirements. Electricity markets and system operations provide the connective tissue, assuring that all planned and procured RA capacity will be available when needed and will be operated when economic to do so. In the longer term, markets must be more closely aligned with real-time operations and facilitate energy storage participation.

This paper decomposes the effects of the transition from an average cost distribution tariff to a cost causation-based distribution tariff, in terms of time and location, that uses nodal prices to recover losses and an 'extent-of-use' method to recover fixed network costs based on use at coincident peak. Our decomposition is designed so that the effects of using coincident peak and location for fixed network charges, as well as using marginal losses under constraints recovering the exact amount of losses, and recovering exactly the cost of network service in total can be isolated and analyzed separately. We apply our tariff transition and decomposition method to an example network with data from Uruguay to isolate the various effects with and without a distributed generation (DG) resource. We show moving to coincident peak charges and to fully charging for marginal losses while rebating the merchandising surplus through the fixed charges have the greatest effects on changes in distribution tariff charges. DG provides countervailing cost changes to distribution tariffs for loads through loss reductions and the implicit 'creation' of new network capacity for which it is paid. The interaction of all these effects may lead to outcomes that are counter-intuitive, which further supports the need to decompose the tariff changes to fully understand the reasons for the direction and magnitude of changes in tariff charges in the transition to tariffs based more on cost causation. Index Terms--Distributed generation, distribution networks, fixed cost allocations, loss allocations, tariffs.

In this paper, we propose a method for the allocation of fixed (capital and nonvariable operation and maintenance) costs at the medium voltage (MV) distribution level. The method is derived from the philosophy behind the widely used MW-mile methodology for transmission networks that bases fixed cost allocations on the 'extent of use' that is derived from load flows. We calculate the 'extent of use' by multiplying the total consumption or generation at a busbar by the marginal current variations, or power to current distribution factors (PIDFs) that an increment of active and reactive power consumed, or generated in the case of distributed generation, at each busbar, produces in each circuit. These PIDFs are analogous to power transfer distribution factors (PTDFs). Unlike traditional tariff designs that average fixed costs on a per kWh basis across all customers, the proposed method provides more cost-reflective price signals and helps eliminate possible cross-subsidies that deter profitable (in the case of competition) or cost-effective (in the case of a fully regulated industry) deployment of DG by directly accounting for use and location in the allocation of fixed costs. An application of this method for a rural radial distribution network is presented. Index Terms--Allocation of fixed costs, distributed generation (DG), distribution networks.

The existence of market clearing prices that support competitive equilibrium prices in electric power market with nonconvexities is addressed.

New federal regulations will boost competition. Getting public power to sign up, however, remains critical. Authorized by the Energy Policy Act of 1992, the Federal Energy Regulatory Commission has ordered [...]

As distributed generation (DG) becomes more widely deployed, distribution networks become more active and take on many of the same characteristics as transmission. We propose the use of nodal pricing that is often used in the pricing of short-term operations in transmission. As an economically efficient mechanism, nodal pricing would properly reward DG for reducing line losses through increased revenues at nodal prices and signal prospective DG where it ought to connect with the distribution network. Applying nodal pricing to a model distribution network, we show significant price differences between buses reflecting high marginal losses. Moreover, we show the contribution of a DG resource located at the end of the network to significant reductions in losses and line loading. We also show the DG resource has significantly greater revenue under nodal pricing, reflecting its contribution to reduced line losses and loading. Index Terms--Distributed generation (DG), distribution networks, loss allocations, nodal pricing.

Energy Services for the Urban Poor in Africa: Issues and Policy Implications. Kebede, Bereket and Ikhupuleng Dube (eds.). London: Zed Books, Ltd in association with African Energy Policy Research Network [...]