The following sections present the benchmark of the performance of the states under each of the three readiness categories: policy and incentives, market maturity, and institutional capacity. Here, the readiness of individual states is expressed in percentage of the total index-based score in each category. Policy and Incentives This readiness category comprising of six readiness factors broadly captures the state of play in the states concerning the existence of specific policies, mandates or incentive mechanisms.
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The promise of Utility driven Demand Side Management (DSM) in India includes effective management of electricity deficit, rising power supply costs, energy subsidies, climate change, environmental degradation and energy security concerns, all of which are indispensable problems faced by electricity distribution utilities (also referred as 'DISCOMs' in this report), governments and society as whole in the foreseeable future. The emergence of Energy Efficiency Services Limited as public sector energy services company (ESCO) to design, finance and implement utility scale DSM solutions and further lead investment related actions has proved to be a silver bullet towards breaking the institutional and financial logjam to scale up utility DSM resources in India. By adopting unique market driven approaches, derived from globally successful and innovative DSM delivery models, EESL has achieved unprecedented scale of success in advancing Utility DSM solutions in the recent past. The EESL's UJALA initiative 1 has become the quintessential DSM program for Indian utilities driven entirely by market based mechanisms. The program has sold over 100 million 7 watt and 9 watt LED lamps to replace less efficient incandescent and CFL lamps among households and institutional consumers. The program is currently delivering over 35 million kWh of energy savings per day that translates to more than INR 14 crore in energy cost savings per day, and 2667 MW of avoided generation capacity. The success of UJALA has reinforced stakeholder confidence in the promise of DSM and reestablished the Utility DSM market potential from INR 44000 crores, estimated in 2010, to INR 1.6 lakh crores by considering the end use energy efficiency opportunities alone. Residential end use appliances, agriculture/irrigation pumping and municipal infrastructure are the top three DSM markets contributing to this potential. The renewed DSM market potential is envisaged to deliver 178 billion units of electrical energy savings per annum that roughly translates to 18-20% of the current levels of all India annual electricity consumption and 150 Million tons of annual CO2 emissions reduction potential. Apart from this, demand response, solar photovoltaic (SPV) rooftop systems along with emerging smart grid technologies offer tremendous potential for Utility DSM in India. The market potential for rooftop SPV systems is 124 GWp and the realistic national demand response potential is yet to be evaluated in a comprehensive manner. Given that the market driven mechanisms have gained significant momentum, India is at the cross roads for adopting the right policy approach that can effectively complement the market mechanisms in ensuring the promise of DSM is delivered to Indian stakeholders. Demand side resources lack the kind of impetus laid for promotion of renewable energy sources in the legal and policy framework (Electricity Act 2003, Electricity Amendment Bill, National Tariff Policy Amendments etc.) governing the power sector. Therefore, on the policy front, there is a n...
Curtailment of discrete customer’s demand coincidence with utility demand during peak time ends up in good benefits to the utility at different levels as this coincidence is very expensive due to additional requirement of demand. Though few Demand Response(DR) programs are working towards this peak time energy coincidence reduction, they are not that successful due to either requirements of technological installations near customer premises or penalising the customer or lack of encouraging the customer to achieve the reduction. This work proposes a Personified Behavioural Demand Response (P-BDR) model especially for residential customers as they are good contributors of peak time demand. Rather than coaxing or compelling the customer, the proposed model relies on customer’s motivation regarding the peak time energy conservation, setting targets based on their monthly contribution to utility peak time demand and measuring their achievements through feedback models. P-BDR model comprises of Target/Goal setting model based on forecasted data and feedback model based on real time data of individual customer. This model is observed on synthetic smart meter data of 20 discrete domestic customers. For the better application of the model, customers are clustered into 4 categories using K-Means Machine learning algorithm. The model sets an individual target of 5%-15% energy consumption reduction during utility peak time based on the customer classification. The model achieves an overall consumption reduction of 14.9% during peak time with the proposed model.
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